[go: up one dir, main page]

WO2023141376A2 - Méthodes et systèmes de traitement d'affections respiratoires à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies - Google Patents

Méthodes et systèmes de traitement d'affections respiratoires à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies Download PDF

Info

Publication number
WO2023141376A2
WO2023141376A2 PCT/US2023/060363 US2023060363W WO2023141376A2 WO 2023141376 A2 WO2023141376 A2 WO 2023141376A2 US 2023060363 W US2023060363 W US 2023060363W WO 2023141376 A2 WO2023141376 A2 WO 2023141376A2
Authority
WO
WIPO (PCT)
Prior art keywords
patient
cough
group
combinations
independently selected
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2023/060363
Other languages
English (en)
Other versions
WO2023141376A3 (fr
Inventor
Steven BASTA
Simon Levy
Julie Miller
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Mahana Therapeutics Inc
Original Assignee
Mahana Therapeutics Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Mahana Therapeutics Inc filed Critical Mahana Therapeutics Inc
Publication of WO2023141376A2 publication Critical patent/WO2023141376A2/fr
Publication of WO2023141376A3 publication Critical patent/WO2023141376A3/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • a patient when a patient is diagnosed with one or more medical conditions, the patient may be referred to additional health professionals for further care and treatment.
  • a patient may be referred to a psychologist, psychiatrist, counselor, or other mental health professional.
  • a patient may also be directed to one or more support groups to assist with any psychological distress that the patient may be experiencing. While these traditional face-to-face options may be greatly beneficial to a patient, often times they do not provide enough psychological support.
  • a patient when a patient is alone, at home, or not otherwise engaged directly with their mental health professional or support group, they may experience a significant degree of one or more negative emotional states, such as fear, anxiety, panic, and depression. Additionally, left unidentified and untreated, these negative emotional states often exacerbate the physical symptoms associated with a patient’s diagnosis, which in turn can lead to greater psychological distress.
  • respiratory health conditions including, but not limited to chronic obstructive pulmonary disease (COPD), asthma, asthma-COPD overlap syndromes (ACOS), medication-induced chronic cough (e.g., due to angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), omeprazole, leflumide, etc.), idiopathic chronic cough, and chronic cough, (e.g., the chronic cough associated with one or more other health conditions such as respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, gastroesophageal reflux (GERD), etc.), have significant impact on the quality of life of patients worldwide.
  • COPD chronic obstructive pulmonary disease
  • ACOS asthma-COPD overlap syndromes
  • ACE angiotensin converting enzyme
  • ARBs angiotensin receptor blockers
  • omeprazole omeprazole
  • chronic cough is a severely debilitating condition that can result from multiple different etiologies and cause patients to cough in excess of hundreds to thousands of times daily.
  • Most cases of chronic cough can be explained by common respiratory and non- respiratory disease conditions, such as chronic rhino sinusitis, asthma, chronic obstructive pulmonary disease (COPD), chronic bronchitis, obesity, gastroesophageal reflux disease (GERD), lung cancer, heart failure, medications (e.g. angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), omeprazole and leflumide) and other important risk factors, such as smoking, occupational and environmental factors.
  • ACE angiotensin converting enzyme
  • ARBs angiotensin receptor blockers
  • leflumide e.g. angiotensin receptor blockers
  • chronic cough has been described as a distinct clinical syndrome, that is, the cough hypersensitivity syndrome. Chamberlain, et al. Lung 2015; 193: 401-408.
  • COPD chronic obstructive pulmonary disease
  • asthma the burden of chronic obstructive pulmonary disease (COPD) and asthma is considerable, both socially and economically.
  • COPD chronic obstructive pulmonary disease
  • uncontrolled disease is still associated with a substantial mortality and morbidity burden.
  • the ability to take medication appropriately is important.
  • Both are heterogeneous diseases, thus there is a need to optimize and personalize clinical management by treating the right patients with the right therapy at the right time during the course of their disease.
  • ACOS Asthma-COPD overlap syndrome
  • many patients are non-adherent to inhaled corticosteroid medication when symptom free, and such nonadherence is linked to poor outcomes.
  • Inhaler and medication nonadherence in these conditions is endemic (70-80%) and has become a central issue in the quality and economics of ambulatory medical care and drug trials.
  • What is needed is an accessible program that would improve medication adherence by combining compliance reminders with access to behavioral therapy that enhances disease outcomes while addressing medication side effects.
  • medication side effects can be minimized while simultaneously the value of taking the medication is reinforced, thus improving adherence.
  • Early symptom improvement, educational content, and flare-up management techniques or other treatment options can bring a patient back to the program, providing more opportunity to remind the patient about medication adherence.
  • Another treatment challenge comes from anxiety and depression, which often appear together in patients with COPD, asthma and chronic cough.
  • Untreated or undertreated depression and anxiety are associated with reduced treatment adherence, loss of disease control, reduced health-related quality of life and increased costs of care due to hospitalizations and other care needs.
  • the inventors herein have identified that there are multiple barriers to these patients getting holistic care, including lack of knowledge about these conditions and potential treatments, stigma associated with seeking mental health care, lack of availability of psychotherapy for specific chronic conditions and associated co-morbidities, delays in getting appointments, and short physician visit times that don’t allow for exploration of co-morbidities. Moreover, some of the medications used to treat anxiety and depression have potential negative implications for patients with respiratory conditions.
  • Other co-morbidities associated with respiratory health conditions include one or more of cardiovascular disease, eczema, sleep disorders, anxiety, depression, irritable bowel syndrome (IBS), and inflammatory bowel disease (IBD) for COPD disorders; one or more of GERD, anxiety, depression, and atopic dermatitis, for asthma; and one or more of COPD, asthma, depression, eosinophilic bronchitis, and GERD for chronic cough conditions.
  • cardiovascular disease eczema
  • sleep disorders anxiety, depression, irritable bowel syndrome (IBS), and inflammatory bowel disease (IBD)
  • IBS irritable bowel syndrome
  • IBD inflammatory bowel disease
  • COPD chronic cough conditions.
  • a respiratory disorder e.g., asthma, COPD, bronchitis
  • a chronic fatigue disorder e.g., a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, a cardiovascular disorder, hypertension, a sleeping disorder, a gastrointestinal disorder (e.g., irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), gastroesophageal reflux disorder (GERD)), a dermatological disease (e.g., psoriasis, eczema, atopic dermatitis), etc.
  • IBS irritable bowel syndrome
  • IBD inflammatory bowel disease
  • GTD gastroesophageal reflux disorder
  • a dermatological disease e.g., psoriasis, eczema, atopic dermatitis
  • behavioral therapy One type of therapy that has been shown to improve physiological states for patients with chronic respiratory disease is behavioral therapy. Williams et af, Jnt J Chron Obstruct Puhmm Dis. 2020: 15 : 903 -919. Behavioral therapy is also a valuable tool for addressing a variety of mental health issues, including anxiety and depression, and improving an individual’s ability to manage and respond effectively to external stimuli, such as stress. Typically, behavioral therapy is administered via a mental health professional, such as a therapist, for example through regular sessions between an individual and their therapist. Such interactions, however, can be time consuming, inconvenient, and costly, thereby limiting accessibility of behavioral therapy treatment.
  • Embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating respiratory health conditions using digital therapeutics in combination with other therapies, in order to ensure that patients receive adequate care, support, and treatment.
  • the invention described herein is an innovative way to deliver interactive psychotherapies concurrent with respiratory medications via a digital therapeutic platform broadly available to all respiratory patients and optimized to improve the effectiveness of these combination therapies, including tailoring to address individual differences, addressing co-occurring disorders (many respiratory conditions are overlapping and associated with other chronic conditions) and associated symptoms and medication side effects, and incorporating other optimization strategies.
  • the inventions covered by the system and method disclosed herein can confer several benefits over conventional systems and methods, and such inventions are further implemented into many practical applications related to improvement of technologies utilized for patient healthcare.
  • the systems and methods disclosed herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing a respiratory disorder in a patient.
  • the systems and methods disclosed herein allow behavioral therapy to be remotely administered to patients suffering from respiratory disorders in a convenient and flexible, yet structured fashion, via a digital therapeutics (DTx ) system in combination with one or more non-behavioral therapies.
  • DTx digital therapeutics
  • the invention(s) disclosed herein can employ non-traditional systems and methods for providing services such as interventions to patients exhibiting symptoms associated with one or more respiratory health conditions.
  • the invention(s) can deliver psychologicalbased interventions to patients, such as, but not limited to, cognitive behavioral therapy (CBT), habit reversal training, behavior changes, cognitive defusion, coping techniquest, stress reduction, arousal reduction training, mindfulness therapy, relaxation training, progressive muscle relaxation training, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, hypnotherapy, and acceptance and commitment (ACT)-based interventions, as well as other types of interventions, which are described in more detail below, by way of a platform having components implemented in a mobile device environment and/or other computer or internet-based architecture.
  • the invention(s) use components of the platform to process large amounts of user data, remotely deliver personalized interventions, and remotely monitor user interactions with such interventions in near real-time in a manner that cannot be practically implemented by the human mind.
  • digital therapeutics (DTx) technologies may be used to administer behavioral therapy treatments in combination with a variety of non-behavioral therapy treatments in a controlled fashion, as treatment for one or more conditions described herein.
  • provided technologies address physiological conditions (e.g., conditions with one or more physical symptoms, features, or manifestations) that may be affected by a subject’s mental health state, for example, presence of a mental health condition such as, but not limited to anxiety, depression, and/or stress.
  • mental health conditions and/or stress levels may be triggered and/or worsened by symptoms of a particular associated physiological condition, and/or may trigger and/or worsen the symptoms of the same particular physiological conditions, for example, in a feedback-like manner, which is often referred to as a ‘vicious cycle.’
  • the DTx technologies disclosed herein can be used to administer guided behavioral therapies in combination with a variety of non-behavioral therapies to treat individuals suffering from certain particular physiological conditions.
  • the DTx technologies can be used in combination with treatments utilizing one or more pharmaceutical compositions.
  • respiratory health conditions are particularly relevant, thus, in certain embodiments, guided behavioral therapy approaches disclosed herein may be administered, in combination with non-behavioral therapies (e.g., medications), to individuals suffering from one or more respiratory health conditions. In this manner, approaches described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more symptoms associated with a variety of respiratory health conditions.
  • the DTx system disclosed herein may be used to improve efficacy of other types of therapies and/or ameliorate side effects of other types of therapies.
  • guided behavioral therapy tools provided by the DTx system disclosed herein may facilitate adherence to various treatment regimens (e.g., of pharmaceutical compositions), and/or management of dosing (e.g., providing insight and/or guidance relevant to dosage adjustments).
  • the DTx technologies described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more side effects associated with one or more non-behavioral therapies for a respiratory disorder in a patient who is undergoing said one or more non-behavioral therapies.
  • the DTx systems and methods may be used to treat, prevent, ameliorate, or reduce likelihood of developing one or more side effects associated with one or more medications used to treat a variety of respiratory health conditions.
  • the DTx systems and methods disclosed herein may be used to enhance the performance of a non-digital therapeutic intervention administered to a patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a respiratory disorder, and/or for the treatment, prevention, amelioration, or reduction in the likelihood of developing one or more symptoms associated with the respiratory disorder.
  • the DTx systems and methods described herein may be used to enhance performance of the therapeutic intervention for the treatment, prevention, amelioration, or reduction in the likelihood of developing one or more side effects associated with the therapeutic intervention.
  • the DTx systems and methods disclosed herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more comorbidities associated with a variety of respiratory health conditions.
  • a patient is provided with a user interface to a DTx system wherein the DTx system remotely administers guided behavioral therapy to the patient.
  • a pre-assessment of a patient exhibiting one or more respiratory health condition symptoms is performed by the DTx system to generate patient profile and preassessment data.
  • the patient profile and pre-assessment data is processed by the DTx system to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type, co-morbidity(ies), and/or condition severity.
  • the patient profile and pre-assessment data and the patient condition data are processed by the DTx system to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components.
  • the patient profile and pre-assessment data and the patient condition data are processed by the DTx system to generate a personalized intervention regimen for the patient, wherein the personalized intervention regimen defines both behavioral therapy components and non-behavioral therapy components to be administered to the patient.
  • the one or more behavioral therapy components are administered, through the user interface of the DTx system, to the patient according to the personalized intervention regimen generated for the patient.
  • the one or more non-behavioral therapy components are administered to the patient in combination with the one or more behavioral therapy components according to the personalized intervention regimen generated for the patient.
  • the patient’s interactions with the one or more behavioral therapy components and the one or more non-behavioral therapy components are monitored remotely in near real-time to generate patient interaction data.
  • the patient interaction data is processed by the DTx system to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen.
  • aspects of the behavioral therapy and/or the non-behavioral therapy components defined by the patient’s personalized intervention regimen are dynamically modified.
  • the invention(s) can also provide interventions that are tailored to individual users/patients suffering from a variety of symptoms, such as, but not limited to chronic fatigue, coughing, hypertension, insomnia, anxiety, depression, social/interpersonal effects, emotional effects, cognitive effects, and behavioral effects, in a customized manner, with implementation of real-time or near real-time assessments of data from multiple sources and comparisons of that data against individual user baseline(s), including, but not limited to, electronic health record sources, self-report sources, and sensor sources.
  • symptoms such as, but not limited to chronic fatigue, coughing, hypertension, insomnia, anxiety, depression, social/interpersonal effects, emotional effects, cognitive effects, and behavioral effects.
  • the invention(s) can also be used for acquisition of user/patient data from multiple data sources, including, but not limited to, health data, biometric data, user demographic data, cough frequency/intensity data, user mood data, and user behavior data.
  • the invention(s) can also be used for generation of training datasets, whereby the training datasets can be used for training machine learning models (e.g., neural networks, etc.) that take input data pertaining to users/patients and produce outputs that can be used to guide customization of interventions.
  • machine learning models e.g., neural networks, etc.
  • the invention(s) can also be used to provide automated delivery of health-promoting or improving interventions, automated tracking/monitoring of user interactions with such interventions, automated communications with users (e.g., through transmission of notifications), and/or automated delivery of modified interventions to users, through a mobile device application platform and/or other platform (e.g., web platform).
  • a mobile device application platform and/or other platform e.g., web platform
  • such interventions can also be delivered as digital therapeutics, alone as a monotherapy or in combination with other therapeutics, such as medications and/or medical devices, through technical systems intended to diagnose and/or treat and/or improve symptoms or health-related quality of life, in collaboration with healthcare providers, health insurers, and/or other entities in the healthcare system.
  • the invention(s) can also employ non- traditional systems and methods for delivering digital therapeutics for improving patient health (e.g., in relation to disease management and monitoring), whereby digital therapeutics are prescribed (“prescription digital therapeutic” or “PDT”) or recommended (e.g., over-the-counter therapy or wellness application) through healthcare providers (e.g., with associated billing codes).
  • prescription digital therapeutic or “PDT”
  • recommended e.g., over-the-counter therapy or wellness application
  • the invention(s) can include systems and methods for improving patient states (e.g., in the context of health, symptoms, disease progression, quality of life, and other contexts). Additionally or alternatively, in some embodiments, the system and/or method can confer any other suitable benefit.
  • the present disclosure provides methods for remotely administering behavioral therapy to a user/patient via a controlled progression of interactive therapy modules, through a graphical user interface (GUI) of a DTx system.
  • GUI graphical user interface
  • technologies described herein allow an individual user/patient to access and take part in a series of guided lessons that provide training in various behavioral skills.
  • these guided lessons may be presented as a sequence of interactive lesson modules that provide training and practice via a graphical user interface (GUI) of a DTx system.
  • GUI graphical user interface
  • approaches described herein provide structured behavioral therapy that is targeted at managing triggers and/or symptoms associated with specific physical conditions. Accordingly, in some embodiments, a behavioral therapy toolkit as provided by the systems and methods described herein can be tailored for a particular physical condition.
  • the present disclosure provides methods for providing for interactive creation of a user personal model via a graphical user interface (GUI) of a DTx system, allowing a user to identify cycles of behaviors, thoughts, emotions, and stressors that influence the frequency and/or severity of symptoms associated with a particular physical condition from which the user is suffering.
  • GUI graphical user interface
  • technologies described herein can increase access to and/or facilitate effective administration of behavioral therapy, and moreover can achieve effective impact on physiological conditions through guided behavioral therapy in combination with other types of therapies.
  • the present disclosure provides improvements to technologies and methods for administering cognitive behavioral therapy (CBT), habit reversal training, arousal reduction training, behavior changes (e.g., respiratory daily care), cognitive defusion, copying technique, stress reduction, relaxation therapy, progressive muscle relaxation training, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, hypnotherapy, acceptance and commitment (ACT) therapy and/or mindfulness-based therapy.
  • CBT cognitive behavioral therapy
  • habit reversal training e.g., arousal reduction training
  • behavior changes e.g., respiratory daily care
  • cognitive defusion e.g., copying technique
  • stress reduction e.g., relaxation therapy
  • progressive muscle relaxation training e.g., breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal
  • the inventors have recognized the above-mentioned disadvantages, and further, have identified the need for an accessible program that would improve medication adherence by combining compliance reminders with access to behavioral therapy that enhances disease outcomes while addressing medication side effects.
  • medication side effects can be minimized while simultaneously the value of taking the medication is reinforced, thus improving adherence.
  • Early symptom improvement, educational content, and flare-up management techniques or other treatment options can bring a patient back to the program, providing more opportunity to remind the patient about medication adherence.
  • a method of improving patient adherence to a treatment regimen of a therapeutic intervention administered to said patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a respiratory disorder and/or one or more side effects associated with said therapeutic intervention comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating respiratory health conditions using digital therapeutics in combination with other therapies, in order to ensure that patients receive adequate care, support, and treatment.
  • FIG. 1A depicts a schematic of a system for treating respiratory health conditions using digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. IB depicts a block diagram of a production environment for treating respiratory health conditions using digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. 2A depicts a flowchart of a method for treating respiratory health conditions using digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. 2B depicts a flowchart of a method for providing adaptive interventions for respiratory health conditions, according to one or more embodiments.
  • FIG. 2C depicts a flowchart of a method for providing adaptive interventions for respiratory health conditions, according to one or more embodiments.
  • FIG. 3A depicts a schematic of architecture implemented for delivery of intervention regimen components and/or modules, according to one or more embodiments.
  • FIG. 3B depicts examples of individual sections that may make up an introduction and education module of an intervention regimen, according to one or more embodiments.
  • FIG. 3C depicts examples of individual sections that may make up a cough or other symptom management module of an intervention regimen, according to one or more embodiments.
  • FIG. 4 depicts an example of formation of a personal disease model, according to one or more embodiments.
  • FIG. 5 A depicts a flowchart of a process for determining severity of a respiratory condition, according to one or more embodiments.
  • FIG. 5B depicts examples of a process for determining severity of a respiratory health condition, according to one or more embodiments.
  • FIG. 6 depicts a flowchart of a pre-assessment and onboarding process of a method for providing adaptive interventions, according to one or more embodiments.
  • FIG. 7 depicts examples of behavioral therapy modules of a program for personalized respiratory condition monitoring and improvement, according to one or more embodiments.
  • FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E depict example schematics of conditional branching architecture implemented for delivery of intervention regimen components, according to one or more embodiments.
  • FIG. 9A, FIG. 9B, FIG. 9C, FIG. 9D, FIG. 9E, FIG. 9F, FIG. 9G and FIG. 9H are screenshots of several portions of an exemplary GUI for a system for treating respiratory health conditions using digital therapeutics, according to one or more embodiments.
  • FIG. 10 A, FIG. 10B, FIG. 10C, and FIG. 10D are screenshots of example user interactions with an initial lesson module for content tailored for a patient with a respiratory condition, which may be a comorbid condition or medication side effect associated with or causing respiratory disorders, according to one or more embodiments.
  • FIG. 11 A and FIG. 1 IB are screenshots showing gate features of an exemplary GUI for a system for treating respiratory health conditions using digital therapeutics, in accordance with one or more embodiments.
  • FIG. 12 A, FIG. 12B, FIG. 12C, and FIG. 12D are screenshots of an exemplary GUI for a symptom and/or medication adherence diary lesson module, according to one or more embodiments.
  • FIG. 13A, FIG. 13B, FIG. 13C, and FIG. 13D are screenshots of example user interactions with a symptom and/or medication adherence diary practice module, in accordance with one or more embodiments.
  • FIG. 14 A, FIG. 14B, FIG. 14C, and FIG. 14D are screenshots of an exemplary GUI for introducing a personal model lesson module, in accordance with one or more embodiments.
  • FIG. 15 A, FIG. 15B, FIG. 15C, and FIG. 15D are screenshots of an exemplary GUI for a personal model lesson module, according to one or more embodiments.
  • FIG. 16 A, FIG. 16B, and FIG. 16C are screenshots of an exemplary personal model graphical representation, according to one or more embodiments.
  • FIG. 17A, FIG. 17B, FIG. 17C, and FIG. 17D are screenshots of an exemplary GUI for a reflections section of a personal model lesson module, according to one or more embodiments.
  • FIG. 18 A, FIG. 18B, FIG. 18C, and FIG. 18D are screenshots of an exemplary GUI for a symptom management lesson module, according to one or more embodiments.
  • FIG. 19A, FIG. 19B, FIG. 19C, and FIG. 19D are screenshots of an exemplary GUI for an unhelpful thought pattern lesson module, according to one or more embodiments.
  • the systems and methods disclosed herein allow behavioral therapy to be administered to patients suffering from respiratory health conditions in a convenient and flexible, yet structured fashion, via a digital therapeutics (DTx) system in combination with one or more non-behavioral therapies.
  • DTx digital therapeutics
  • behavioral therapy may include therapies such as, but not limited to, cognitive behavioral therapy (CBT), mindfulness therapy, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit reversal training, aversion therapy, acceptance and commitment (ACT)-based interventions, psychotherapy, habit reversal training (HRT), arousal reduction training, cognitive defusion, coping techniques, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), relaxation therapy, progressive muscle relaxation (PMR) training, autogenic training (AT), biofeedback therapy, somatic anchoring therapy, hypnotherapy, experiential therapy, psychodynamic therapy,
  • CBT cognitive behavioral therapy
  • CBT cognitive behavioral therapy
  • breathing exercises breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit
  • such guided behavioral therapy technologies are based at least in part on cognitive behavioral therapy (CBT), and provide structured modules and/or lessons via a graphical user interface (GUI) of a digital therapeutics (DTx) system, for example to allow patients to develop a skillset for treating a physiological disease, disorder and/or condition, and for managing stress and/or other psychological symptoms associated with such disease, disorder and/or condition.
  • a relevant disease, disorder or condition may be or comprise a respiratory condition, such as, but not limited to COPD, asthma, ACOS, medication- induced chronic cough, chronic cough, and combinations thereof.
  • the chronic cough is associated with one or more other health conditions including, respiratory conditions and/or non-respiratory conditions.
  • chronic cough may be associated with one or more of asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, and GERD.
  • medication-induced chronic cough may be associated with medications such as angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • the DTx systems and methods described herein are based at least in part on cognitive behavioral therapy (CBT) and/or other digital therapeutics that would teach breathing techniques or speech therapy to manage asthma or cough.
  • CBT cognitive behavioral therapy
  • Respiratory health conditions or “respiratory disorders” or “respiratory diseases” refer to, without limitation, cough hypersensitivity syndrome, chronic obstructive pulmonary disease (COPD), asthma, bronchospasm, and the like.
  • Respiratory health conditions include, for example, sub-acute cough, acute cough, chronic cough, treatment-resistant cough, idiopathic chronic cough, cough associated with upper respiratory infection, post-viral cough, medication-induced cough (e.g., as induced by ACE-inhibitors), idiopathic pulmonary fibrosis, cough associated with smoking or a form of bronchitis.
  • Respiratory health conditions can include urge to cough associated with any respiratory disease, for example urge to cough associated with chronic obstructive pulmonary disease (COPD), cough-variant asthma, interstitial lung disease, or whooping cough.
  • COPD chronic obstructive pulmonary disease
  • the systems and methods described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing a respiratory disorder.
  • the systems and methods described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more symptoms associated with a respiratory disorder in a patient.
  • the systems and methods described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more side effects associated with a therapeutic intervention (e.g., one or more medications) for a respiratory disorder in a patient who is undergoing said therapeutic intervention
  • a therapeutic intervention e.g., one or more medications
  • the systems and methods described herein may be used for enhancing the performance of a therapeutic intervention (e.g., one or more medications) administered to a patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a respiratory disorder and/or one or more side effects associated with the therapeutic intervention.
  • a therapeutic intervention e.g., one or more medications
  • the systems and methods described herein may be used for improving patient adherence to a treatment regimen of a therapeutic intervention administered to said patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a respiratory disorder and/or one or more side effects associated with the therapeutic intervention.
  • the systems and methods described herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing one or more comorbidities associated with a respiratory disorder in a patient.
  • Respiratory health conditions or “respiratory disorders” or “respiratory diseases” refer to, without limitation, cough hypersensitivity syndrome, chronic obstructive pulmonary disease (COPD), asthma, asthma-COPS overlap syndrome (ACOS), bronchospasm, and the like.
  • Respiratory health conditions include, for example, sub-acute cough, acute cough, chronic cough, treatment-resistant cough, cough associated with upper respiratory infection, post-viral cough, medication-induced cough (e.g., as induced by ACE-inhibitors), cough associated with idiopathic pulmonary fibrosis, cough associated with smoking, cough associated with a form of bronchitis.
  • Respiratory health conditions can include urge to cough associated with any respiratory disease, for example urge to cough associated COPD, cough-variant asthma, interstitial lung disease, or whooping cough.
  • Acute cough refers to a cough lasting up to two weeks in duration.
  • acute cough can be the result of an acute disease, such as a cold or flu.
  • An acute cough will disappear when the underlying cause (e.g., cold or flu) is eliminated.
  • Sub-acute cough refers to a cough lasting between two and eight weeks. In some cases, a sub-acute cough follows a period in which a subject is infected with a disease (e.g., cold or flu). A sub-acute cough is one that often remains after the underlying cause has been removed. For instance, a sub-acute cough is found post-infection (e.g., post-viral infection).
  • a disease e.g., cold or flu
  • a sub-acute cough is one that often remains after the underlying cause has been removed. For instance, a sub-acute cough is found post-infection (e.g., post-viral infection).
  • Chronic cough refers to a persistent or refractory cough lasting longer than eight weeks that may be associated with one or more other health conditions (e.g., COPD, asthma, idiopathic pulmonary fibrosis, GERD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, etc.) or may not have an obvious underlying cause (that is, idiopathic).
  • other health conditions e.g., COPD, asthma, idiopathic pulmonary fibrosis, GERD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, etc.
  • respiratory health conditions or respiratory disorders include, but not limited to COPD, asthma, ACOS, bronchospasm, sub-acute cough, acute cough, chronic cough, treatment-resistant cough, cough associated with upper respiratory infection, post-viral cough, medication-induced cough, cough associated with idiopathic pulmonary fibrosis, cough associated with smoking, cough associated with bronchitis, cough associated with a gastrointestinal disorder, and urge to cough.
  • the systems and methods disclosed herein may be used to treat, prevent, ameliorate, or reduce the likelihood of developing a chronic cough disorder in a patient. Further, the systems and methods disclosed herein allow behavioral therapy to be remotely administered to patients suffering from chronic cough disorders in a convenient and flexible, yet structured fashion, via a digital therapeutics (DTx) system in combination with one or more non- behavioral therapies. In some embodiments, the invention(s) disclosed herein can employ non- traditional systems and methods for providing services such as interventions to patients exhibiting symptoms associated with one or more respiratory health conditions.
  • DTx digital therapeutics
  • the invention(s) can deliver psychological-based interventions to patients, such as, but not limited to, cognitive behavioral therapy (CBT), mindfulness therapy, relaxation therapy, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, hypnotherapy, habit reversal training, aversion therapy, and acceptance and commitment (ACT)-based interventions, as well as other types of interventions, which are described in more detail below, by way of a platform having components implemented in a mobile device environment and/or other computer or internet-based architecture.
  • CBT cognitive behavioral therapy
  • ACT acceptance and commitment
  • the invention(s) use components of the platform to process large amounts of user data, remotely deliver personalized interventions, and remotely monitor user interactions with such interventions in near real-time in a manner that cannot be practically implemented by the human mind.
  • the systems and methods described herein may employ breathing therapies and speech therapies to manage chronic cough.
  • a DTx program could include measurement of breathing parameters, provide real-time or near real-time feedback to improve breathing and reduce cough, improve pulse oximetry levels, etc.
  • the user may be instructed to hold the phone against their chest and the accelerometer along with sound can provide feedback to improve breathing and reduce cough, improve pulse oximetry levels, etc.
  • approaches described herein provide patients with structured behavioral therapy that is targeted at managing triggers and/or symptoms associated with specific physical and/or physiological conditions.
  • physiological conditions such as respiratory conditions
  • symptoms and effects of these physiological conditions may trigger and/or worsen related mental health conditions and can be a source of significant stress for many patients.
  • This feedback loop can create a vicious cycle, in which symptoms of a particular physiological condition trigger and/or worsen mental health states, causing issues such as anxiety and/or depression, which, in turn, trigger and/or worsen physical/physiological symptoms.
  • Feedback loops of this kind are particularly relevant to mind-body health conditions.
  • symptoms associated with a respiratory condition may be triggered by acid reflux, which in turn is caused by a gastrointestinal disorder (e.g., gastroesophageal reflux) triggered by stress, and mental health conditions such as depression and/or anxiety can worsen such symptoms.
  • a gastrointestinal disorder e.g., gastroesophageal reflux
  • mental health conditions such as depression and/or anxiety
  • intense coughing as well as the many complexities of managing the respiratory condition (e.g., importance of daily use of inhaler even when asymptomatic, etc.), are themselves significant stressors and may contribute to skin conditions (e.g., atopic dermatitis), gastrointestinal disorders, sleep disorders, depression and/or anxiety.
  • a behavioral therapy toolkit as provided by technologies (e.g., systems and methods) disclosed herein can be tailored for a particular physical/physiological condition.
  • particular behavioral therapy lesson modules can be designed to facilitate tracking of specific symptoms, tracking and elucidating specific stressors, and/or providing targeted exercises (e.g., speech therapy, breathing, progressive relaxation, habit reversal, etc.), which are well suited for managing specific triggers and symptoms of the particular physiological condition.
  • behavioral therapy lesson modules targeted at a respiratory health condition such but not limited to COPD, asthma, ACOS, medication-induced chronic cough, chronic cough associated with one or more other health conditions, cough hypersensitivity syndrome and idiopathic chronic cough (that is, chronic cough without an identifiable underlying cause)
  • a respiratory health condition such as COPD, asthma, ACOS, medication-induced chronic cough, chronic cough associated with one or more other health conditions, cough hypersensitivity syndrome and idiopathic chronic cough (that is, chronic cough without an identifiable underlying cause)
  • a respiratory health condition such but not limited to COPD, asthma, ACOS, medication-induced chronic cough, chronic cough associated with one or more other health conditions, cough hypersensitivity syndrome and idiopathic chronic cough (that is, chronic cough without an identifiable underlying cause)
  • idiopathic chronic cough that is, chronic cough without an identifiable underlying cause
  • the technologies, methods, and systems disclosed herein provide a valuable complement to physician visits and recommendations (e.g., with regard to lifestyle changes) and standard of care therapies (e.g., administration of medication(s)). Furthermore, technologies disclosed herein can increase access to and/or facilitate effective administration of behavioral therapy to achieve effective impact on physiological conditions such as, but not limited to, respiratory health conditions, through guided behavioral therapy.
  • the term “patient,” and/or “subject,” may include an individual who is suffering from a relevant disease, disorder or condition.
  • a patient/ subject is an individual who is susceptible to a disease, disorder, or condition.
  • a patient/subject displays one or more symptoms or characteristics of a disease, disorder or condition.
  • a patient/subject does not display any symptom or characteristic of a disease, disorder, or condition.
  • a patient/subject is someone with one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition.
  • a patient/subject is an individual to whom diagnosis and/or therapy is and/or has been administered.
  • a patient/subject is an individual who has been diagnosed with one or more diseases, disorders, and/or conditions and is the recipient of one or more therapies in a clinical or non-clinical setting. In some embodiments, a patient/subject is an individual who has not been diagnosed with a health condition, but is a recipient of one or more therapies in a clinical or non-clinical setting.
  • the term “digital therapeutics system,” and “prescription digital therapeutics (PDT) system” may include a system utilized for remotely administering a therapy to a patient, wherein the DTx system may be required to be approved or other oversight by a government agency before it can be marketed for administration to humans, or a “digital health” application that provides health education or general wellness content and does not require premarket authorization.
  • a PDT system requires FDA approval and rigorous clinical evidence to substantiate intended use and impact on disease state.
  • a PDT system requires a medical prescription is required for administration to patients or a DTx system may be recommended by a a health care provider but accessible directly to end users.
  • the term “user” may include a patient/subject who utilizes a DTx system or a PDT system.
  • an individual who is “suffering from” a disease, disorder, and/or condition displays one or more symptoms of a disease, disorder, and/or condition and/or has been diagnosed with the disease, disorder, or condition.
  • the term “therapy,” “behavioral therapy,” and/or “guided behavioral therapy” may include psychological techniques, methodologies, and/or modalities intended or demonstrated to achieve impact on and/or alteration of one or more behaviors of a patient/subject.
  • Examples of therapies may include, but are not limited to, cognitive behavioral therapy (CBT), mindfulness therapy, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit reversal training, aversion therapy, acceptance and commitment (ACT)-based interventions, psychotherapy, habit reversal training (HRT), arousal reduction training, rational -emotive therapy, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), relaxation therapy, progressive muscle relaxation (PMR) training, autogenic training (AT), biofeedback therapy, somatic anchoring therapy, hypnotherapy, cognitive defusion, coping techniques, experiential therapy, and psychodynamic therapy.
  • CBT cognitive behavioral therapy
  • CBT cognitive behavioral therapy
  • breathing exercises breathing exercises
  • cough suppression therapy speech and language pathology therapy
  • voice therapy vocal hygiene training
  • laryngospasm behavioral modification habit reversal training
  • ACT acceptance and commitment
  • ACT acceptance and commitment
  • ACT acceptance
  • mind-body intervention may include one or more therapeutic practices that employ a variety of techniques designed to facilitate the mind’s capacity to affect bodily function and systems.
  • Examples of mind-body interventions may include, but are not limited to, relaxation, imagery, biofeedback, meditation, habit reversal, hypnosis, tai, chi, and yoga.
  • the phrase “administration” may include providing, delivering, and/or applying a therapy to a patient.
  • a therapy may be administered to a patient directly by a health practitioner.
  • a therapy may be administered to a patient remotely, for example, over the internet or through a computer system, without the direct involvement of a health practitioner.
  • the therapy may be self-administered by the patient.
  • a therapy may also be administered to a patient remotely with partial involvement of a health practitioner.
  • the therapy to be administered may be selected by a health practitioner, but the therapy may then be selfadministered by the patient, utilizing a computer system, or the therapy may be administered to the patient by a computer system, but a health practitioner may monitor the patient’s response data.
  • compositions may be administered by one or more routes such as ocular, oral, parenteral, topical, etc.
  • administration may involve dosing, application, or interaction that is intermittent (e.g., a plurality of doses separated in time) and/or periodic (e.g., individual doses separated by a common period of time) dosing.
  • administration may involve continuous dosing (e.g., perfusion), application or interaction for at least a selected period of time.
  • the term “treat,” “treatment,” or “treating” may include administration of therapy that has been established to partially or completely alleviate, ameliorate, relieve, inhibit, prevent, delay onset of, reduce severity of, and/or reduce incidence of one or more symptoms or features of a disease, disorder, and/or condition (e.g., when administered to a relevant population).
  • treatment may be administered to a patient who is not exhibiting (and/or has not exhibited) one or more signs of a relevant disease, disorder, and/or condition.
  • treatment may be administered to a patient who exhibits only early signs of the disease, disorder, and/or condition, for example for the purpose of decreasing risk of developing one or more features of pathology associated with the disease, disorder, and/or condition.
  • a treatment is termed “therapeutic” when administered to a patient who is displaying or has displayed one or more features, symptoms, or other characteristics of a relevant disease, disorder and/or condition.
  • a treatment is termed “prophylactic” when administered to a patient who has not displayed features, symptoms, or other characteristics of a relevant disease, disorder and/or condition.
  • the term “protocol” or “therapeutic protocol” may include procedures and/or systems of rules for administration of a therapy.
  • a therapeutic protocol defines the rules, syntax, semantics, and synchronization of communications with a patient.
  • a therapy may include a series of modules, lessons, questionnaires, and exercises, and a related protocol may dictate the order, speed, and/or frequency in which various modules, lessons, exercises and questionnaires are presented to a patient.
  • a protocol may also dictate the specific layout, content and general presentation of the various lessons, exercises and questionnaires.
  • a protocol can be as specific as to dictate each word or sequence of words selected for use in the therapy.
  • a therapy may be administered to a patient according to any number of protocols or any number of combinations of protocols.
  • a therapeutic regimen may include a therapy for administration to a patient as part of a therapeutic treatment, wherein the therapy is administered to the patient according to a specific set of therapeutic protocols.
  • a therapeutic/intervention regimen for a behavioral therapy may include a specific set of modules, lessons, questionnaires, exercises, and other content, which may be administered to a patient in a particular order, at a particular frequency, utilizing a particular layout, etc.
  • a therapeutic/intervention regimen for a non-behavioral therapy may include administration of a non-behavioral therapy, such as a pharmaceutical or nutraceutical composition, in a particular amount, according to a particular dosing schedule.
  • a therapeutic/intervention regimen may be correlated with a desired or beneficial therapeutic outcome.
  • a therapeutic/intervention regimen may be personalized or tailored to meet the needs of a specific patient.
  • the term “combination therapy” may include situations in which a subject is simultaneously exposed to two or more therapeutic regimens (e.g., two or more therapeutic modalities and/or agents).
  • the two or more regimens may be administered simultaneously; in some embodiments, such regimens may be administered sequentially (e.g., all “doses” of a first regimen are administered prior to administration of any doses of a second regimen); in some embodiments, such modalities and/or agents are administered in overlapping dosing regimens.
  • “administration” of combination therapy may involve administration of one or more agent(s) or modality(ies) to a subject receiving the other agent(s) or modality(ies) in the combination.
  • combination therapy does not require that individual agents be administered together in a single composition (or even necessarily at the same time), although in some embodiments, two or more agents, or active moieties thereof, may be administered together in a combination composition, or even in a combination compound (e.g., as part of a single chemical complex or covalent entity).
  • the term “therapeutic agent” may include any agent that elicits a desired effect when administered to an organism, e.g., in a pharmaceutical composition, via a digital therapeutics (DTx) system, and/or according to a therapeutic regimen as described herein.
  • an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population.
  • the appropriate population may be a population of model organisms.
  • an appropriate population may be defined by various criteria, such as a certain age group, gender, genetic background, preexisting conditions, etc.
  • a therapeutic agent can be used to alleviate, ameliorate, relieve, inhibit, prevent, delay onset of, reduce severity of, and/or reduce incidence of one or more symptoms or features of a disease, disorder, and/or condition.
  • the term “dosing regimen” and/or “dosing schedule” may include a set of unit doses (typically more than one) that are administered individually to a subject, typically separated by periods of time.
  • a given therapeutic agent or modality has a recommended dosing regimen, which may involve one or more doses.
  • a dosing regimen comprises a plurality of doses each of which is separated in time from other doses.
  • individual doses are separated from one another by a time period of the same length; in some embodiments, a dosing regimen comprises a plurality of doses and at least two different time periods separating individual doses.
  • all doses within a dosing regimen are of the same unit dose amount. In some embodiments, different doses within a dosing regimen are of different amounts. In some embodiments, a dosing regimen comprises a first dose in a first dose amount, followed by one or more additional doses in a second dose amount different from the first dose amount. In some embodiments, a dosing regimen comprises a first dose in a first dose amount, followed by one or more additional doses in a second dose amount same as the first dose amount In some embodiments, a dosing regimen is correlated with a desired or beneficial outcome when administered across a relevant population (i.e., is a therapeutic dosing regimen).
  • the term “pharmaceutical composition” may include a composition in which an active agent is formulated together with one or more pharmaceutically acceptable carriers.
  • the active agent is present in unit dose amount appropriate for administration in a therapeutic regimen that has been established a statistically significant probability of achieving a predetermined therapeutic effect when administered to a relevant population.
  • a pharmaceutical composition may be specially formulated for administration in a particular form (e.g., in a solid form or a liquid form), and/or may be specifically adapted for, for example: oral administration (for example, as a drenche [aqueous or non-aqueous solutions or suspensions], tablet, capsule, bolus, powder, granule, paste, etc., which may be formulated specifically for example for buccal, sublingual, or systemic absorption); parenteral administration (for example, by subcutaneous, intramuscular, intravenous or epidural injection as, for example, a sterile solution or suspension, or sustained-release formulation, etc.); topical application (for example, as a cream, ointment, patch or spray applied for example to skin, lungs, or oral cavity); intravaginal or intrarectal administration (for example, as a pessary, suppository, cream, or foam); ocular administration; nasal or pulmonary administration, etc.
  • oral administration for example, as a drenche
  • nutraceutical composition may include a composition comprising one or more food(s) and/or food component(s), and/or one or more microbiome components, that provide medical or health benefits.
  • a nutraceutical is or comprises a component selected from the group consisting of microorganisms, proteins, vitamins, herbs, and combinations thereof, such as bacteria.
  • nutraceutical compositions are dietary supplements.
  • nutraceutical compositions are medical foods.
  • the term “amelioration” may include prevention (e.g., delay), reduction (e.g., in frequency and/or intensity), improvement, and/or palliation of a state, or one or more features thereof, experienced by a patient. Amelioration may include, but does not require, complete recovery or complete prevention of a disease, disorder or condition (e.g., radiation injury).
  • an appropriate reference measurement may be or may comprise a measurement in a particular system (e.g., in a single individual) under otherwise comparable conditions absent (e.g., prior to and/or after addition of) a particular agent or treatment, or in presence of an appropriate comparable reference agent.
  • an appropriate reference measurement may be or may comprise a measurement in a comparable system known or expected to respond in a particular way, for example in presence of the relevant agent or treatment.
  • prevention when used in connection with the occurrence of a disease, disorder, and/or condition, may include reducing a risk of developing the disease, disorder and/or condition and/or to delaying onset of one or more characteristics or symptoms of the disease, disorder or condition. Prevention may be considered complete when onset of a disease, disorder or condition has been delayed for a predefined period of time.
  • patient illness narrative may include a narrative expressed by a patient regarding the patient’s personal experiences with a disease, disorder, and/or condition.
  • An illness narrative is typically a narrative solicited from a patient, which enables a healthcare practitioner to build a more complete picture of the patient’s past and present health state in the context of the patient’s life, while providing the patient with an opportunity for self-reflection and validation.
  • a personal model and/or “personal disease model” may include a construction built based on patient input, which enables the patient to identify stressors, counterproductive behaviors, unhelpful thoughts, and negative emotions as associated with the patient’s disease, disorder, and/or condition.
  • a personal model is constructed as a graphical representation, which comprises text corresponding to patient-selected counterproductive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between the patient’s behaviors, thoughts, and emotions.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms.
  • a personal model may be utilized to help a patient identify links between their behaviors, thoughts, and emotions, and to help a patient consider possible changes in their behavior that could be implemented to address their symptoms.
  • the term “ecological momentary assessment” may include repeatedly sampling a subject’s current behaviors and experiences in real time, in the subject’s natural environment, with the aim of minimizing recall bias and allowing study of microprocesses that influence behavior in real-world contexts.
  • the term “machine learning module” may include a computer implemented process that implements one or more particular machine learning algorithms, such as supervised, unsupervised, and semi-supervised systems, an artificial neural network (ANN), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values.
  • ANN artificial neural network
  • FIG. 1A depicts a schematic of a system 100 A for treating respiratory health conditions using digital therapeutics in combination with other therapies, according to one or more embodiments.
  • system 100A includes: an online system 110 for digital content associated with the adaptive interventions, one or more client devices including client device 120 for delivering the behavioral therapy and skills training to one or more users, one or more external systems including external system 130, and a network 140 for data transmission between the online system 110, the client device(s) 120, and the external system(s) 130.
  • the system 100A includes functionality for educating patients (e.g., patients, users of the platform, etc.) regarding treatment and therapy options in the context of improving symptoms associated with respiratory health conditions; detecting, in real or near-real time, states of respiratory health condition symptom severity in non-invasive manners; and delivering therapeutic interventions in a customized, and adaptive manner to one or more users/patients exhibiting respiratory health condition symptoms, co-morbid condition symptoms, and/or medication side effects.
  • patients e.g., patients, users of the platform, etc.
  • therapeutic interventions in a customized, and adaptive manner to one or more users/patients exhibiting respiratory health condition symptoms, co-morbid condition symptoms, and/or medication side effects.
  • the system 100 A can provide tailored cognitive behavioral therapies (CBTs) and/or other psychotherapy modalities, such as cognitive behavioral therapy (CBT), mindfulness therapy, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit reversal training, aversion therapy, acceptance and commitment (ACT)-based interventions, psychotherapy, habit reversal training (HRT), arousal reduction training, rational -emotive therapy, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), relaxation therapy, progressive muscle relaxation (PMR) training, autogenic training (AT), biofeedback therapy, somatic anchoring therapy, hypnotherapy, cognitive defusion, coping techniques, experiential therapy, psychodynamic therapy, and combinations thereof for patients in an adaptive and customizable manner.
  • CBT cognitive behavioral therapy
  • CBT cognitive behavioral therapy
  • breathing exercises breathing exercises
  • cough suppression therapy speech and language pathology therapy
  • voice therapy vocal hygiene training
  • components of the above-listed therapeutic modalities may be combined to tailor a therapeutic intervention regimen to the needs of a particular patient.
  • respiratory health conditions are indicated herein, variations of the system 100 A can be adapted for generation and provision of interventions for systems associated with other health conditions.
  • the online system 110 functions to generate, store, and transmit digital content associated with the behavioral therapy and related adaptive interventions, according to algorithms that allow the online system 110 to administer (or guide administration) of interventions to patients in a timely and customized manner.
  • the online system 110 thus procures digital content associated with one or more therapeutic interventions and allows users/patients of the system 100A to access the digital content in an active or passive manner, in order to improve the patient(s)’ ability to manage respiratory health condition symptoms.
  • the online system 110 can include content generation components 112, content storage components 114, content transmission components 116, communication elements 118, and/or analytic platform 119 elements, implemented in computer architecture.
  • the online system 110 can additionally or alternatively include any other suitable subsystems or components associated with administration of guided therapy, adaptive interventions, and/or monitoring of patient health condition states.
  • the online system 110 can include computing architecture configured for generation of interactive digital objects in computer-readable formats, where such interactive digital objects can be included in modules of therapeutic interventions provided to patients exhibiting one or more respiratory health condition symptoms.
  • the content generation components 112 can include architecture for generation of content in one or more of: visual formats (e.g., with image objects, video objects, etc.), audible formats, haptic formats, and any other suitable formats.
  • Such content can be delivered through output devices of other components of the system 100A, such as display components (e.g., of a device, of an augmented reality device, of a virtual reality device, etc.), speaker components, haptic output device components, and/or any other suitable components.
  • the online system 110 can include architecture for storage and retrieval of computer-readable media associated with digital content and/or other objects.
  • Data storage systems can be associated with any suitable format, and include components configured for cloud and/or non-based cloud computing.
  • the information stored in the content storage components 114 can be organized according to specific data structures (e.g., with relational, columnar, correlation, or other suitable architecture).
  • Stored content can be associated with various digital objects (e.g., graphical/textual/audio/visual/haptic objects associated with content, and/or rearrangement of objects within particular environments, as associated with therapeutics and/or communications between entities, as described in more detail below).
  • the online system 110 can be configured to transmit content over wired and/or wireless interfaces, through network 140 (described in more detail below).
  • the content transmission components 116 of the online system 110 can include interfaces to the network 140, for content transmission to client devices 120 and/or external systems 130.
  • the online system 110 can include elements that enable communications between patients and other entities (e.g., care providers, coaches associated with health interventions, other patients, etc.) in text format, in audio format, and/or in any other suitable formats.
  • the online system 110 can support messaging, calling, and/or any other suitable communication types using web or other computer- based communication subsystems.
  • the online system 110 can include architecture for an analytics platform 119 for performing analytics in relation to generation of interventions (e.g., digital therapeutics as monotherapies, digital therapeutics as combinatorial therapies), evaluation of performance of interventions (e.g., in relation to performance, in relation to effectiveness, etc.), modification of interventions (e.g., in relation to content aspects, in relation to frequency aspects, etc.), provision of interventions (e.g., delivery method, etc.), generating and processing training data for refinement of models for intervention generation and provision, and other architecture for performing analytics.
  • interventions e.g., digital therapeutics as monotherapies, digital therapeutics as combinatorial therapies
  • evaluation of performance of interventions e.g., in relation to performance, in relation to effectiveness, etc.
  • modification of interventions e.g., in relation to content aspects, in relation to frequency aspects, etc.
  • provision of interventions e.g., delivery method, etc.
  • generating and processing training data for refinement of models for intervention generation and provision e.g., delivery method, etc.
  • one or more portions of the online system 110 can include processing subsystem components comprising non-transitory media storing instructions for executing one or more method operations described below.
  • the processing subsystem components can be distributed across the online system 110, client devices 120, and external systems 130, or organized in any other suitable manner.
  • the online system 110 can be implemented in a network-addressable computing system that can host one or more components for generating, storing, receiving, and sending data (e.g., content-related data, user-related data, data related to entities associated with various therapeutics, etc.).
  • the online system 110 can thus be accessed by the other components of the system 100 A either directly or via network 140 described below.
  • the online system 110 can include one or more servers (e.g., unitary servers, distributed servers spanning multiple computers or multiple datacenters, etc.).
  • the servers can include one or more server types (e.g., web server, messaging servers, advertising servers, file servers, application servers, exchange servers, database servers, proxy servers, etc.) for performing functions or processes described.
  • each server can thus include one or more of: hardware, software, and embedded logic components for carrying out the appropriate functionalities associated with the method(s) described below.
  • the client device(s) 120 function to deliver the behavioral therapy and/or adaptive interventions generated and/or stored by the online system 110 to patients exhibiting respiratory health condition symptoms in a timely manner.
  • the client device(s) 120 can include computing components, input devices, and/or output devices providing interfaces for receiving patient inputs and transmitting digital content data and/or sensor-derived data over the network 140 (described in more detail below).
  • the client device(s) 120 can include one or more of: mobile computing devices (e.g., a smartphone a personal digital assistant); a conventional computing system (e.g., desktop computer, laptop computer); a tablet computing device; a wearable computing device (e.g., a wrist-borne wearable computing device, a headmounted wearable computing device, an apparel-coupled wearable computing device); a cough or respiration computing device; and any other suitable computing device.
  • mobile computing devices e.g., a smartphone a personal digital assistant
  • a conventional computing system e.g., desktop computer, laptop computer
  • a tablet computing device e.g., a wearable computing device (e.g., a wrist-borne wearable computing device, a headmounted wearable computing device, an apparel-coupled wearable computing device); a cough or respiration computing device; and any other suitable computing device.
  • a wearable computing device e.g., a wrist-borne wearable computing device, a headmounted wearable computing device, an apparel
  • the client device(s) 120 can be configured to store and/or execute an application (e.g., mobile application, web application) that allows a user of the client device 120 to interact with the online system 110 by way of the network 140, in order to receive digital content associated with one or more therapeutic interventions and/or provide data associated with survey responses, sensor-derived data associated with interactions with such interventions, and/or any other suitable data.
  • an application e.g., mobile application, web application
  • the client device(s) 120 can include operation modes for administering treatments to the user (e.g., in relation to providing digital therapeutics upon diagnosis of the respiratory health condition of the user, in relation to providing medications, in relation to providing cough management therapies, etc.).
  • the external system(s) 130 function to transmit data (e.g., 3 rd party data) and/or receive data (e.g., 3 rd party data) associated with therapeutic interventions and/or user data (e.g., patient data).
  • the external system(s) 130 can include systems associated with electronic health records (EHRs) of the patient(s), systems associated with collection and/or storage of patient data (e.g., biometric data, behavioral data, social network data, communication data, etc.), systems associated with care providers (e.g., health insurance providers, health care practitioners, etc.), and/or any other suitable systems.
  • EHRs electronic health records
  • care providers e.g., health insurance providers, health care practitioners, etc.
  • the external system(s) can provide applications for communicating data in a manner that is protective of personal health information (PHI) and/or other sensitive patient data. Additionally or alternatively, the external system(s) can be associated with 3 rd party content generators and generate digital content in visual formats, audible formats, haptic formats, and/or any other suitable formats.
  • PHI personal health information
  • the external system(s) can be associated with 3 rd party content generators and generate digital content in visual formats, audible formats, haptic formats, and/or any other suitable formats.
  • the external system(s) 130 and/or client device(s) 120 can be configured to interact with the online system 110 by way of an application programming interface (API) executing on a native operating system of the external system(s) 130 and/or client device(s), in order to access API-associated data associated with the therapeutic interventions, patient health records, and/or other data (e.g., biometric data, patient behavior data through social networks, communication data through communication subsystems, etc.).
  • API application programming interface
  • the external system(s) 130 and/or client devices 120 can further include sensing components configured to generate data from which patient biometrics and/or behaviors can be extracted.
  • the external system(s) 130 and/or client devices 120 can include sensing components associated with one or more of: activity of a patient (e.g., through accelerometers, gyroscopes, motion coprocessing devices, etc.); facial expressions of the patient (e.g., through eye tracking, through image/video processing) for determination of cognitive states (e.g., associated with depression, anxiety, emotions, etc.) and/or performance of activities and/or interacting with content provided through the intervention regimen; physiological and/or psychological stress of a patient (e.g., in relation to respiration parameters, in relation to cardiovascular parameters, in relation to galvanic skin response, in relation to neurological activity, in relation to other stress biometrics, etc.); sleep behavior of a patient (e.g., with a sleep-monitoring device
  • the external system(s) 130 and/or client devices 120 can include components for extracting behavioral data associated with communications and social behavior, which can be indicative of changes in patient health associated with different symptoms.
  • Such components can include location sensors (e.g., direct location sensors, location sensing modules based on connections to local networks, triangulation systems, etc.) for tracking user motility and/or other behavior patterns, components associated with API access to social networking data, components associated with messaging communication behavior (e.g., components for accessing SMS or other messaging application data of a patient, with respect to messaging entities, messaging content, etc.), components associated with calling communication behavior (e.g., in relation to inbound/outbound calls, in relation to call duration, in relation to call content, etc.), data from digital assistants (e.g., voice-activated digital assistants) and any other suitable components from which behavioral data can be extracted.
  • location sensors e.g., direct location sensors, location sensing modules based on connections to local networks, triangulation systems, etc.
  • components associated with API access to social networking data
  • the network 140 functions to enable data transmission between the online system 110, the client device(s) 120, and the external system(s) 130, in relation to detection of patient states of wellbeing (e.g. with respect to respiratory health condition symptoms).
  • the network 140 can include a combination of one or more of local area networks and wide area networks, and/or can include wired and/or wireless connections to the network 140.
  • the network 140 can implement communication linking technologies including one or more of: Ethernet, worldwide interoperability for microwave access (WiMAX), 802.11 architecture (e.g., Wi-Fi, etc.), 3G architecture, 4G architecture, 5G architecture, long term evolution (LTE) architecture, code division multiple access (CDMA) systems, digital subscriber line (DSL) architecture, and any other suitable technologies for data transmission.
  • WiMAX worldwide interoperability for microwave access
  • 802.11 architecture e.g., Wi-Fi, etc.
  • 3G architecture 4G architecture
  • 4G architecture 5G architecture
  • long term evolution (LTE) architecture long term evolution
  • CDMA code division multiple access
  • DSL digital subscriber line
  • the network 140 can be configured for implementation of networking protocols and/or formats including one or more of: hypertext transport protocol (HTTP), multiprotocol label switching (MPLS), transmission control protocol/Internet protocol (TCP/IP), file transfer protocol (FTP), simple mail transfer protocol (SMTP), hypertext markup language (HTML), extensive markup language (XML), and any other suitable protocol/format.
  • the network 140 can also be configured for and/or provide, through communication links, encryption protocols for improving security of patient data transmitted over the network 140.
  • the system 100 A can include or be configured to interface with other system components associated with generation and/or delivery of behavioral therapy and related adaptive interventions.
  • the system 100A can include or be associated with environmental control devices configured to affect patient states of wellbeing passively or actively, in relation to the intervention types described in more detail below.
  • such devices can include environmental control devices, including one or more of lighting control devices, audio output devices, temperature control devices, and any other suitable environmental control devices.
  • the system 100 A can coordinate operation of such devices with delivery of adaptive interventions to patients, such that aspects of the patient’s environment can be modulated in coordination with other therapeutic measures to improve patient wellbeing in relation to respiratory health condition symptoms.
  • the system 100A can include and/or communicate control instructions for devices in the environment of the patient, in order to facilitate control of cough/wheeze volume, in relation to magnitude of cough/wheeze/intensity of cough/wheeze (e.g., by focusing the user on real time environmental changes) and/or to cause improvements in lives of patients in another suitable manner.
  • the system 100A can include an output device (e.g., component of client device 120, component of external system 130, etc.) that functions as an environmental control device in an environment of the patient, where the processing subsystem further includes instructions for adjusting the operation mode in coordination with monitoring a change in symptoms (e.g., cough or other respiratory symptoms) of the patient. Modulation of output device operation modes can thereby produce an adjustment in symptoms (e.g., cough count reduction) associated with the condition of the patient.
  • the environmental control device can modulate one or more of an audio output, a thermal parameter adjustment, a visually-observed output, a haptic output, and a light output in the environment.
  • the system 100A can include an output device (e.g., component of client device 120, component of external system 130, etc.) that functions as a communication device for transmitting communications between the patient and an entity associated with the patient, where the processing subsystem further includes instructions for generating a scripted communication for transmission to an entity associated with the patient, in coordination with monitoring a change in a physiological symptoms of the patient.
  • the system 100 A can be configured to interface or include any other suitable system components.
  • Embodiments, variations, and examples of one or more components of the system 100 A described above can implement one or more embodiments, variations, and examples of the methods 200 A, 200B, and/or 200C, as described below.
  • the system 100 A can additionally or alternatively be configured to implement other methods.
  • FIG. IB depicts a block diagram of a production environment 100B for treating respiratory health conditions using digital therapeutics in combination with other therapies, according to one or more embodiments.
  • production environment 100B includes DTx computing environment 141, patient 142, and patient computing systems 144.
  • production environment 100B optionally includes patient monitoring devices 146, health practitioner 148, and/or health practitioner computing systems 149.
  • production environment 100B includes communications channels 143, which facilitate communication between DTx computing environment 141 and one or more of patient computing systems 144, patient monitoring devices 146, and health practitioner computing systems 149.
  • DTx computing environment 141 includes DTx user interface 150, patient monitoring system 152, patient condition determination system 166, personalized regimen generation system 168, content selection system 170, and module gating system 172.
  • DTx computing environment 141 further includes patient database 156.
  • patient database 156 includes patient profile and pre-assessment data 158, patient condition data 162, patient personalized regimen data 164, and patient interaction data 154.
  • DTx computing environment 141 further includes therapeutic module database 174.
  • therapeutic module database 174 includes therapeutic module data 176, which further includes first therapeutic module 178, and second therapeutic module 184 through Nth therapeutic module 190.
  • first therapeutic module 178 includes module 1 content data 180 and module 1 protocol data 182
  • second therapeutic module 184 includes module 2 content data 186 and module 2 protocol data 188
  • Nth therapeutic module 190 includes module N content data 192 and module N protocol data 194.
  • DTx computing environment 141 further includes processor 196 and physical memory 198, which together coordinate the operation and interaction of the data and data processing systems associated with DTx computing environment 141.
  • processor 196 and physical memory 198 which together coordinate the operation and interaction of the data and data processing systems associated with DTx computing environment 141.
  • patient 142 is provided with a digital therapeutics (DTx) system, wherein the DTx system remotely administers guided behavioral therapy through an adaptive intervention regimen including a plurality of interactive therapy modules.
  • the DTx computing environment 141 communicates with patient 142 via one or more communications channels 143 between patient computing systems 144 and a user interface of the DTx system, such as DTx user interface 150.
  • therapeutic module database 174 contains a repository of data related to each of the available therapy modules, including module content data and module protocol data.
  • a therapeutic protocol defines the rules, syntax, semantics, and synchronization of communications with a patient.
  • the therapeutic module database may be populated and/or updated periodically by health practitioner 148, for example, through health practitioner computing systems 150.
  • module gating system 172 is responsible for determining which parts of the intervention regimen patient 142 has already completed, if any, as well as determining which modules and/or module content should be gated, locked, and/or unlocked. The operation of module gating system 172 will be discussed in additional detail below.
  • content selection system 170 may select module 1 content data 180 from first therapeutic module 178 of therapeutic module database 174. Content selection system 170 may then administer module 1 content data 180 to patient 142 through DTx user interface 150. In one embodiment, module 1 content data 180 is administered to patient 142 according to one or more therapeutic protocols defined by module 1 protocol data 182.
  • first therapeutic module 178 may be an introduction and education module, which introduces the patient to the system features, and provides education to the patient relating to the methods utilized by the system and/or relating to the patient’s particular disease, disorder, and/or condition.
  • first therapeutic module 178 also generates patient profile and pre-assessment data 158 by virtue of interaction between patient 142 and the content provided through DTx user interface 150 of the DTx system.
  • patient profile and pre-assessment data is generated independently of first therapeutic module 178. Additional details regarding first therapeutic module 178 (the introduction and education module) will be provided below.
  • content selection system 170 may select module 2 content data 186 from second therapeutic module 184 of therapeutic module database 174. Content selection system 170 may then administer module 2 content data 186 to patient 142 through DTx user interface 150. In one embodiment, module 2 content data 186 is administered to patient 142 according to one or more therapeutic protocols defined by module 2 protocol data 188.
  • second therapeutic module 184 may be a physical illness narrative module, which, in some embodiments, solicits narratives from the patient regarding the impact that the patient’s disease, disorder, and/or condition has had on their lifestyle, mental state, and overall well-being.
  • second therapeutic module 184 generates patient illness narrative data (not shown) by virtue of interaction between patient 142 and the content provided through DTx user interface 150 of the DTx system.
  • second therapeutic module 184 also introduces the patient to the concept of a personal disease model, and guides the user through the process of creating a personal model.
  • second therapeutic module 184 solicits additional data from the patient for use in creation of the personal model, such as data related to the patient’s counter-productive behaviors, unhelpful thoughts, and negative emotions. Additional details regarding second therapeutic module 184 (the physical illness narrative module) will be provided below.
  • patient profile and pre-assessment data 158 is processed by patient condition determination system 166 of the DTx system to generate patient condition data 162, as will be discussed in additional detail below.
  • personalized regimen generation system 168 utilizes patient profile and pre-assessment data 158 and patient condition data 162 to generate a personalized intervention regimen for the patient, which is represented in FIG. IB by patient personalized regimen data 164.
  • patient personalized regimen data 164 includes data representing regimen details such as, but not limited to, which of the available remaining therapy modules to administer to the patient, in what order to administer the therapy modules, a time schedule for when/how often to administer the therapy modules, what content to include in each of the therapy modules, and how to present the therapy module content to the patient.
  • personalized regimen generation system 168 may further process patient profile and pre-assessment data 158 and patient condition data 162 to identify one or more current or potential complementary therapies to be administered to patient 142 in combination with the behavioral therapy components represented by therapeutic module data 176.
  • complementary therapies may include one or more non-behavioral therapies, such as pharmaceutical and/or nutraceutical compositions, and personalized regimen generation system 168 may incorporate data related to administration of such therapies (e.g. therapy type, dosage amount, and dosage schedules) into patient personalized regimen data 164. Additional details regarding generation of a personalized intervention regimen for the patient will be discussed below.
  • patient personalized regimen data 164 is provided to module gating system 172 to determine which components of the intervention should be gated, locked, or unlocked, and content selection system 170 may then administer content data related to the appropriate therapeutic module to patient 142 through DTx user interface 150.
  • content selection system 170 may provide one or more options, notifications, alerts, and/or recommendations to patient 142 through DTx user interface 150, wherein the one or more options, notifications, alerts, and/or recommendations relate to current or potential complementary (non-behavioral) therapies to be administered in combination with the behavioral therapy modules/components.
  • the patient’s interactions with the behavioral therapy components and/or the patient’s interactions with and/or reactions to the non-behavioral therapy components of the personalized intervention regimen may be monitored remotely, either at fixed intervals, or in near real-time.
  • the patient’s interactions with the regimen components such as through a patient monitoring system 152 of the DTx system, or through external patient monitoring devices 146, such as sensors, etc., which may then transmit patient data and/or patient interaction data 154 over one or more communications networks 143.
  • the progression of the user through the through the therapeutic modules may be dynamically and remotely controlled, for example, though a system such as module gating system 172.
  • module gating system 172 may be programmed to gate, lock, or unlock various modules and module components at set intervals. If the patient interaction data 154 indicates that the user would benefit from shorter or longer intervals between lesson modules, module gating system 172 may dynamically adjust how often to unlock new content. A more detailed description of the module gating system used to dynamically and remotely control user progression through the modules will be provided below.
  • the patient’s personalized intervention regimen may be modified and/or updated. For example, user input in one module might change the recommendation for how to present subsequent modules, and a patient’s reactions to one more non-behavioral therapy components may change the recommendations for the dosing of that particular component. In the case where the patient is being remotely monitored in near real-time, this allows for the personalized intervention regimen to be dynamically adaptive, thus resulting in administration of the guided therapy in combination with other types of respiratory therapies in a manner that is most efficient and effective for the patient. Additional details regarding dynamically modifying the patient’s personalized intervention regimen will be discussed in further detail below.
  • FIG. 2A depicts a flowchart of a method 200A for treating respiratory health conditions using digital therapeutics in combination with other therapies, according to one or more embodiments.
  • the method 200A can include operations for: providing a patient with a user interface to a digital therapeutics (DTx) system wherein the DTx system remotely administers guided behavioral therapy to the patient 204; performing, by the DTx system, a pre-assessment of a patient exhibiting one or more respiratory health condition symptoms to generate patient profile and pre-assessment data 206; processing, by the DTx system, the patient profile and pre-assessment data to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type and/or condition severity 208; processing, by the DTx system, the patient profile and pre-assessment data and the patient condition data to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components 210; processing, by the DTx system, the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient, wherein
  • DTx digital therapeutics
  • method 200A functions to educate users regarding treatment and therapy options in the context of improving symptoms associated with a variety of health conditions; detect, in real or near-real time, states of health condition symptom severity in non- invasive manners; and administer therapeutic interventions in a customized, and adaptive manner to one or more patients exhibiting health condition symptoms.
  • the method 200A can be used to provide tailored behavioral therapy to patients in an adaptive and customizable manner.
  • the method 200A can be used to provide behavioral therapy to patients in combination with other types of complementary, non-behavioral therapies. Method 200A will be discussed in additional detail below.
  • providing guided behavioral therapy and skills training includes providing adaptive interventions for patients with respiratory health conditions.
  • FIG. 2B depicts a flowchart of a method 200B for providing adaptive interventions for respiratory health conditions, according to one or more embodiments.
  • a method 200B can include operations for: performing a pre-assessment of a patient exhibiting one or more respiratory health condition symptoms 226; generating an intervention regimen for the patient upon processing data from the pre-assessment with an intervention-determining model 228; delivering the intervention regimen to the patient 230; monitoring a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient contemporaneously with delivery of the intervention regimen 232; and in response to at least one of the set of interactions and the health status progression, performing an action configured to improve wellbeing of the patient with respect to the respiratory health condition 234.
  • Method 200B will be discussed in additional detail below.
  • FIG. 2C depicts a flowchart of a method 200C for providing adaptive interventions for respiratory health conditions, according to one or more embodiments.
  • a method 200C can include operations for: establishing an interface between a device and a user 240; from the interface, receiving a set of signals associated with a health condition of the user, wherein the set of signals encodes physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user 242; determining a characterization of the respiratory health condition upon processing the set of signals with a model 244; based upon the characterization, modulating content of a treatment comprising a set of components, the set of components comprising a subset of cognitive behavioral therapy (CBT) components for improving a state of the user 246; and administering the treatment to the user 248.
  • CBT cognitive behavioral therapy
  • Methods 200B and 200C function to educate patients regarding treatment and therapy options in the context of improving symptoms associated with respiratory health conditions; detect, in real or near-real time, states of respiratory health condition symptom severity in non-invasive manners; and deliver interventions in a customized, and adaptive manner to one or more users exhibiting respiratory health condition symptoms.
  • methods 200B and 200C can be used to provide tailored cognitive behavioral therapy (CBT) and/or other therapeutic modalities to patients in an adaptive and customizable manner. While respiratory health condition symptoms are described, variations of the methods 200B and 200C can be adapted for generation and provision of interventions for systems associated with other health conditions.
  • CBT cognitive behavioral therapy
  • aspects of methods 200A, 200B, and 200C can be performed at desired frequencies (e.g., weekly, more often than weekly, less often than weekly).
  • desired frequencies e.g., weekly, more often than weekly, less often than weekly.
  • the method can promote interactions more often than weekly (e.g., daily, 2 times a week, 3 times a week, four times a week, five times a week, six times a week, etc.) or less often than weekly, in relation to reinforcement of skills acquired by the patients.
  • received data can be processed in real time, or non- real time.
  • the methods 200A, 200B, and 200C can have delivery and processing aspects associated with other suitable frequencies.
  • the methods 200A, 200B, and 200C can be performed by an embodiment, variation, or example of the system 100A described in above (e.g., in relation to processing subsystem components with instructions stored in non-transitory media and other input/output devices); however, the methods 200A, 200B, and 200C can additionally or alternatively be performed using any other suitable system components.
  • FIG. 2A depicts a flowchart of a method 200A for treating respiratory health conditions using digital therapeutics in combination with other therapies, according to one or more embodiments.
  • method 200A begins at BEGIN 202, and method flow proceeds to operation 204.
  • a patient is provided with a user interface to a digital therapeutics (DTx) system wherein the DTx system remotely administers guided behavioral therapy to the patient.
  • DTx digital therapeutics
  • a patient may consult with one or more healthcare practitioners regarding symptoms that the patient is experiencing, and the healthcare practitioner may determine that the patient is suffering from one or more health-related conditions.
  • therapies such as, but not limited to cognitive behavioral therapy (CBT), mindfulness therapy, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit reversal training, aversion therapy, acceptance and commitment (ACT)-based interventions, psychotherapy, habit reversal training (HRT), arousal reduction training, rationalemotive therapy, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), relaxation therapy, progressive muscle relaxation (PMR) training, autogenic training (AT), biofeedback therapy, somatic anchoring therapy, hypnotherapy, cognitive defusion, coping techniques, experiential therapy, psychodynamic therapy
  • CBT cognitive behavioral therapy
  • breathing exercises breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification
  • components of the above listed modalities may be combined to form a hybrid type of therapy.
  • a hybrid therapy may utilize particular components taken from CBT, voice therapy, and laryngospasm behavioral modification, wherein the components are selected based on the specific needs of the patient.
  • behavioral therapies can also be combined with other types of non-behavioral therapies, as will be discussed in detail below.
  • behavioral therapy and in particular cognitive behavioral therapy (CBT) has traditionally been considered effective for treatment of psychological conditions such as, for example, alcohol and drug use problems, anxiety disorders, depression, chronic fatigue disorders, eating disorders, emotional trauma, grief or loss, hypertension, marital or other relationship problems, mental illness, obsessive-compulsive disorder (OCD), pain, phobias, post-traumatic stress disorder (PTSD), schizophrenia, sexual disorders, sleep disorders, etc.
  • CBT cognitive behavioral therapy
  • OCD obsessive-compulsive disorder
  • PTSD post-traumatic stress disorder
  • schizophrenia sexual disorders, sleep disorders, etc.
  • behavioral therapy has traditionally involved counseling by a mental health provider such as a psychiatrist, psychologist, or other provider; typically, behavioral therapy provides a structured format and a limited (i.e., finite) number of sessions.
  • the present disclosure provides new behavioral therapy technologies which may, in some embodiments, be provided to an individual via non-human interactions, such as via a computer- based system.
  • computer-based systems are designed to mimic portions of interactions, such as useful exercises, assessments, and techniques that may traditionally be carried out in the context of counseling sessions with a mental health provider and/or via exercises recommended thereby (e.g., ‘homework,’ such as values inventories, journaling exercises, selfassessments, and the like).
  • provided behavioral therapies may be useful in the treatment of certain physiological conditions, such as, but not limited to, respiratory health conditions (e.g., COPD, asthma, ACOS, medication-induced chronic cough (e.g., chronic cough associated with one or more medications including angiotensin drugs, proton pump inhibitors, and anti-inflammatories), cough hypersensitivity syndrome, idiopathic chronic cough, and/or chronic cough associated with one or more other health conditions such as respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, and GERD.
  • respiratory health conditions e.g., COPD, asthma, ACOS
  • medication-induced chronic cough e.g., chronic cough associated with one or more medications including angiotensin drugs, proton pump inhibitors, and anti-inflammatories
  • cough hypersensitivity syndrome e.g., chronic cough associated with one or more medications including angiotensin drugs, proton pump inhibitors, and
  • the doctor may prescribe a therapeutics system to the patient.
  • the therapeutics system is a prescription digital therapeutics (PDT) system.
  • PDT prescription digital therapeutics
  • a PDT system differs from traditional computer-based wellness systems, in that the PDT system is required to be approved by a government agency before it can be marketed for administration to humans.
  • a PDT system requires FDA approval and rigorous clinical evidence to substantiate intended use and impact on disease state.
  • a PDT system is typically a system for which a medical prescription is required for administration to patients, or it may be recommended for an “over-the-counter” or “OTC” digital therapeutics system.
  • method flow proceeds to operation 206.
  • the PDT system performs a pre-assessment of a patient exhibiting one or more respiratory health condition symptoms to generate patient profile and pre-assessment data.
  • an embodiment of the online system in coordination with the network and a client device, can perform the pre-assessment of operation 206 contemporaneously with executing an onboarding process with the patient with the online system.
  • Operation 206 functions to retrieve data describing characteristics of the patient, preferences of the patient, goals of the patient and/or any other suitable patient features that can be used to provide adaptive interventions through an intervention regimen associated with administration of guided behavioral therapy to the patient in a customized and personalized manner.
  • operation 206 can include pre-assessing and onboarding patients to generate patient profile and pre-assessment data, wherein the patient profile and pre-assessment data includes one or more of demographics (e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.), household situations (e.g., living alone, living with family, living with a caregiver, etc.), dietary characteristics (e.g., omnivorous, vegetarian, pescatarian, vegan, reduced carbohydrate consumption, reduced acid consumption, gluten-free, simple carbohydrate, or other dietary restrictions, etc.), levels of activity, levels of environmental pollution, levels of cigarette use, psychological symptom severity, levels of mobility (e.g., in relation to distance traveled in a period of time), biomarker statuses (e.g., sputum eosinophilia, exhaled nitric oxide, cholesterol levels, lipid states
  • demographics e.g., genders,
  • patient profile and pre-assessment data generated at operation 206 includes data related to non-behavioral therapies that the patient is receiving and/or has received.
  • patient profile and pre-assessment data may include data such as, but not limited to, data indicating the type of non-behavioral therapy (e.g., pharmaceutical, nutraceutical, etc.), data indicating the class of non-behavioral therapy (e.g., long-acting bronchodilators (132-agonists (LABAs), long-acting muscarinic antagonists (LAMAs), short-acting bronchodilators, nonsteroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastas
  • another event may include events such as, but not limited to, eating, exercise, exposure to light and/or temperature, exposure to one or more stressors (e.g., life events, social interactions, travel, etc.).
  • the non-behavioral therapy comprises one or more pharmaceutical compositions each comprising at least one compound independently selected from the group consisting of long-acting bronchodilators (132-agonists (LABAs), long-acting muscarinic antagonists (LAMAs)), short-acting bronchodilators, non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)-signal transducers
  • LAMAs long-acting bron
  • the one or more pharmaceutical compositions may each comprise at least one compound independently selected from the list of medication for respiratory disorders indicated in Table 1 below.
  • patient profile and pre-assessment data includes data, such as, but not limited to, physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the patient.
  • the pre-assessment and/or onboarding process performed in operation 206 can identify mental health statuses of the patient, in relation to comorbid or non-comorbid conditions (e.g., associated with anxiety, associated with depression, associated with social behavior, etc.), where the intervention regimen described in more detail below can be configured to improve mental health states of the patient in a timely and adaptive manner.
  • related data can include psychological and/or disease symptom/clinical profile data that informs selection of high priority therapy components, where examples include data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia characteristics of the patient, promoting behavioral activation content by the system and response chaining, where response chaining involves linking of effortful avoided tasks to those that are neutral or slightly rewarding); sources of motivation; reward sensitivity (e.g., sensitivity associated with drive and reward responsiveness (e.g., using a BIS/BAS assessment tool); and threat sensitivity.
  • data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia
  • the method 200 A can include receiving a reward sensitivity dataset characterizing motivation and reinforcement behavior of the patient, and modulating aspects of the treatment upon processing the reward sensitivity dataset with one or more models described herein.
  • Mental health, reward tendencies and sensitivity, and motivational aspect identification can, however, be assessed outside of the preassessment of operation 206.
  • the pre-assessment and/or onboarding process performed in operation 206 can identify user preferences associated with scheduling of content delivery (e.g., in relation to frequencies of content delivery described above) associated with one or more aspects of the intervention regimen, preferred formats (e.g., visual formats, audio formats, haptic formats, etc.) of content delivery, frequency of content delivery, location of user when content is delivered, specific device(s) to which content is delivered, and/or any other suitable user preferences.
  • preferred formats e.g., visual formats, audio formats, haptic formats, etc.
  • the pre-assessment and/or onboarding process performed in operation 206 can identify user goals for improving health, in relation to the intervention regimen.
  • Such goals can include one or more goals, such as, but not limited to: reduction of anxiety, reduction of negative emotions, reduction of depression symptoms, changing habits or responses to cough signals, improvement of sleep behavior, improvement in socialization, improvement of respiratory health condition symptoms, improvement of medication adherence, improvement in respiratory-related quality of life, improvement of other health condition symptoms, and/or any other suitable goals.
  • Goals can be organized at a high level of abstraction (e.g., improve sleep behavior), and/or at lower levels of abstraction (e.g., improve quality of sleep, reduce number of symptom-induced disturbances to sleep, etc.).
  • the patient profile and pre-assessment data can be obtained through various mechanisms, including, but not limited to, from a pre-assessment module of the DTx system, from patient health records accessible by the DTx system, from API access of health monitoring systems through the DTx system, and/or from biometric sensor data obtained by the DTx system from various devices utilized by the patient.
  • patient profile and preassessment data can be collected repeatedly throughout performance of the methods described herein, as will be discussed in additional detail below.
  • the online system and/or other system components can implement surveying tools (e.g., to obtain self-report data from the patient) and/or non-survey-based tools for acquisition of data.
  • Survey tools can be delivered through an application associated with the DTx system executing on the client device of the patient and/or through another suitable method, where the survey tools can implement architecture for assessing the patient in relation to mental health, discomfort, respiratory health symptom severity or disease activity, types of respiratory health condition symptoms, and/or other statuses.
  • the surveying tools can be derived from one or more patient reported outcome instruments, such as, but not limited to: leicester cough questionnaire (LCQ); cough-specific quality of life questionnaire; health related quality of life (HRQOL) questionnaire; quality of life (QoL) questionnaire; visual analog scale for cough severity; cough severity score (CSS); cough severity diary (CSD); numeric rating scale (NRS); tussigenic challenges; and combinations thereof, and any other tool or instrument.
  • LCQ leicester cough questionnaire
  • HRQOL health related quality of life
  • QoL quality of life
  • CCS cough severity score
  • CSD cough severity diary
  • NFS numeric rating scale
  • tussigenic challenges and combinations thereof, and any other tool or instrument.
  • survey components can be implemented during pre-assessment of a patient and/or within modules of the intervention regimen, as described in more detail below.
  • the online system and/or other system components can implement data from devices (e.g., non-survey data).
  • embodiments of the system can perform pre-assessment with implementation of data from devices including one or more devices, such as, but not limited to: electronic health record-associated devices; wearable devices (e.g., wrist-borne wearable devices, head-mounted wearable devices, etc.) for monitoring behavior and activities (e.g., related to physiological/cognitive stress, related to respiration activity, related to sedentary and active states, etc.) of the user; non-invasive torso-coupled devices; implanted devices, location monitoring devices, social networking tracking devices, spirometer, peak flow meter, high-resolution computed tomography (CT) scanners, cough monitors, audio-recognition devices, EMG devices, accelerometers, plethysmographs, electrocardiographs, the LifeShirt, VitaloJAK, Leicester Cough Monitor (LCM), LR102, hull automatic cough counter, cough counter mobile applications, pulmonary function measuring tools, pulse-oxygen devices, and combinations thereof.
  • devices including one or more devices, such as, but
  • Nonsurvey-derived data can additionally or alternatively include data derived from API access of social networking platforms, other communication platforms (e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users), locationdetermining platforms, and/or other platforms, in order to assess social behaviors of the user.
  • other communication platforms e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users
  • locationdetermining platforms e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users
  • other platforms e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users
  • multiple surveying tools may be combined in a single assessment module, or may be provided as distinct, separate, assessment modules.
  • Assessment modules may be based on, and used to solicit input for, a variety of diagnostic questionnaires, depending on a particular respiratory health condition for which a patient is to be evaluated. Additionally or alternatively, assessment modules may be designed to evaluate any other physiological and/or psychological conditions of the patient.
  • data pertaining to patient symptoms, quality of life, and other medical information may be obtained via access to electronic health records (EHRs) and/or electronic medical records (EMRs).
  • EHRs electronic health records
  • EMRs electronic medical records
  • applications in accordance with technologies as described herein may provide for communication with a secure database in order to receive and/or access EHR and/or EMR data for the user.
  • data may be used to populate a patient profile, and as a basis for tailoring content, e.g., as described herein.
  • method flow proceeds to operation 208.
  • the DTx system processes the patient pre-assessment data to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type, and/or condition severity.
  • processing of the patient pre-assessment data in operation 208 can result in identification of the patient as having other health condition symptoms associated with respiratory health condition, such as, but not limited to, one or more of: chronic fatigue, skin conditions, gastrointestinal disorders, hypertension, insomnia, anxiety, depression, and combinations thereof.
  • processing of the patient assessment data at 208 can result in identification of a subtype of a respiratory health disorder, including COPD, asthma, ACOS, medication-induced chronic cough (e.g., associated with one or more medications including angiotensin drugs, proton pump inhibitors, and anti-inflammatories), cough hypersensitivity syndrome, idiopathic chronic cough, and chronic cough associated with one or more other health conditions including respiratory conditions and/or non-respiratory conditions such as asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, and GERD.
  • a respiratory health disorder including COPD, asthma, ACOS, medication-induced chronic cough (e.g., associated with one or more medications including angiotensin drugs, proton pump inhibitors, and anti-inflammatories), cough hypersensitivity syndrome, idiopathic chronic cough, and chronic cough associated with one or more other health conditions including respiratory conditions and/or non-respiratory conditions such as asthma, COPD, chronic bron
  • processing of the patient pre-assessment data in operation 208 can result in identification of the patient as having one or more comorbidities associated with respiratory, such as, but not limited to, one or more of: a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, fatigue, a cardiovascular disorder, a dermatological disorder, eczema, atopic dermatitis, a sleep disorder, a gastrointestinal disorder, irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), GERD, a respiratory disorder, COPD, asthma, eosinophilic bronchitis, and combinations thereof, and/or any other suitable comorbidities.
  • a generalized anxiety disorder such as, but not limited to, one or more of: a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, fatigue, a cardiovascular disorder, a dermatological disorder, eczema, atopic dermatitis, a sleep disorder, a gastrointestinal disorder, irritable bowel syndrome
  • operation 208 can further identify one or more sub-types of a respiratory health condition, and/or one or more sub-types of comorbidities associated with the respiratory health condition.
  • a type of respiratory disorder is asthma, which can be further classified into a variety of subtypes.
  • asthma may be classified according to markers of airway inflammation into four inflammatory subtypes: eosinophilic asthma (EA), neutrophilic asthma, mixed granulocytic asthma and paucigranulocytic asthma.
  • EA eosinophilic asthma
  • neutrophilic asthma neutrophilic asthma
  • mixed granulocytic asthma mixed granulocytic asthma
  • paucigranulocytic asthma paucigranulocytic asthma.
  • the DTx system can be configured to receive, automatically detect, or automatically extract information regarding the particular subtype(s) of a respiratory condition that a patient has, based on a combination of patient health record data, data collected from health monitoring systems, data collected from biometric sensors, and data collected from patient- reported outcome instruments, in order to prioritize relevant content provided to the patient, in the interests of customizing the program. If the processing operation 208 identifies that the patient is predominantly subtype eosinophilic asthma, subsequent portions of the intervention regimen can prioritize content associated more highly with eosinophilic asthma. In some embodiments, however, subtype identification may be determined outside of the processing of operation 208.
  • operation 208 of method 200A includes a method of determining severity of the respiratory health condition.
  • operation 208 can calculate levels of a respiratory health condition-associated marker (e.g., from a sample from the patient, such as hand movements, from interactions with the system, etc.) to identify the patient as having a certain state of severity (e.g., expression, phenotype, etc.) of the respiratory health condition.
  • a respiratory health condition-associated marker e.g., from a sample from the patient, such as hand movements, from interactions with the system, etc.
  • a certain state of severity e.g., expression, phenotype, etc.
  • operation 208 can be implemented through the DTx system executing on a mobile device or other device associated with the patient, where a user interface of the DTx system prompts inputs from the patient pertaining to various symptoms (e.g., breathlessness, chronic cough, fatigue, difficulty breathing, chest tightness, coughing, wheezing, dyspnea, dry cough, hacking cough, etc.), generates a report indicating severity of the respiratory health condition (e.g., COPD, asthma, ACOS, medication-induced chronic cough, cough hypersensitivity syndrome, idiopathic chronic cough, and chronic cough associated with one or more other health conditions including respiratory conditions and/or non-respiratory conditions, such as asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, GERD, etc.)).
  • symptoms e.g., breathlessness, chronic cough, fatigue, difficulty breathing, chest tightness, coughing, wheezing, dyspnea, dry cough, hacking
  • asthma can be classified based on control and severity into one or more severity based subtypes.
  • the one or more severity based sub-types include 1) Controlled, mild asthma, 2) Uncontrolled, unknown severity, and 3) Partly controlled, severe asthma.
  • the DTx system disclosed herein can include architecture for receiving data derived from the patient (e.g., through sensor components, through survey components, associated with cough characteristics, motion characteristics, pulmonary function characteristics, mood characteristics, and other characteristics), processing the data with one or more models, and returning scores (e.g., measures of symptom severity, etc.). Scores can also be used for tagging user data with symptom severity, in relation to model aspects and model training/refinement described below.
  • method flow proceeds to operation 210.
  • the patient profile and preassessment data and the patient condition data are processed to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components.
  • the digital therapeutics (DTx) system disclosed herein may utilize behavioral therapy components in combination with non-behavioral therapy components to provide treatment for various physiological conditions (e.g., conditions with one or more physical symptoms, features, or manifestations), such as those described herein.
  • the DTx system disclosed herein may administer behavioral therapies and associated components in combination with one or more non-behavioral therapies and associated components, such as those described herein.
  • behavioral therapy is administered to subject(s) who are receiving or have received non-behavioral therapy for a relevant disease, disorder, or condition.
  • behavioral therapies and non- behavioral therapies may be approved, and/or administered as a combination product.
  • digital therapeutics (DTx) systems and methods described herein are utilized to administer guided behavioral therapy to a patient undergoing treatment for one or more respiratory health conditions via administration of one or more non-behavioral therapies.
  • non-behavioral therapies for respiratory health conditions, including, for example, pharmaceutical compositions such as, but not limited to: LABAs, LAMAs, short-acting bronchodilators, non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, JAKs-STATs signaling pathways inhibitors, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, antacids, promotility
  • pharmaceutical compositions such as, but not limited to: LABAs, LAMAs, short-acting bronchod
  • DTx may be used in combination with one or more pharmaceutical compositions for the treatment, prevention, amelioration, or reduction in the likelihood of developing a respiratory disorder in a patient.
  • the respiratory disorder is COPD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)-signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • LABAs LAMAs
  • short-acting bronchodilators non-steroid-based anti inflammatories, inhaled corticosteroids, combination
  • the respiratory disorder is asthma
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids, LABAs, LAMAs, short-acting bronchodilators, leukotriene receptor antagonists, systemic corticosteroids, eosinophilia-targeted biological therapies, combination therapies, xanthines, and combinations thereof.
  • the respiratory disorder is ACOS
  • the one or more pharmaceutical compositions each comprise at least one compound selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)- signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • the respiratory disorder is chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids; anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, and combinations thereof.
  • the respiratory disorder is chronic cough associated with GERD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of antacids, promotility drugs, PPIs, and combinations thereof.
  • the respiratory disorder is medication-induced chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of ACE inhibitors, ARBs, proton-pump inhibitors, antiinflammatories, and combinations thereof.
  • one or more non-behavioral therapies utilized for treatment of respiratory health conditions may include nutraceutical compositions such as supplements, probiotics, prebiotics, synbiotics, natural products, herbal therapies (e.g., honey, N-acetyl cysteine, mucilage containing herbs, traditional Chinese medicine teas, etc.).
  • nutraceutical compositions such as supplements, probiotics, prebiotics, synbiotics, natural products, herbal therapies (e.g., honey, N-acetyl cysteine, mucilage containing herbs, traditional Chinese medicine teas, etc.).
  • One or more non-behavioral therapies may further include nutritional therapies, acupuncture, mind-body interventions (e.g., relaxation, meditation, yoga), whole system medicine (e.g., Eastern Medicine, Ayurveda), and physical exercises.
  • One or more non-behavioral therapies may further include therapies utilizing a variety of medical devices, such as, but not limited to, wearable devices, ingestible devices, implanted devices, biofeedback devices, cough assist devices, and combinations thereof.
  • a patient suffering from a respiratory health condition may be treated using any combination of the above listed non-behavioral therapies.
  • the digital therapeutics (DTx) systems and methods disclosed herein collect patient medication information, for example in the pre-assessment operation discussed above, via interactive lesson modules such as a pre-assessment module, via modules specifically related to medication, etc., and/or via user entry into a user profile.
  • the prescription digital therapeutics (PDT) systems and methods described herein may collect and offer recommendations regarding an amount and/or timing of dosage of particular medications. Such recommendations regarding amount and/or timing may be absolute and/or relative to other events and/or activities. For example, recommendations may comprise a particular schedule of dosage, e.g., a particular rate, timing (e.g., in a morning, afternoon, or evening), etc.
  • Timings and/or amounts relative to other activities may include timings and/or amounts relative to other activities, such as meal consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • recommendations may be based on data provided by the patient, for example in daily symptom diary entries, via assessment modules, personal model creation modules, etc., such as those described in more detail below.
  • such recommendations are generated via use of one or more machine learning modules that receive, as input, data corresponding to patient symptom and/or habits, as tracked by various modules such as those described herein. In some embodiments, this information is used as feedback, to refine and dynamically update parameters of machine learning modules. In some embodiments, dosage recommendations provided via the approaches described herein are restricted to fall within a pre-defined range, for example as specified by a physician.
  • dosage recommendations provided by technologies (e.g., systems and methods) described herein comprise an identification of one or more specific symptoms, so as to provide recommendation to discuss particular symptoms with a medical professional, such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • a medical professional such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • the non-behavioral therapy components are related to therapies that have previously been administered to the patient. In one embodiment, the non-behavioral therapy components are related to therapies that are currently being administered to the patient. In one embodiment, the non-behavioral therapy components are related to therapies that will be and/or are recommended to be administered to the patient.
  • method flow proceeds to operation 212.
  • the patient profile and pre-assessment data and the patient condition data are processed to generate a personalized intervention regimen for the patient, wherein the personalized intervention regimen defines both behavioral therapy components and non-behavioral therapy components to be administered to the patient.
  • the personalized intervention regimen provides, through client devices, an array of empirically-supported intervention options or actions delivered via a modular and flexible approach, whereby modules of the regimen (a set of overarching principles and evidence-based interventions) can be adaptively provided based on patient states assessed in real-time or near real-time. This allows for individualized treatment planning.
  • guided behavioral therapy technologies as provided herein provide a user with a sequence of interactive lesson modules that the user accesses and interacts with via a graphical user interface (GUI) of a DTx system, which may include a web-based application accessible via a web-browser of a user personal computer (e.g., desktop, laptop, etc.), and/or a mobile application, running, at least in part, on and/or accessible via a user mobile computing device.
  • GUI graphical user interface
  • Each interactive lesson module may represent a guided lesson in a particular behavioral therapy skill and includes specific graphical content and/or graphical widgets designed to introduce a user to a particular behavioral therapy skill, such as keeping a symptom diary, managing symptoms, setting goals, identifying and understanding thoughts e.g., unhelpful and/or irrational thoughts), and the like.
  • interactive lesson modules are arranged in a particular sequence.
  • a DTx system in accordance with approaches described herein may include controls that encourage and/or require a user to progress through a particular sequence of lesson modules in a prescribed order.
  • the DTx system may restrict access by the user to certain lesson modules, occurring later in the sequence, until others have been completed first.
  • the order of modules of the intervention regimen provided can vary from patient to patient and/or vary based on other factors (e.g., due to refinement and training of models, as described in further detail below); however, in some embodiments, all patients will have access to and be offered all of the skill modules through DTx systems executing on their respective client devices.
  • the skills-based interventions rely on skill acquisition (initial phase of learning the new skill), then skill practice before proceeding to learn the subsequent new skill (e.g., in one’s natural home/social environment). Monitoring of task performance and practicing skills is described in further detail below.
  • the modules can allow users to develop and train core skills (e.g., 8 core skills, another suitable number of core skills, etc.) associated with understanding their disease, disorder, and/or condition, therapies available, mind-body connections; relaxation skills; behavioral change, avoidance, and activation; problem solving and coping; habit reversal; cognitive flexibility; social problem solving and communication; and relapse prevention and skills maintenance.
  • core skills e.g. 8 core skills, another suitable number of core skills, etc.
  • sizes of lesson modules - for example, a number of screens a user cycles through, a number of graphical widgets they interact with, an estimated approximate time they are expected to spend with various lesson module(s), etc. - may be tailored to remain relatively small, so as to provide a user ‘bite-sized’ lessons that can and/or are designed to facilitate retention.
  • lesson modules may be designed such that they may be completed with no more than about twenty minutes of continuous user interaction.
  • lesson modules may be designed such that they may be completed with no more than about fifteen minutes of continuous user interaction.
  • lesson modules may be designed such that they may be completed with no more than about ten minutes of continuous user interaction.
  • Disease, condition, and/or syndrome-specific components include content addressing one or more of: an illness narrative, symptom management for coughing, wheezing and other symptoms, disease-specific psychoeducation, social skills training, and emphasis on respiratory health condition (e.g., COPD, asthma, ACOS, chronic cough associated with one or more other respiratory and/or non-respiratory conditions, medication-induced chronic cough, cough hypersensitivity syndrome, idiopathic chronic cough etc.) cognitions, beliefs, and behaviors.
  • Intervention modules can further include general cognitive behavioral components shared across psychological conditions/disorders such as behavioral activation, attentional processes, relaxation, problem solving, cognitive reframing, and other areas.
  • generating a personalized intervention regimen can include defining a type, amount, and/or dosing schedule of a non-behavioral therapy to be administered to the patient in combination with the behavioral therapy components.
  • a dosing schedule for administration of a non- behavioral therapy may be defined relative to a schedule for administration of the behavioral therapy.
  • generating a personalized intervention regimen can include adjusting (e.g., decreasing, increasing, maintaining) an amount of the non-behavioral therapy treatment administered to the patient, for example, based upon the state of the patient’s health condition symptom severity, and/or correspondingly adjusting (e.g., decreasing, increasing, maintaining) an amount of a behavioral therapy treatment provided to the patient, thereby titrating relative treatment types provided to the patient based upon returned outputs of models associated with the methods described.
  • a treatment cocktail can include prescription digital therapeutic aspects (e.g. behavioral therapy components) as well as non-prescription digital therapeutic aspects (e.g. non-behavioral therapy components).
  • FIG. 3A depicts a schematic of architecture 300 implemented for delivery of behavioral therapy intervention regimen components and/or modules, according to one or more embodiments.
  • architecture 300 includes introduction and education module 301, which in some embodiments, also includes symptom assessment module 302.
  • introduction and education module 301 is utilized to generate patient profile and pre-assessment data.
  • the patient profile and preassessment data is generated and/or obtained outside of the functioning of the introduction and education module 301.
  • architecture 300 further includes physical illness narrative module 304, which is utilized to generate patient illness narrative data, which in turn, may be utilized for personalization of an intervention regimen, as well as for constructing personal model 303.
  • the patient profile and pre-assessment data generated by introduction and education module 301, and the patient illness narrative data generated by physical illness narrative module 304 are processed through the DTx system to generate a personalized and adaptive intervention regimen for the patient, as will be discussed in additional detail below.
  • the personalized intervention regimen includes one or more additional interactive therapy modules, such as, but not limited to, relaxation module 306, behavioral change and avoidance module 308, problem solving and coping module 310, respiratory management module 312, cognitive restructuring and flexibility module 314, social problem-solving and communication module 316, relapse prevention and skills maintenance module 318, and adherence module 320.
  • additional interactive therapy modules such as, but not limited to, relaxation module 306, behavioral change and avoidance module 308, problem solving and coping module 310, respiratory management module 312, cognitive restructuring and flexibility module 314, social problem-solving and communication module 316, relapse prevention and skills maintenance module 318, and adherence module 320.
  • a symptom diary and rigger tracking module 321, and a medication adherence module 323 are also provided.
  • the one or more behavioral therapy components are administered to the patient through the user interface of the digital therapeutics (DTx) system according to the personalized intervention regimen generated for the patient.
  • the behavioral and cognitive change interventions described below interrupt the problematic behaviors that are maintaining/perpetuating the targeted symptoms, provide new adaptive coping strategies, and improve perceived control of symptom management in a positive manner.
  • the ability to tailor ‘at the right time’ requires relevant information about the user that is used to decide under what conditions to provide an intervention and the appropriateness of the intervention.
  • the following interactive therapy modules will be discussed with reference to FIG. 3A. As noted above, inclusion of these therapy modules and/or the order of inclusion of these additional therapy modules, in various embodiments, is dependent on the personalized intervention regimen generated for a particular patient.
  • modules are described in a particular order, it should be noted that the modules can be performed in any other suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models described below, and/or based on other factors). Furthermore, aspects of the modules can overlap with each other in any suitable manner.
  • introduction and education module 301 focuses on education about the patient’s disease and symptoms (e.g., more common symptoms, less common symptoms, etc.).
  • the introduction and education module is designed to create awareness about what matters to the patient (their reason for trying the program), introduce therapy concepts (e.g., related to CBT, related to other therapies), introduces skills that the user will build by interacting with the system, and assesses user’s level of commitment for change.
  • an overview of this program links to the patient’s specific psychological/disease management challenges.
  • the following points are emphasized: (1) the treatment is modular/flexible in nature and tailored for patient’s needs (2) the patient will learn skills, that if practiced, will help them manage their symptoms (e.g., with highlighting of red flag symptoms), improve their quality of life, and lessen the toll that the patient’s health conditions take on the patient.
  • Introduction and education module 301 thus can guide the patient to explore the influence that moods, attitudes, beliefs and behavior exert on health and the impact of illness.
  • Introduction and education module 301 can further function to provide tools for education, persuasion (e.g., regarding effectiveness of program completion), personalization, motivation enhancement, setting expectations, eliciting commitment by users, and establishing a relationship between users and the system (e.g., in lieu of a human coach, with supplementation of therapy by a human coach, etc.).
  • Delivery methods for introduction and education module 301 can include one or more of: graphics/animations, metaphorical digital content, interactive exercises provided in a DTx system environment, and a clinical vignette simulating patient-provider interactions.
  • introduction and education module 301 may include a variety of individual sections designed to lay a foundation for progression through later modules. While the sections described below are described in a particular order for illustrative purposes, variations of introduction and education module 301 can additionally or alternatively be arranged in another suitable order, omit sections as desired, and/or include additional sections as desired.
  • FIG. 3B depicts examples of individual sections that may make up an introduction and education module 301 of an intervention regimen, according to one or more embodiments.
  • introduction and education module 301 includes a First Section 322 configured to welcome the patient and introduce the patient to goals of the intervention regimen delivered through the online system and client device.
  • the First Section 322 is delivered by the system in an interactive format (e.g., with video and text content) that creates a feedback loop with users and processes user responses to tailor subsequent module delivery and content, in order to increase engagement.
  • goals can be set in coordination with user desires, with establishment of collaborative empirence. Goals can be specific, in terms of detailed planning of what users will do, including frequency, intensity, duration, and context (e.g., where, when, how, with whom, etc.) of the goal(s).
  • introduction and education module 301 can determine topics having greater relevance to the user’s current issues (e.g., in relation to comorbid conditions, such as anxiety and depression, in relation to health condition subtypes, such as subtypes of asthma, etc.).
  • the First Section 322 can include a description of how the program will involve regular practice (e.g., daily, every two days, every 3 days, etc.) of skills (e.g., core skills described above and below), with a guideline for program length (e.g., 8 weeks, less than 8 weeks, more than 8 weeks), and methods of identifying personal progress (e.g., feeling better with mastery of a subset of skills).
  • introduction and education module 301 includes a Second Section 324 configured to allow the patient to submit information, through a user interface of the DTx system, regarding personal aspects of his/her health condition as an initial physical illness narrative, along with video content to which the patient can compare his/her experiences.
  • Second Section 324 has goals of facilitating emotional awareness, establishing a physical illness narrative that can be revisited as the user gains mastery of skills, and helping the user to articulate and track his/her experiences.
  • introduction and education module 301 includes a Third Section 326 configured for personalization of subsequent portions of the intervention regimen to the patient, by allowing the patient to indicate, through a user interface of the DTx system, which symptoms (e.g., fatigue, coughing, wheezing, hypertension, insomnia, anxiety, depression, medication side effects, other symptoms, etc.) are most bothersome.
  • Third Section 326 can also include architecture for mapping the user’s symptoms and health condition-induced factors to various impacts associated with the user’s values.
  • one or more of the mappings can be created, such as, but not limited to: symptoms associated with chronic fatigue, coughing, wheezing, chest tightness, hypertension, insomnia, anxiety, depression, and other physical symptoms with mappings to aspects of life (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; medication side effects with mappings to aspects of life (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; social/relationship issues (e.g., stress on loved ones, impacts on friendships, etc.) with mappings to behaviors (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; and behavioral, mental, and emotional factors (e.g., exhaustion, lack of control, inability to perform activities, additional help needed for tasks, limitations in diet, limitations in travel, embarras
  • introduction and education module 301 includes a Fourth Section 328 configured for personalization and values identification, with tools for allowing the user to provide data related to positive and negative changes in his/her life that are attributed to having the health condition, in relation to changes in relationships, levels of embarrassment, curiosity, being understood, stress to self and loved ones, confidence, energy levels, senses of lack of control, worry (e.g., about health issues experienced outside of a comfortable environment, about disease progression, and symptoms, about medication effects, about ability to conduct daily activities, about dietary constraints, about travel, etc.), and other aspects.
  • worry e.g., about health issues experienced outside of a comfortable environment, about disease progression, and symptoms, about medication effects, about ability to conduct daily activities, about dietary constraints, about travel, etc.
  • Fourth Section 328 can also revisit aspects of the user’s initial physical illness narrative, with ranking of: symptoms (e.g., chronic fatigue, intense coughing, wheezing, chest tightness, hypertension, insomnia, anxiety, depression, etc.); social/interpersonal factors (e.g., changes to relationships, embarrassment, stress to loved ones, dealing with constant questions about illness, not being understood, etc.); emotional factors (e.g., lack of confidence, mental exhaustion, lack of control, etc.); cognitive factors (e.g., worry about health issues outside of places of comfort, worry about disease progression, catastrophizing, depression, anxiety, other comorbid conditions, etc.); and behavioral factors (e.g., not being able to conduct daily activities, clothing restrictions, travel restrictions, etc.).
  • symptoms e.g., chronic fatigue, intense coughing, wheezing, chest tightness, hypertension, insomnia, anxiety, depression, etc.
  • social/interpersonal factors e.g., changes to relationships, embarrassment, stress to loved ones
  • introduction and education module 301 includes a Fifth Section 330 configured for allowing further customization, by providing the patient with interactive elements that allow the patient to prioritize the order in which content associated with interventions is received.
  • introduction and education module 301 also includes a Sixth Section 332 configured for introducing subsequent portions/modules of the intervention according to user preferences indicated from outputs of the Fifth Section 330, where the goals of Sixth Section 332 include promotion of treatment credibility (e.g., through presentation of video content by patients having experiences similar to those of the user(s)).
  • introduction and education module 301 includes a Seventh Section 334 configured for delivery of content for educating the patient about their condition, where the content includes an animated element and audio format content configured to actively interact with the user.
  • the interactive elements function to gauge how well the patient understands the content provided, and to provide additional content to engage and inform the patient depending upon responses of the patient.
  • the Seventh Section 334 has goals of shaping knowledge of symptoms and treatment components of the intervention regimen and enhancing motivation.
  • Seventh Section 334 can teach users of the system regarding the brain’s role in proper gut functioning, and the connection between the mind and the body. As such, the user can be primed to gain skills related to affecting response to coughing and other respiratory symptoms and regulation by changing behaviors, attentional biases, and automatic thought patterns. Seventh Section 334 can further gage internalization and understanding of the user, with provision of further content in this section and/or the eighth section to promote further understanding.
  • introduction and education module 301 includes an Eighth Section 336 configured for delivery of content for educating the patient in a manner personalized to the patient, where the content includes video and audio format content configured to actively interact with the user, in order to aid the user in understanding influences on the perception of symptoms, based on symptom severity (e.g., related to a threshold level of severity of symptoms, related to fight-or-flight responses, etc.).
  • Eighth Section 336 also provides interactive exercises for learning about physiological-cognitive pathways for perceiving and responding to experienced symptoms and implements architecture for assessing stress and other disease aspects, with implementation of therapeutic techniques for changing reactivity of the brain, thereby decreasing symptom severity.
  • introduction and education module 301 includes a Ninth Section 338 configured for eliciting commitment from the patient, in relation to different set goals of the patient.
  • the digital content of Ninth Section 338 includes interactive elements for creating a reminder system (according to personalized user preferences and formats for receiving reminders), and interactive elements for setting goals to improve one or more aspects of dealing with the patient’s health condition (e.g., with a menu of choices as well as a field for custom user inputs and a field for prompting the user to confirm chosen goals, where example choices can include repeating of tasks, reviewing content, reflecting, identifying entities for social accountability, relocation of application icons on a home screen of a device in a manner that promotes regular use, identifying factors that may obstruct progress, etc.), where the interactive elements allow the patient to confirm when (e.g., specific times), how often, and where the patient will perform activities to meet such goals.
  • Ninth Section 338 includes a brief introduction to subsequent modules of the intervention regimen that are customized to the patient.
  • Ninth Section 338 has goals including setting of expectations, promoting therapeutic persuasiveness, eliciting commitment, increasing user engagement, providing reminders, providing instruction for performing behaviors (e.g., SMART goals).
  • introduction and education module 301 can additionally or alternatively be arranged in another suitable order, omit sections as desired, and/or include additional sections as desired.
  • the term “physical illness narrative,” “personal illness narrative,” and/or “patient illness narrative” may include a narrative expressed by a patient regarding the patient’s personal experiences with a disease, disorder, and/or condition.
  • An illness narrative is typically a narrative solicited from a patient, which enables a healthcare practitioner to build a more complete picture of the patient’s past and present health state in the context of the patient’s life, while providing the patient with an opportunity for self-reflection and validation.
  • physical illness narrative module 304 provides a form of validation (being heard), highlights cognitive distortions/attentional biases and other clinically relevant processes to address, as well as begins the work of emotional exposure. It also provides a point of reference for reflection throughout and at the end of the program. Physical illness narrative module 304 promotes formation of a “personal disease model,” or “personal model” for users, such that they can identify patterns and/or cycles in their disease expression and/or progression, in relation to biology, behaviors, environment, stressors, emotions, and thoughts.
  • the term “personal model,” and/or “personal disease model” may include a construction built based on patient input, which enables the patient to identify stressors, counter-productive behaviors, unhelpful thoughts, and negative emotions as associated with the patient’s disease, disorder, and/or condition.
  • a personal model may be utilized to help a patient identify such links, and to consider possible changes in their behavior that could be implemented to address their symptoms.
  • second patient response data representing the patient’s responses to content provided to the patient through the second interactive therapy module is obtained, for example, through the user interface of the DTx system, or from a variety of patient devices, such as, but not limited to, sensors and/or biometric devices.
  • the DTx system then processes the second patient response data to generate physical illness narrative data, which can then be used for a variety of purposes.
  • the patient illness narrative data can be utilized to personalize an intervention regimen for the patient, as will be discussed in additional detail below.
  • the patient illness narrative data generated by physical illness narrative module 304 can also be utilized as the basis for formation of a personal model, such as personal model 303 of FIG. 3 A, which can then be graphically represented to the user to aid in progression through the intervention regimen.
  • key functions of physical illness narrative module 304 can include creation of a patient’s personal model 303, validation of a patient’s experience, enhancement of self-understanding and illness comprehension, setting the stage for application of behavioral therapy skills to accept uncontrollable elements of physical illness and/or or increase proactivity to address controllable elements of physical illness, and generation of interest for patient engagement.
  • physical illness narrative module 304 introduces a patient to a process for creating a personal model 303, for example so as to orient them and provide content designed to offer helpful motivation.
  • graphical content representing educational material is displayed to a patient, for example to introduce them to concept of vicious cycles, and explain how symptoms, stress, and discomfort can create a feedback loop.
  • graphical content corresponding to shared patient experiences and/or testimonials is displayed.
  • viewing shared experiences from other patients may help prime a patient to be receptive to therapy, provide motivation, and foster a particular sense of therapy.
  • such content can serve to reinforce skills that lesson modules present to a patient, by allowing the patient to hear benefits of various lessons and/or skill practice from real patients.
  • testimonial content can comprise stories from patients describing their experiences living with a particular health condition and which behavioral therapy skills and/or lesson they found particularly helpful.
  • patients providing videos may be loosely coached, e.g., to structure, direct, etc. their stories in a particular way, while still allowing them to provide authentic, ‘from the heart’ descriptions of their experiences. Additionally or alternatively, among other things, viewing relatable experiences from real patients (e.g., and not actors) can provide a patient with a helpful sense of not being alone in their experiences.
  • a patient may be prompted to read about another patient’s experiences with their condition and guided behavioral therapy approaches such as those described herein.
  • a patient may view exemplary personal models created by and shared by others.
  • screens comprising graphical content providing helpful encouragement are displayed within a GUI of the DTx system.
  • Other lesson modules for example any lesson modules described herein and/or additional lesson modules, providing for development of other behavioral therapy skills provided via the technologies described herein may also include content comprising patient experiences and/or testimonials.
  • FIG. 4 depicts an example of formation of a personal disease model, according to one or more embodiments.
  • physical illness narrative module 304 can receive patient report data (or other data) regarding the patient’s illness history (e.g., experiences in a clinical setting, such as with a clinician or hospital environment), thoughts (e.g., thoughts of guilt or responsibility for condition and behaviors, etc.), emotions (e.g., in relation to helplessness, feeling worthless, in relation to embarrassment, etc.), in order to address cognitive distortions for emotional exposure throughout subsequent interactions with the system.
  • patient report data or other data regarding the patient’s illness history (e.g., experiences in a clinical setting, such as with a clinician or hospital environment), thoughts (e.g., thoughts of guilt or responsibility for condition and behaviors, etc.), emotions (e.g., in relation to helplessness, feeling worthless, in relation to embarrassment, etc.), in order to address cognitive distortions for emotional exposure throughout subsequent interactions with the system.
  • physical illness narrative module 304 is used to implement, via a GUI of the DTx system, a structured process for conveniently soliciting patient input of specific counterproductive behaviors, unhelpful thoughts, and negative emotions that they identify, e.g., in their life and/or as associated with their particular condition for use in creating a patient’s own personal model 303.
  • physical illness narrative module 304 and/or other related modules can include architecture for prompting the patient to provide data and/or automatically receiving data (e.g., through API access of health monitoring systems, through receiving of sensor signals of devices of the patient, etc.) pertaining to one or more of: biological aspects (e.g., physiological symptoms); behavioral aspects (e.g., in relation to social event behavior, in relation to other aspects); environmental aspects (e.g., in relation to stress, in relation to temperatures, in relation to diet, etc.); emotional aspects; and thoughts linked to behaviors (e.g., regarding anxiety around uncontrolled coughing, regarding to anxiety around performing various activities, etc.), [0256]
  • physical illness narrative module 304 can include architecture for prompting the patient to provide data and/or automatically receiving data (e.g., through API access of health monitoring systems, through receiving of sensor signals of devices of the patient, etc.) pertaining to one or more aspects such as, but not limited to: respiratory symptoms, stress symptoms, coughing/wheezing frequency and/
  • physical illness narrative module 304 may automatically return an analysis summarizing the personal model 303 of the patient (e.g., in a visual format, etc.). Such personalization thus promotes interruption of vicious cycles for patients.
  • the method 200 A can include returning a mapping with a network of flows between a set of behaviors specific to the patient, a set of thought patterns specific to the patient, a set of physiological symptoms specific to the patient, a set of emotions specific to the patient, and environmental triggers specific to the patient, where returned outputs of models described can be configured to disrupt flows of the network contributing to deterioration of symptoms of the patient.
  • a personal model is constructed as a graphical representation, which comprises text corresponding to patient-selected counter-productive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between each other.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms. Examples of personal model graphical representations will be provided below in the discussion of the DTx user interface.
  • generation of a visual or graphical representation of a personal model 303 may include, retrieving, by the illness narrative module 304, stored information previously input by a patient.
  • a patient may have previously provided input identifying causes and/or stressors that impact their particular condition.
  • a patient provides input corresponding to causes and/or stressors associated with their particular condition via the physical illness narrative module 304.
  • a graphical representation of a partially completed personal model 303 is rendered, showing the patient identified causes and stressors superimposed on a flow diagram, with portions allocated for graphical representations of additional information such as counter-productive behaviors, unhelpful thoughts, and negative emotions, to be displayed.
  • the physical illness narrative module 304 includes graphical content prompting a patient to review their personal model 303.
  • a series of questions e.g., from a predefined list of questions, e.g., based on a therapeutic protocol
  • graphical content including passages of rendered text, mimicking conversation with a therapist can be displayed.
  • encouraging graphical content is displayed, and the patient is returned to a home screen.
  • delivery methods for the physical illness narrative module 304 can include audio format content and/or textual content for guiding exercises.
  • physical illness narrative module 304 may be a subcomponent of multiple modules, such that its content can be revisited. For instance, upon development of core skills associated with the modules, the system can trigger revisitation of aspects of physical illness narrative module 304 within the DTx system, such that patients can solidify new skills, reflect on their initial versions of their physical illness narrative and what has changed, generalize skills, maintain skills, and implement cognitive flexibility.
  • a relaxation module 306 provides a patient with understanding of what physiological stress feels like (e.g., with education on fight or flight responses) and recognition of the importance of actively optimizing their stress response, particularly because of the connection between stress reactivity, stress hormones and autonomic arousal, and flares in symptoms.
  • Relaxation module 306 informs the patient that (1) stress is a natural reaction and it causes its own physical symptoms (2) the brain does not differentiate between an event that is actually happening to us and an event that we only think is happening, and (3) the connection between stress and flares and symptoms.
  • relaxation module 306 provides the patient with a rationale for each type of relaxation and how it is tailored for their specific stress symptoms, and provides guided relaxation exercises (e.g., through an application associated with the DTx system executing at the client device).
  • Relaxation module 306 promotes mastery of at least one relaxation technique.
  • Key functions of relaxation module 306 can include decreasing physiological reactivity associated with stress, worry, anxiety, and discomfort, activation (for depression symptoms), and stress management.
  • Delivery methods for relaxation module 306 can include audio format and/or visual content for guiding exercises associated with targeted muscle groups for progressive muscle relaxation, video-guided demonstration of diaphragmatic breathing, and haptic feedback for exercise guidance.
  • relaxation module 306 can include video format content that introduces the general concept of relaxation; educates the patient on the applicability of stressreduction exercises to specific health conditions, with active text boxes that promote user engagement and personalization of the module to the patient’s specific symptoms and contexts; addresses common doubts or concerns about relaxation; promotes a guided breathing exercise with a diaphragmatic breathing demonstration and corresponding animated graphic; promotes guided exercises for muscle relaxation using progressive muscle relaxation (PMR) techniques using graphical animations (e.g., of targeted muscle groups); provides information on how relaxation practices can be used (e.g., for cough or other respiratory symptoms, for anxiety, for other stressors, etc.), and encourages practice of exercises by including active interactive elements that the patient can use for scheduling and/or accountability in practicing exercises.
  • PMR progressive muscle relaxation
  • behavior change and avoidance module 308 provides content covering the importance of activation and approaching avoided situations/experiences in breaking the cycle of persistent respiratory symptoms and depressive and/or anxious mood.
  • Specific action plans are developed for decreasing avoidance behavior.
  • Key functions of this module can include linking behaviors and mood, mood monitoring (e.g. self- monitoring), activity scheduling, identifying and counteracting avoidance behavior, action planning, activity scheduling, creating anxiety hierarchies, self-monitoring, behavioral experiments, exposure (e.g., imaginal exposure, actual exposure to counteract anxiety) and systematic desensitization for anxiety, coping performance, confidence building, and routine building.
  • Delivery methods for behavior change and avoidance module 308 can include use of automated tailoring for choosing topics that have greater relevance to a patient's current problems (e.g., if a patient reports anxiety, information about physiological responses of anxiety and their relationship with thoughts and behaviors would be more appropriate than information about the physiological symptoms of depression or generic stress).
  • problem solving and coping module 310 provides content covering how to differentiate controllable vs. uncontrollable stressors, problem- focused coping (e.g., with problem identification, solution brainstorming, evaluation of solution options, etc.) vs. emotion-focused coping (e.g., with grounding exercises), as well as types of adaptive and maladaptive coping. Mood/anxiety/stress may be managed/ameliorated by using externally-focused coping to distressing and modifiable conditions and internally-focused coping to adjust one’s expectations and interpretations for unmodifiable conditions.
  • problem solving and coping module 310 can include architecture and instructions for promoting practicing of problem solving and coping methods by the patient, such that the patient is better able to handle stronger symptoms (and milder symptoms).
  • Delivery methods for problem solving and coping module 310 can include digital content with explanations and testimonials of other patients and their uses of problem solving skills, peer support groups facilitated by the DTx system, and other delivery methods.
  • cough management module 312 focuses on awareness of the respiratory experience, discusses how cough or restricted breathing (e.g., wheezing) influences mood and vice versa, promotes recognition of certain behaviors (e.g., overactivity, avoidance) and automatic thoughts that may influence breathing and cough management as well as how to feel more in control of cough/breathing by also improving physical and role functioning though increasing adaptive behaviors/coping (attention) and decreasing avoidance/maladaptive behaviors.
  • Key functions of respiratory management module 312 can include behavioral experimentation, behavior substitution, acceptance of respiratory interruptions, and self-monitoring, with one or more disease-or-syndrome-specific targets.
  • cough management module 312 can include architecture and content for educating patients regarding re-directing attention away from respiratory symptoms by focusing on parts of the body that are not in distress, and other methods.
  • the system can include a processor with instructions stored in non-transitory media that when executed, perform operations for identifying when a patient is in a state of discomfort, and triggering a response (e.g., verbal cues and instructions to modify attention and/or engage in various cough/wheezing/chest tightness observation exercises, a change in the environment of the patient, by playing music, by activating a display and providing video or image content, by providing haptic stimulation to the patient, etc.).
  • a response e.g., verbal cues and instructions to modify attention and/or engage in various cough/wheezing/chest tightness observation exercises, a change in the environment of the patient, by playing music, by activating a display and providing video or image content, by providing haptic stimulation to the patient, etc.
  • delivery methods for respiratory management module 312 can include audio format content and/or textual content for managing discomfort (e.g., with music, exercise, etc.) and/or for promoting attention restructuring.
  • FIG. 3C depicts examples of individual sections that may make up a respiratory management module of an intervention regimen, according to one or more embodiments.
  • respiratory management module 312 can include a First Section 340 that includes content focused on common types of discomfort (e.g., coughing, wheezing, shortness of breath, etc.) associated with the patient’s health condition.
  • a First Section 340 that includes content focused on common types of discomfort (e.g., coughing, wheezing, shortness of breath, etc.) associated with the patient’s health condition.
  • respiratory management module 312 can include a Second Section 342 focusing on facts about breathing associated with the patient’s health condition, in relation to controlling coughing and wheezing, bronchial restriction for people with health conditions vs. without health conditions, factors that can trigger respiratory difficulties, and other factors.
  • Second Section 342 can also include image and video content (e.g., including testimonials of patients similar to the user) and other interactive exercises.
  • cough management module 312 can include a Third Section 344 describing differences between acute cough and chronic cough associated with health conditions, and therapies associated with each type of discomfort.
  • respiratory management module 312 can include a Fourth Section 346 focused on cough response attributed to specific nerves of the brain, with interactive exercises and content for re-training the brain to adjust cough response (i.e., cough modulation). I
  • respiratory management module 312 can include a Fifth Section 348 focusing on factors that affect respiratory conditions (e.g., smoking, pollution, obesity, reflux, anxiety, worry, etc.) and methods for modulating cough/chest tightness intensity and duration (e.g., relaxation, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, medicine, etc.).
  • factors that affect respiratory conditions e.g., smoking, pollution, obesity, reflux, anxiety, worry, etc.
  • methods for modulating cough/chest tightness intensity and duration e.g., relaxation, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, medicine, etc.
  • cough management module 312 can include a Sixth Section 350 describing the importance of relaxation in modulating cough frequency and creation of a respiratory management plan.
  • respiratory management module 312 can include a Seventh Section 352 focused on the effects of coughing and restricted breathing on negative emotions, with architecture for including customized content from the patient’s illness narrative (associated with other modules), in a textual, audio, and/or visual format, and allowing the patient to update his/her illness narrative.
  • respiratory management module 312 can include an Eighth Section 354 focused on development of automatic habitual thinking patterns to interrupt and break these negative cycles.
  • respiratory management module 312 can include a Ninth Section 356 with architecture for presenting a patient testimonial regarding a personal experience of catastrophizing thoughts and the effects on worsening mood, discomfort, and perpetuation of biased attentional processing.
  • respiratory management module 312 can include a Tenth Section 358 focused on promoting a healthy lifestyle to protect the body against stress, cough/wheezing flares, and other health condition symptoms.
  • respiratory management module 312 can include an Eleventh Section 360, which provides architecture for helping the patient establish goals in various activities in his/her daily life (e.g., school, public speaking, sports, etc.), as they relate to cough/wheeze management.
  • respiratory management module 312 can include a Twelfth Section 362 focused on activity pacing to prevent increases in cough or other symptoms, with interactive content (e.g., derived from patient testimonials, etc.).
  • respiratory management module 312 can include a Thirteenth Section 364 focused on providing examples of activity pacing (e.g., taking breaks during physical exercise, setting limits in relation to periods of respiratory difficulties, etc.), with interactive modules for setting goals specific to activities that the patient values and/or enjoys.
  • activity pacing e.g., taking breaks during physical exercise, setting limits in relation to periods of respiratory difficulties, etc.
  • respiratory management module 312 can also include a Fourteenth Section 366 focused on helping the patient to generate a respiratory management plan with respect to relaxation skills gained (e.g., diaphragmatic breathing, progressive muscle relaxation, etc.), cognitive flexibility skills (e.g., catastrophizing avoidance, etc.), smoking and outdoor activities (e.g., with respect to avoiding cigarette smoke or air pollution, etc.), with respect to activity performing, and with respect to activity pacing.
  • relaxation skills gained e.g., diaphragmatic breathing, progressive muscle relaxation, etc.
  • cognitive flexibility skills e.g., catastrophizing avoidance, etc.
  • smoking and outdoor activities e.g., with respect to avoiding cigarette smoke or air pollution, etc.
  • cognitive restructuring and flexibility module 314 targets one’s interpretations of events/experiences (e.g., how core thoughts influence our feelings and behavior).
  • Cognitive restructuring and flexibility module 314 emphasizes connections between thoughts and physical sensations due to a variety of symptoms.
  • the aim of cognitive restructuring and flexibility module 314 is to teach patients how to identify unhelpful automatic thinking patterns and develop a new pattern of realistic, balanced, and flexible thinking.
  • a health behavior change is targeted in the area of sleep and worry by providing education about worry and how it might interfere with sleep.
  • Strategies to manage worry before bedtime e.g., use a relaxation practice are provided as well as basic sleep hygiene.
  • Cognitive restructuring and flexibility module 314 can include resetting of cognitive distortions (e.g., about self, others, and the world), identification of unhelpful thoughts, challenging of automatic thoughts, creating more balanced thoughts, re-attribution, appraisals of moods, and improving cognitive flexibility.
  • Delivery methods for cognitive restructuring and flexibility module 314 can include a tool providing digital content for reassembling a traditional thought record in which patients enter an unhelpful automatic thought and select from a list of negative thoughts that best matched. After selecting from a list of most common automatic thoughts, the tool can generate a list of possible challenge/altemative thoughts. The patient can then input their own personalized challenge/altemative thought.
  • social problem solving and communication module 316 provides content promoting effective social behaviors in the context of a variety of health conditions.
  • Social problem solving and communication module 316 can provide tools for one or more of: action planning, social skills training, social support, exposure, and activation, with identification of oneself as a role model, and presentation of information regarding vicarious consequences.
  • social problem solving and communication module 316 is intended to assist interactions between patients and their social environment in the context of their health condition(s), and how to communicate effectively about the medical condition/disease.
  • Some examples include requesting support in college (disability services office) or at work; informing a patient that his/her behavior may be an example to others; coping with sense of urgency to cough or tightness in one’s chest; and problem solving about reversing coughing behaviors.
  • Key functions of social problem solving and communication module 316 can include activation and action planning, problem solving by analysis of factors influencing the behavior and generating strategies to overcome barriers, demonstrating one’s ability to cope, decreasing avoidance behaviors, ensuring practice of new coping skills, when symptoms are more severe (e.g., with behavioral rehearsal, etc.). Delivery methods for social problem solving and communication module 316 can include digital content with testimonials of other patients and their uses of problem solving, peer support groups facilitated by the DTx system, and other delivery methods.
  • social problem solving and communication module 316 can include architecture for triggering actions based on detected changes in symptoms. For instance, in one example, social problem solving and communication module 316 can process data generated by interactions between the user and the system (e.g., with sensor-based monitoring of symptom progression, with user input-based monitoring of symptom progression, etc.), and based upon the data, generate control instructions for recommended actions that would improve social problem solving ability.
  • Examples of recommended actions can include one or more of: guidance for conducting a conversation regarding symptoms (e.g., example language for communicating discomfort, reflux, or other-related symptoms to an entity, so that the user can reduce anxiety about the reactions of others, etc.); triggering automatic communications between the patient and an entity (e.g., automatically sending a private message to a teacher so that the teacher can excuse the patient to manage cough-related, respiratory-related, and/or other symptoms); and performing other suitable actions.
  • symptoms e.g., example language for communicating discomfort, reflux, or other-related symptoms to an entity, so that the user can reduce anxiety about the reactions of others, etc.
  • triggering automatic communications between the patient and an entity e.g., automatically sending a private message to a teacher so that the teacher can excuse the patient to manage cough-related, respiratory-related, and/or other symptoms
  • performing other suitable actions e.g., guidance for conducting a conversation regarding symptoms (e.g., example language for communicating discomfort, reflux, or other-related symptoms to an entity, so that the user can
  • relapse prevention and skills maintenance module 318 encourages maintenance/continuation of treatment gains and reinforces positive changes in thoughts and behavior that were accomplished during the active treatment time.
  • Key functions of relapse prevention and skills maintenance module 318 can include skills generalization, skills maintenance, and adaptive monitoring to refresh skills learned. Additionally, relapse prevention and skills maintenance module 318 can perform one or more of: informing patients of signs of relapse into old patterns, development of specific proactive coping tools for future challenges, encouragement of proactive coping for mood regulation, explaining perseverance, education regarding sequential coping strategies, and identification of skills/techniques that were most effective for the user, based on analysis of user outcomes. Delivery methods for trigger avoidance and skills maintenance module 318 can include digital content and/or notifications related to monitored states of the patient (e.g., related to relapse) as described in further detail below.
  • an intervention regimen may include a symptom (including medication side effects) diary module that introduces and familiarizes a patient with techniques for tracking their respiratory condition symptoms and identifying cough triggers.
  • a symptom including medication side effects
  • technologies described herein provide a convenient interface that facilitates patient tracking and/or monitoring of their respiratory health condition symptoms on a regular basis.
  • a patient may use utilize the DTx system disclosed herein to rate cough frequency and stress on a scale, provide ratings characterizing constipation and diarrhea (or other medication side effects), and provide information characterizing their daily activity routines.
  • symptom diary and trigger tracking module 321 may include features providing options for setting goals, for example, goals pertaining to a regular timing and/or type of non-triggering alternative (e.g., re-directing habits) and/or activity (e.g., physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary, etc.).
  • goals pertaining to a regular timing and/or type of non-triggering alternative e.g., re-directing habits
  • activity e.g., physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary, etc.
  • daily activities with associated respiratory symptoms may be characterized via use of a streamlined tracking interface.
  • conventional tracking tools typically allow users to input a wide array of information, including detailed information characterizing types of activities that may trigger cough and/or wheeze episodes.
  • approaches described herein provide a streamlined tracking interface that expressly limits a range of user input and avoids allowing a user to input detailed information regarding daily activities and known/potential cough and/or wheeze associations.
  • less finely grained information such as a broad categorization of activity (e.g., meals, sleep, exercise, interactions, stressors), and a particular time at which the activity occurred mapped against cough histories can provide sufficient information for tracking cough/wheeze triggers and/or evaluating respiratory health condition symptoms, in the context of daily activities and/or identifying patterns.
  • this approach may facilitate user input of activities information, and can improve adherence to treatment protocols.
  • this approach encompasses recognition that patients suffering from certain respiratory health conditions and associated mental health conditions, such anxiety and/or depression, can suffer from unhelpful thoughts and compulsive behavior, which conventional, overly complex activity trackers may exacerbate. Accordingly, among other things, by providing, in some embodiments, a streamlined activity tracking approach, technologies described herein can address unique challenges associated with a particular patient population.
  • the present disclosure provides methods for facilitating activity and respiratory symptom tracking by a subject suffering from a chronic health condition, for example including steps of: causing, by a processor of a computing device, display of a streamlined alcohol/nicotine-tracking user interface comprising one or more trigger tracking features, wherein, for each of one or more particular daily use, the tracking features provide for user input of use data, including one or more of: binary user input indicating how much nicotine consumed or reflux/post-nasal incidents each day, and a time at which the particular trigger was experienced.
  • the symptom/trigger data input by the user via the tracking features is received by the processor stored for display and/or further processing, by the processor, the use data.
  • the digital therapeutics (DTx) system described herein can include mechanisms to facilitate a patient’s adherence to one or more particular non-behavioral therapies, such as dosing regimens of pharmaceutical compositions, nutraceutical compositions, and/or therapies involving use of medical devices.
  • various lesson modules and/or practice modules, as described herein may include features that allow a patient to track their adherence to medication.
  • medication adherence module 323 may include features that provide for patient input (e.g., via one or more graphical widgets) of when and what medication the patient took. Tracking features such as these may serve as a helpful reminder to the patient to actually take their medication.
  • tracking features may allow identification of patterns related to a patient’s medication regimens, such as benefits with respect to symptom improvement conferred by adherence to a regimen and/or symptoms and/or activities that are associated with degree to which the patient adheres to a medication regimen.
  • medication adherence module 323 may provide features for setting goals pertaining to adherence to medication.
  • goals pertaining to medication adherence may include goals relating to a timing and/or particular type of medication, such as adherence to a regular schedule and/or timing of a particular medication.
  • medication adherence goals may include timing of a particular medication in relation to symptoms (e.g., of a user physiological condition) and/or other events, such as relative to alcohol/nicotine consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • guided behavioral therapy technologies described herein may provide alerts, such as in-app pop up messages, push notifications, digital calendar integration, email/text message reminders, and the like, that facilitate medication adherence. Such notifications may include, for example, reminders to take particular medications.
  • the DTx systems and methods as described herein may provide for communication between a patient and one or more external medication tracking devices, as will be discussed in additional detail below.
  • guided behavioral therapy technologies described herein may also provide content (e.g., graphical content, e.g., presented within a GUI, such as those described herein) that explains and/or educates a user about one or more particular medications that they are taking.
  • medication adherence module 323 may be a standalone module, or may be included in the DTx system as part of another module, such a daily symptom diary and trigger tracking module 321 discussed above.
  • exercises associated with the intervention regimen can include one or more of: a card sorting task to identify a patient’s reinforcers/motivators (e.g., in relation to social reinforcers, reminders, accountability, gaming/competition, responsiveness to quantitative summary feedback, monetary incentives, altruism, learning, elimination of symptoms, etc.); computerized performance tasks (e.g., delayed discounting) to measure/identify salient reinforcers and/or learning style; and performance tasks (e.g., validated distress tolerance computer tasks, tasks associated with mimicked social interactions, etc.) to measure emotional awareness and ability to tolerate various types of distress (psychological, physical, etc.).
  • a card sorting task to identify a patient’s reinforcers/motivators (e.g., in relation to social reinforcers, reminders, accountability, gaming/competition, responsiveness to quantitative summary feedback, monetary incentives, altruism, learning, elimination of symptoms, etc.); computerized performance tasks (e.g., delayed discounting) to measure/identify salient reinforcer
  • modules are described in a particular order, it should be noted that the modules can be performed in any other suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models described below, and/or based on other factors). Furthermore, aspects of the modules can overlap with each other in any suitable manner.
  • method flow proceeds to operation 215.
  • the one or more non-behavioral therapy components are administered to the patient in combination with the one or more behavioral therapy components according to the personalized intervention regimen generated for the patient.
  • administering therapies according to an intervention regimen can further include administration of other types of interventions, such as those including non-behavioral therapy components, in combination with interventions that include behavioral therapy components, by way of the online system in coordination with other devices, where monitoring of performance of activities with such interventions is described below.
  • non-behavioral therapy components can include one or more of: pharmaceutical compositions, nutraceutical compositions, nutritional therapies, whole system medicine, mind-body interventions, physical exercise, and biofeedback.
  • some therapies can be administered via a variety of routes, such as, but not limited to, ocular, oral, parenteral, topical, bronchial (e.g., by bronchial instillation), buccal, dermal (which may be or comprise, for example, one or more of topical to the dermis, intradermal, interdermal, transdermal, etc.), enteral, intra-arterial, intradermal, intragastric, intramedullary, intramuscular, intranasal, intraperitoneal, intrathecal, intravenous, intraventricular, within a specific organ (e.g., intrahepatic), mucosal, nasal, oral, rectal, subcutaneous, sublingual, topical, tracheal (e.g., by intratracheal instillation), vaginal, and vitreal.
  • routes such as, but not limited to, ocular, oral, parenteral, topical, bronchial (e.g., by bronchial instillation), buccal,
  • administration may be performed via a medical device such as, for example, a wearable device, an implanted device, and/or an ingestible device.
  • a medical device such as, for example, a wearable device, an implanted device, and/or an ingestible device.
  • wearable devices may be designed and/or demonstrated to monitor respiratory symptoms.
  • therapies can be self-administered by patients, for example, in the case of therapies involving physical exercise or mind-body interventions.
  • method flow proceeds to operation 216.
  • the patient at operation 216, the patient’s interactions with the one or more behavioral therapy components and the one or more non-behavioral therapy components are monitored remotely in near real-time to generate patient interaction data.
  • an embodiment of the online system in coordination with the network and a client device, can monitor the patient’s interactions with the behavioral and non-behavioral therapy components contemporaneously with administration of the intervention regimen.
  • Monitoring patient interactions functions to provide intimate understanding of progress of the patient in achieving health goals, and to provide further personalization of and administration of intervention content at appropriate times, in order to maintain or improve progress of the patient.
  • Monitoring is preferably performed in near-real time or real time, such that actions can be taken to adjust interventions to patient states according to just-in-time adaptive intervention (JITAI) protocols.
  • JITAI just-in-time adaptive intervention
  • monitoring can be performed with any suitable delay (e.g., in relation to achieving better accuracy of assessed states of the patient).
  • monitoring can be performed using survey components, such as the patient reported outcome instruments described above, which may be delivered with interactive interventions of the intervention regimen, where the patient is prompted and provided with interactive elements that allow the patient to provide self-report data indicating progress statuses.
  • Monitoring can additionally or alternatively be performed with processing of other non-survey data streams, where the non-survey data streams are associated with system or device usage metrics, social networking behavior extracted from usage of social networking platforms and communication platforms, sensor-derived data, and/or other data. Monitoring can thus occur with any frequency and/or level of intrusiveness.
  • operation 216 can process monitoring data (e.g., real time data, non- real time data, dynamic data, static data) with a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • monitoring data e.g., real time data, non- real time data, dynamic data, static data
  • a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • ecological momentary assessments of the patient can be used for monitoring.
  • client device usage parameters can be used for monitoring.
  • client device usage parameters can include frequency of application switching, duration of time spent in association with each application login, screen time parameters, data usage associated with different applications and/or types of applications (e.g., social networking, creative, utility, travel, activity-related, etc.) executing on the client device of the patient, time of day of application usage, location of device usage, and other client device usage parameters.
  • applications e.g., social networking, creative, utility, travel, activity-related, etc.
  • the system can process voice data and/or text communication data of the patient for monitoring and modifying interventions and program aspects.
  • voice data can include voice sampling data from which emotional states can be extracted using voice processing models.
  • natural language processing of textual data e.g., from communication platforms, from social networking platforms
  • the client device can be used to provide context for behaviors of the patient and/or assess emotional or cognitive states of the patient.
  • electronic health record data can be used for monitoring.
  • the online system can be configured to receive a notification providing information regarding the type of care the patient has received, and to use this data for monitoring statuses of the patient.
  • the system can include architecture for processing data from other sensors of the client device, devices in the environment of the patient, and/or wearable computing devices can be used for monitoring.
  • Such device data can include activity data, location data, motion data, biometric data, and/or other data configured to provide context to behaviors associated with the health condition of the patient.
  • motion data from motion of sensors of the client device can indicate that the user is coughing or wheezing, and may be experiencing symptoms that can be addressed with components of the intervention regimen.
  • device usage data can indicate that the patient has been using a particular device (e.g., a scratcher device, where use does not require extensive motion of the patient), in a fixed location (e.g., from GPS data), and in a prone position (e.g., from motion chip data), and may be experiencing health condition symptoms that can be addressed with components of the intervention regimen.
  • a particular device e.g., a scratcher device, where use does not require extensive motion of the patient
  • a fixed location e.g., from GPS data
  • a prone position e.g., from motion chip data
  • the DTx systems and methods as described herein may provide for communication between a patient and one or more external medication tracking devices, such as a smart pill packet, smart pill bottle, etc.
  • external medication tracking devices such as a smart pill packet or smart inhaler may communication with and provide data to a cloudbased system to indicate, for example, if/when/how often a patient takes their medication.
  • technologies described herein may receive updates from the cloud-based system to track the patient’s taking of their medication.
  • An application may, for example, use received updates to check that a patient is adhering to their medication schedule, goals, etc., and present reminders accordingly.
  • technologies described herein may provide for other approaches of communication, e.g., directly, with external medication devices, for example wirelessly, e.g., over a wireless network, via Bluetooth®, and the like.
  • monitoring the patient’s interactions with the behavioral and non-behavioral therapy components includes obtaining one or more of: patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient medications data; patient medication adherence data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • active monitoring of patient states can be used to adjust administration of intervention regimen modules in order to appropriately meet the needs of the patient.
  • Other data and combinations of data can, however, be used for monitoring.
  • method flow proceeds to operation 218.
  • the patient interaction data is processed by the DTx system to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen.
  • the recommended modifications to the patient’s personalized intervention regimen include recommended modifications to aspects of the behavioral therapy components of the regimen, based on processing of patient interaction data representing patient interactions with the behavioral therapy components of the regimen, wherein the patient interaction data is generated by the monitoring operation 216, as discussed above.
  • operation 218 functions to generate recommendations for further customization of the behavioral therapy components of the intervention regimen, in order to improve personalization of delivered content to meet the needs of the patient, in an adaptive manner.
  • Operation 218 can also function to generate recommendations for increasing engagement between the patient and the intervention regimen, in order to improve effectiveness of provided treatments and increase the chances of success of the patient in achieving their goals.
  • behavioral therapy components of the intervention regimen may include a plurality of interactive therapy modules.
  • recommendations for modifying aspects of the behavioral therapy components of the patient’s personalized intervention regimen can include one or more recommendations, such as, but not limited to: adjusting the order of administration of the behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records (EHRs); updating the patient’s personal health records (PHRs); updating the patient’s open medical records, for instance by writing to or modifying records whenever new information is generated regarding the user/patient.
  • EHRs electronic health records
  • PHRs personal health records
  • recommendations for modifying aspects of the behavioral therapy components of the patient’s personalized intervention regimen can include recommendations for providing features for increasing engagement and optimal learning.
  • specific descriptions self-reported by the patient can be used in subsequent portions of the intervention regimen to increase personalization of the intervention to drive engagement.
  • features for increasing engagement and optimal learning can include features that mimic therapist/healthcare provider, or social group interactions (e.g., patient testimonials, clinician video content, etc.).
  • features for increasing engagement and optimal learning can include features that link the patient’s specific current problems and/or challenges faced by the patient as a trigger to notify the patient to interact with content of the intervention regimen and recommend appropriate skill for improving health states.
  • the recommended modifications to the patient’s personalized intervention regimen include recommended modifications to aspects of the non-behavioral therapy components of the regimen, based on processing of patient interaction data representing patient interactions with the non-behavioral therapy components of the regimen, wherein the patient interaction data is generated by the monitoring operation 216, as discussed above.
  • recommendations for modifying aspects of the non-behavioral therapy components of the patient’s personalized intervention regimen can include one or more recommendations, such as, but not limited to: adjusting the order of administration of the non- behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the dosage amount of the non-behavioral therapy components; and adjusting the dosage schedule of the non- behavioral therapy components .
  • a dosage amount of the non-behavioral therapy treatment may be based upon the state of the patient’s health condition symptom severity.
  • a dosing schedule for administration of a non-behavioral therapy may be relative to a schedule for administration of the behavioral therapy.
  • Such recommendations regarding amount and/or dosing may be absolute and/or relative to other events and/or activities.
  • recommendations may comprise a particular schedule of dosage, e.g., a particular rate, timing (e.g., in a morning, afternoon, or evening), etc.
  • Recommendations regarding timing may include timings and/or amounts relative to other activities, such as meal consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • adjusting an amount of the non-behavioral therapy can include correspondingly adjusting an amount of a behavioral therapy treatment provided to the patient, thereby titrating relative treatment types provided to the patient based upon returned outputs of models associated with the methods described.
  • dosage recommendations provided via the approaches described herein are restricted to fall within a pre-defined range, for example as specified by a physician.
  • dosage recommendations provided by technologies (e.g., systems and methods) described herein comprise an identification of one or more specific symptoms, so as to provide recommendation to discuss particular symptoms with a medical professional, such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • recommendations may be generated via use of one or more machine learning modules that receive, as input, data corresponding to patient symptom and/or habits, as tracked by various modules such as those described herein. In some embodiments, this information is used as feedback, to refine and dynamically update parameters of machine learning modules.
  • one or more notifications are issued to a computing device accessible to one or more health practitioners associated with the patient (e.g., nurses, physicians, dieticians, therapists, etc., who may be registered to view patient updates with a secure hub).
  • one or more notifications are issued to a patient computing device, for example, through the DTx system disclosed herein, and/or via an out-of-app notification, such as text message, push notification, email, calendar reminder, etc.
  • the one or more notifications include options and/or recommendations for modifications to the patient’s personalized intervention regimen, for the patient to discuss with their healthcare practitioner
  • the one or more notifications include identification of activities, behaviors, and/or symptoms of the patient.
  • the one or more notifications include options and/or recommendations for new therapies and/or potential adjustments to current therapies being administered to the patient.
  • the options and/or recommendations are based on potential compatibility of new and/or modified therapies with the identified activities, behaviors, and/or symptoms of the patient.
  • options and/or recommendations may include adjusting aspects of the patient’s intervention regimen, such that it is compatible with the patient’s physical exercise, travel, work, etc. schedule, adjusting aspects of the patient’s intervention regimen in view of the patient’s activities, behaviors, and/or symptoms to improve a potential side-effect profile of the patient, and/or adjusting aspects of the patient’s intervention regimen based on the demonstrated or perceived ability of the new and/or modified therapies to alleviate particular symptoms experienced by the patient.
  • the one or more notifications include options and/or recommendations for one or more tests for the patient to complete (e.g., blood test).
  • the one or more notifications include alerts and/or reminders to the patient to selfadminister at least a portion of a therapy.
  • a notification may be a reminder to take a particular pharmaceutical composition and/or a particular nutraceutical composition and/or a notification may be a reminder to use a wearable device for a prescribed period of time according to a particular therapeutic regimen.
  • method flow proceeds to operation 220.
  • aspects of the behavioral therapy and/or the non-behavioral therapy components defined by the patient’s personalized intervention regimen may be modified based on the intervention modification data.
  • an embodiment of the online system in coordination with the network and a client device can, based on the intervention modification data, perform one or more actions to dynamically modify aspects of the behavioral therapy and/or the non-behavioral therapy components defined by patient’s personalized intervention regimen.
  • dynamically modifying aspects of the behavioral and non- behavioral therapy components of the patient’s personalized intervention regimen includes one or more of adjusting the order of administration of the behavioral therapy components; adjusting the order of administration of the non-behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the dosage amount of the non-behavioral therapy components; adjusting the dosage schedule of the non-behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records; updating the patient’s personal health records; updating the patient’s open medical records; and increasing personalization of the intervention regimen.
  • dynamically modifying aspects of the patient’s personalized intervention regimen to promote patient engagement can be done using one or more of artificial reality tools (e.g., augmented reality platforms, virtual reality platforms) for reducing depression, anxiety, discomfort, and/or other symptoms; artificial intelligence-based coaching elements for driving interactions with the patient; smart assistants (e.g., AlexaTM, SiriTM, GoogleTM Assistant, etc.) for assisting the patient in relation to task management, gamification elements within intervention regimen-associated applications executing on the client device; gamification elements of other devices (e.g., cough monitoring device that tracks respiratory function throughout the day to generate a “success score”); smart pill devices and/or medicationdispensing devices that provide insights in an engaging manner in coordination with intervention regimen modules; adjustment of reinforcement schedules (e.g., in relation to reward sensitivity, positive reinforcement, negative reinforcement, etc.) for providing intervention regimen content to the patient; and other elements for increasing engagement.
  • artificial reality tools e.g., augmented reality platforms, virtual reality platforms
  • artificial intelligence-based coaching elements
  • features for modifying, updating, and/or personalizing the intervention regimen, as well as for promoting engagement with the intervention regimen can be delivered within modules of the intervention regimen before, during and/or after monitoring of the patient at operation 216.
  • the patient’s personalized intervention regimen is modified dynamically, in near-real time, based on the intervention modification data generated at operation 218.
  • method flow may return to operation 214 to continue administering the intervention according to the modified personalized intervention regimen.
  • method flow proceeds to END operation 222, and the method 200A for treating respiratory health conditions using digital therapeutics in combination with other therapies is exited to await new instructions.
  • FIG. 2B depicts a flowchart of a method 200B for providing adaptive interventions for respiratory health conditions, according to one or more embodiments.
  • method 200B begins at BEGIN 224, and method flow proceeds to operation 226.
  • operation 226 a pre-assessment of a patient exhibiting one or more respiratory health condition symptoms is performed.
  • an embodiment of the online system in coordination with the network and a client device, can perform operation 226, performing a pre-assessment of a patient exhibiting one or more respiratory health condition (or co-morbidity) symptoms, contemporaneously with executing an onboarding process with the patient with the online system.
  • Operation 226 functions to retrieve data describing characteristics of the patient, preferences of the patient, goals of the patient and/or any other suitable patient features that can be used to provide adaptive interventions in a customized and personalized manner, in order to promote user engagement with the intervention regimen(s) described in subsequent operations of the method 200B.
  • operation 226 can include pre-assessing and onboarding patients and assessing characteristics including one or more of: demographics (e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.), household situations (e.g., living alone, living with family, living with a caregiver, etc.), dietary characteristics (e.g., omnivorous, vegetarian, pescatarian, vegan, reduced carbohydrate consumption, reduced acid consumption, gluten-free, simple carbohydrate, or other dietary restrictions, etc.), levels of activity, levels of alcohol and/or nicotine consumption, levels of drug use, psychological symptom severity, levels of mobility (e.g., in relation to distance traveled in a period of time), biomarker statuses (e.g., inflammatory markers, exhaled breath marker statuses, etc.), weight, height, body mass index, percentage of skin impacted, genotypic factors, durations of mindfulness (e.g., mindful minutes), e.g., mindful minutes, etc.,
  • the pre-assessment and/or onboarding process performed in operation 226 can identify the patient as having respiratory health condition symptoms such as, but not limited to, one or more of: breathlessness, chronic cough, fatigue, difficulty breathing, chest tightness, coughing, wheezing, dyspnea, dry cough, hacking cough, and combinations thereof.
  • a set of signals can encode physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user, from the pre-assessment, health record access, API access of health monitoring systems, and/or biometric sensors. Furthermore, such signals can be collected repeatedly throughout performance of the methods described, as will be discussed in additional detail below.
  • the pre-assessment can be configured to receive information regarding (or automatically detect, or automatically extract, based upon symptoms, etc.) the subtype(s) of a respiratory disorder (e.g., inflammation-based subtypes of asthma such as eosinophilic asthma, neutrophilic asthma, mixed granulocytic asthma, and paucigranulocytic asthma etc.) a patient has, in order to prioritize relevant content provided to the patient, in the interests of customizing the program. For instance, if the pre-assessment operation 226 identifies that the patient is predominantly subtype eosinophilic asthma, subsequent portions of the method 200B can prioritize content associated more highly with eosinophilic asthma.
  • a respiratory disorder e.g., inflammation-based subtypes of asthma such as eosinophilic asthma, neutrophilic asthma, mixed granulocytic asthma, and paucigranulocytic asthma etc.
  • Subtype identification can, however, be assessed outside of the pre-assessment of operation 226.
  • digital therapeutics (DTx) provided by the method 200B and system 100AA can be provided as monotherapies, or as complementary therapies.
  • complementary therapies for respiratory health conditions can include one or more therapies, such as, but not limited to: LABAs, LAMAs, short-acting bronchodilators, non- steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, inhibitors in the JAKs-STATs signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, opioids, nasal anti
  • therapies such as, but not
  • Complementary therapies can further include one or more of: psychological treatments, hypnotherapy, acupuncture, herbal therapies, oils, and other therapies.
  • operation 226 of method 200B includes a method of determining severity of an associated gastrointestinal (GI) (e.g., common co-morbidity) and/or respiratory condition.
  • GI associated gastrointestinal
  • FIG. 5A depicts a flowchart of a process for determining severity of a an associated gastrointestinal and/or respiratory condition, according to one or more embodiments.
  • FIG. 5B depicts examples of a process for determining severity of a respiratory condition, according to one or more embodiments.
  • the process 500 can include operation 501 for calculating levels of a respiratory health condition-associated marker (e.g., from a sample from the user, such as a blood sample, breath sample, or a saliva sample, from interactions with the system, etc.) to identify the user (e.g. the patient), as having a certain state of severity (e.g., expression, phenotype, etc.) of the respiratory health condition.
  • a respiratory health condition-associated marker e.g., from a sample from the user, such as a blood sample, breath sample, or a saliva sample, from interactions with the system, etc.
  • a certain state of severity e.g., expression, phenotype, etc.
  • 5 A can be implemented through a DTx system executing on a mobile device or other device associated with the user, where a user interface of the DTx system prompts inputs from the user pertaining to various symptoms (e.g., respiratory symptom, symptom severity, energy levels, digestive issues, cognitive symptoms, behavioral effects, etc.) and generates a report indicating severity of the respiratory health condition as shown in FIG. 5B.
  • various symptoms e.g., respiratory symptom, symptom severity, energy levels, digestive issues, cognitive symptoms, behavioral effects, etc.
  • the process 500 shown in FIG. 5A can then include operation 502, administering a treatment (e.g., monotherapy, complementary therapy) to the user having the state of severity, where the treatment comprises one or more of the therapies described.
  • a treatment e.g., monotherapy, complementary therapy
  • the process 200B can include adjusting (e.g., decreasing, increasing, maintaining) an amount of a non-behavioral therapy treatment provided to the user based upon the state of severity, and/or correspondingly adjusting (e.g., decreasing, increasing, maintaining) an amount of a behavioral therapy treatment provided to the user, thereby titrating relative treatment types provided to the user based upon returned outputs of models associated with the methods described.
  • a treatment cocktail can include prescription digital therapeutic aspects and non-prescription digital therapeutic aspects.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify mental health statuses of the patient, in relation to comorbid or non-comorbid conditions (e.g., associated with anxiety, associated with depression, associated with social behavior, etc.), where the intervention regimen described in more detail above can be configured to improve mental health states of the patient in a timely and adaptive manner.
  • the DTx systems and methods described herein may be used to treat, ameliorate, prevent, or reduce the likelihood of developing one or more comorbidities associated with a respiratory disorder in a patient.
  • the one or more comorbidities associated with the chronic disorder and treated using the DTx systems and methods described herein include, but not limited to a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, fatigue, a cardiovascular disorder, a dermatological disorder, eczema, atopic dermatitis, a sleep disorder, a gastrointestinal disorder, irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), GERD, a respiratory disorder, COPD, asthma, eosinophilic bronchitis, and/or any other suitable comorbidities.
  • a generalized anxiety disorder a social anxiety disorder, a depressive disorder, fatigue, a cardiovascular disorder, a dermatological disorder, eczema, atopic dermatitis, a sleep disorder, a gastrointestinal disorder, irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), GERD, a respiratory disorder, COPD, asthma, eosinophilic bronchitis,
  • related data can include psychological and/or disease symptom/clinical profile data that informs selection of high priority therapy components, where examples include data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia characteristics of the patient, promoting behavioral activation content by the system and response chaining, where response chaining involves linking of effortful avoided tasks to those that are neutral or slightly rewarding); sources of motivation; reward sensitivity (e.g., sensitivity associated with drive and reward responsiveness (e.g., using a BIS/BAS assessment tool); and threat sensitivity.
  • data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia
  • the method 200B can include receiving a reward sensitivity dataset characterizing motivation and reinforcement behavior of the user, and modulating aspects of the treatment upon processing the reward sensitivity dataset with one or more models described.
  • Mental health, reward tendencies and sensitivity, and motivational aspect identification can, however, be assessed outside of the preassessment of operation 226.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify user preferences associated with scheduling of content delivery (e.g., in relation to frequencies of content delivery described above) associated with one or more aspects of the intervention regimen, preferred formats (e.g., visual formats, audio formats, haptic formats, etc.) of content delivery, frequency of content delivery, location of user when content is delivered, specific device(s) to which content is delivered, and/or any other suitable user preferences.
  • preferred formats e.g., visual formats, audio formats, haptic formats, etc.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify user goals for improving health, in relation to the intervention regimen.
  • goals can include one or more goals, such as, but not limited to: reduction of anxiety, reduction of negative emotions, reduction of depression symptoms, improvement of sleep behavior, improvement in socialization, improvement of respiratory health condition symptoms, improvement of medication adherence, improvement in respiratory-related quality of life, improvement of other health condition symptoms, and/or any other suitable goals.
  • Goals can be organized at a high level of abstraction (e.g., improve sleep behavior), and/or at lower levels of abstraction (e.g., improve quality of sleep, reduce number of symptom-induced disturbances to sleep, etc.).
  • the online system and/or other system components can implement surveying tools (e.g., for self-report of data from the patient) and/or non-survey-based tools for acquisition of data.
  • Survey tools can be delivered through an application associated with the DTx system executing on the client device of the patient and/or through another suitable method, where the survey tools can implement architecture for assessing the patient in relation to mental health, discomfort, respiratory health symptom severity or disease activity, types of respiratory health condition symptoms, and/or other statuses.
  • the surveying tools can be derived from one or more tools such as, but not limited to a cough-specific quality of life questionnaire; health related quality of life (HRQOL) questionnaire; quality of life (QoL) questionnaire; visual analog scale for cough severity; cough severity score (CSS); cough severity diary (CSD); numeric rating scale (NRS); tussigenic challenges; a work and social adjustment scale (WSAS)-derived instrument; a clinical disease activity measurement instrument; a patient health questionnaire; a GAD-7 anxiety disorder questionnaire; and any other tool or instrument.
  • Survey components can be implemented during pre-assessment of a patient and/or within modules of the intervention regimen, as described in more detail above.
  • the system can include architecture for receiving data derived from the patient (e.g., through sensor components, through survey components, associated with respiratory characteristics, digestive characteristics, cognitive characteristics, and other characteristics), processing the data with one or more models, and returning scores (e.g., measures of symptom severity, etc.). Scores can also be used for tagging user data with symptom severity, in relation to model aspects and model training/refinement described below.
  • the online system and/or other system components can implement data from devices (e.g., non-survey data).
  • devices e.g., non-survey data
  • embodiments of the system can perform preassessment with implementation of data from devices including one or more devices, such as, but not limited to: electronic health record-associated devices; sleep monitoring devices; devices; electronic health record-associated devices, torso-coupled devices, wearable devices, implanted devices, location monitoring devices, social networking tracking devices, location monitoring devices, cardiovascular monitoring devices, spirometer, peak flow meter, high-resolution computed tomography (CT) scanners, cough monitors, audio-recognition devices, EMG devices, accelerometers, plethysmographs, electrocardiographs, the LifeShirt, VitaloJAK, Leicester Cough Monitor (LCM), LR102, hull automatic cough counter, cough counter mobile applications, pulmonary function measuring tools, pulse-oxygen devices, and combinations thereof, and other devices, such as, but not limited to: electronic health record-associated
  • Non-survey-derived data can additionally or alternatively include data derived from API access of social networking platforms, other communication platforms (e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users), location-determining platforms, and/or other platforms, in order to assess social behaviors of the user.
  • FIG. 6 depicts a flowchart of a pre-assessment and onboarding process of a method for providing adaptive interventions, according to one or more embodiments.
  • the pre-assessment and onboarding process 600 can include operation 611, which facilitates downloading of an application associated with the system and/or using of a non-downloadable version of the system (e.g., via web application, etc.) for delivering the intervention regimen by a client device of the patient; operation 612, which renders a welcome/introduction screen within the application associated with the system; operation 613, which delivers content within the application for educating the patient regarding the purpose of the system and provides an overview of the intervention regimen; operation 614, which creates a patient profile within the online system, resulting in a first tier of personalization by implementing survey and non-survey based tools (e.g., to assess gender, age, preferences for scheduling of content delivery, specific respiratory health condition symptoms of the patient, etc.); and operation 615, which, within the application associated with the system, assesses goals of the patient, resulting in a second tier of personalization.
  • operation 611 which facilitates downloading of an application associated with the system and/or using of a non
  • the second tier of personalization can operate by assessing goals related to anxiety reduction, depression reduction, reduction of respiratory disease or syndrome symptoms, improvement of sleep, improvement of socialization, and other goals.
  • FIG. 6 further depicts operation 616, which, in one embodiment, processes the data from operations 614 and 615 with an intervention-determining model to output a personalized intervention regimen with adaptive behavioral therapy tools and exercises for improving health and wellbeing of the patient, in relation to his/her specific goals.
  • FIG. 6 also depicts operation 617 where a first module of the intervention regimen is delivered to the patient within the application associated with the system, and operation 618, which provides further adaptation of modules of the intervention regimen as the patient progresses through the intervention regimen and interacts with content.
  • FIG. 6 depicts examples of behavioral therapy modules of a program for personalized respiratory condition monitoring and improvement, according to one or more embodiments.
  • process flow proceeds to operation 228.
  • an intervention regimen for the patient is generated upon processing data from the pre-assessment with an intervention-determining model.
  • one embodiment of the online system in coordination with the network and a client device, can process data from the pre-assessment with an intervention-determining model.
  • Operation 228 functions to generate an intervention regimen for the patient upon processing pre-assessment data, in order to design a customized intervention regimen to address specific symptoms and needs of the patient. While operation 228 is described in relation to pre-assessment data, model architecture and associated algorithms can additionally or alternatively be applied to assessment of patient data as the patient interacts with content of the intervention regimen, in order to adaptively modify delivery of intervention regimen components to the patient, with processing of incoming data.
  • the intervention-determining model contemporaneously processes data associated with patient goals, user respiratory health condition symptoms, patient mental health states, other characteristics, and interactions with content of the DTx system, providing the intervention regimen as inputs, in order to output a customized and modulatable intervention regimen to improve the health and/or wellbeing of the patient.
  • the intervention-determining model can include architecture for one or more of: conditional decision making (e.g., with conditional branching structure that processes input data in stages and determines an output at each node of the branching structure); ranking (e.g., with ranking algorithms configured to rank candidate intervention regimen components according to appropriateness, based on the input data); matching (e.g., with performance of best match operations between input data and different groups representing modules of the intervention regimen, with centroid-based approaches, etc.); correlation (e.g., correlation functions that process input data to generate outputs associated with different intervention regimen components); and/or any other suitable architecture. Training of models is further described below.
  • conditional decision making e.g., with conditional branching structure that processes input data in stages and determines an output at each node of the branching structure
  • ranking e.g., with ranking algorithms configured to rank candidate intervention regimen components according to appropriateness, based on the input data
  • matching e.g., with performance of best match operations between input data and different groups representing modules of the intervention regimen, with cent
  • method flow proceeds to operation 230.
  • the online system in coordination with other system components (e.g., the client device, external systems, network, etc.) delivers the intervention regimen to the patient, for instance, through an application associated with the DTx system executing at the client device of the patient.
  • content associated with the intervention regimen can be of visual (e.g., image format, video format), textual, audio, haptic, and/or other formats, through connected devices (e.g., mobile computing devices, wearable devices, audio output devices, displays, temperature control devices, lighting control devices, etc.) and generated in a manner that promotes user engagement.
  • connected devices e.g., mobile computing devices, wearable devices, audio output devices, displays, temperature control devices, lighting control devices, etc.
  • the system in providing the interventions (e.g., such as interventions described in more detail below), can coordinate with and/or provide instructions for control of other devices, for intervention delivery.
  • the system can coordinate with environmental control devices (e.g., connected audio output devices, connected temperature control devices, connected lighting control devices, connected pill dispensing devices, connected smart pill devices, etc.) to change aspects of the patient’s environment in association with provision of the intervention regimen.
  • environmental control devices e.g., connected audio output devices, connected temperature control devices, connected lighting control devices, connected pill dispensing devices, connected smart pill devices, etc.
  • the intervention regimen can provide a grounding exercise to reduce anxiety regarding respiratory health condition symptoms, where the user is prompted to observe aspects of the environment with multiple senses, and the system can coordinate with environmental control devices to adjust one or more of lighting (e.g., colors, intensity, etc.), sounds (e.g., through audio output devices), and/or temperature in the patient’s environment.
  • the intervention regimen can provide a relaxation exercise to reduce anxiety and discomfort associated with respiratory health condition symptoms, and coordinate with an audio output device to play music pleasing to the patient.
  • the intervention regimen can provide an exercise activity involving movements or dancing, to reduce bloating and depression associated with respiratory health condition symptoms, and coordinate with an audio output device to play dance music to the user, while reducing environmental temperature with a smart thermostat device.
  • the system can provide coordinated interventions, however, in any other suitable manner, where details of interventions are provided in more detail above.
  • DTx for use in the improvement of non-digital therapeutic interventions for respiratory disorders.
  • a method of enhancing the performance of a therapeutic intervention administered to a patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a respiratory disorder and/or one or more side effects associated with the therapeutic intervention comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the therapeutic intervention for the respiratory disorder includes treatments utilizing one or more pharmaceutical compositions.
  • the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of headache, nausea, upset stomach, itching, diarrhea, cramps, insomnia, mood changes, nervousness, restlessness, difficulty sleeping, vomiting, abdominal pain, gas, tiredness, wheezing, muscle tightening, heart palpitations, stomach pain, joint pain, back pain, cough, fast heartbeat, tiredness, constipation, stomach cramps, agitation, irregular heartbeat, rapid breathing, heartburn, drowsiness, fatigue, skin rash, depression, tinnitus, dizziness, and combinations thereof.
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators, non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, JAKs -STATs signaling pathway inhibitors, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, antacids, promotility drugs, PPIs,
  • enhancing performance of the therapeutic intervention comprises adjusting dosage of the one or more pharmaceutical compositions.
  • adjusting the dosage of the one or more pharmaceutical composition comprises increasing the dosage to increase effectiveness of the therapeutic intervention without increasing the associated side effects.
  • adjusting dosage of the one or more pharmaceutical composition comprises increasing the dosage of the one or more pharmaceutical compositions without increasing the associated side effects to a higher amount that is therapeutically effective in a patient who is not responsive to lower amounts of the one or more pharmaceutical compositions.
  • adjusting dosage of the one or more pharmaceutical composition comprises reducing the dosage of the one or more pharmaceutical compounds responsive to treatment or amelioration of one or more symptoms of the respiratory disorder using the digital therapeutics; and wherein the reduced dosage is therapeutically effective.
  • enhancing performance of the therapeutic intervention comprises reducing, ameliorating, or preventing the one or more side effects associated with the therapeutic intervention.
  • enhancing performance of the therapeutic intervention comprises increasing bioavailability of the one or more pharmaceutical compositions by reducing, ameliorating, or preventing one or more of side effects associated with the therapeutic intervention and/or by reducing, ameliorating, or preventing one or more symptoms associated with the respiratory disorder.
  • the respiratory disorder is selected from the group consisting of COPD, asthma, ACOS, medication-induced chronic cough, chronic cough, and combinations thereof.
  • the chronic cough is associated with one or more other health conditions each independently selected from the group consisting of respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, GERD, and combinations thereof.
  • the medication-induced chronic cough is associated with one or more medications, the one or more medications each independently selected from the group consisting of angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing a respiratory disorder in a patient comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the patient is undergoing or has undergone a therapeutic intervention for said condition.
  • the therapeutic intervention comprises one or more non-digital treatments selected from the group consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mind-body interventions; treatments utilizing whole system medicine; treatments utilizing one or more surgeries; and combinations thereof.
  • the therapeutic intervention comprising one or more non-digital treatments is provided prior to, contemporaneously with, and/or after administering the digital therapeutic to the patient.
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of long-acting bronchodilators (132- agonists (LABAs), long-acting muscarinic antagonists (LAMAs), short-acting bronchodilators, non- steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)- signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics
  • LAMAs long-acting muscarinic antagonists
  • STATs janus-kin
  • the one or more nutraceutical compositions each comprise at least one nutraceutical component independently selected from the group consisting of microorganisms, proteins, vitamins, herbs, and combinations thereof.
  • the one or more medical devices are each independently selected from the group consisting of metered dose inhalers (MDI), dry powder inhalers (DPI), soft mist inhalers (SMI), breath actuated inhalers, and nebulizers, zephyr endobronchial valve, inhalers, oxygen therapy devices, continuous positive airway pressure (CPAP) devices, bilevel positive airway pressure (BiPAP) devices, cough assist devices, high frequency chest wall oscillation devices, wearable devices, implanted devices, biofeedback devices, and combinations thereof.
  • MDI metered dose inhalers
  • DPI dry powder inhalers
  • SMI soft mist inhalers
  • breath actuated inhalers zephyr endobronchial valve
  • inhalers oxygen therapy devices
  • CPAP continuous positive airway pressure
  • BiPAP bilevel positive airway pressure
  • cough assist devices high frequency chest wall oscillation devices
  • wearable devices implanted devices
  • biofeedback devices biofeedback devices
  • the respiratory disorder is selected from the group consisting of chronic obstructive pulmonary disease (COPD), asthma, asthma-COPD overlap syndromes (ACOS), medication-induced chronic cough, chronic cough, and combinations thereof.
  • COPD chronic obstructive pulmonary disease
  • ACOS asthma-COPD overlap syndromes
  • medication-induced chronic cough chronic cough, and combinations thereof.
  • the chronic cough is associated with one or more other health conditions each independently selected from the group consisting of respiratory conditions, non- respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, gastroesophageal reflux (GERD), and combinations thereof.
  • the medication-induced chronic cough is associated with one or more medications, the one or more medications each independently selected from the group consisting of angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • the respiratory disorder is COPD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)-signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • the respiratory disorder is asthma
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids, LABAs, LAMAs, short-acting bronchodilators, leukotriene receptor antagonists, systemic corticosteroids, eosinophilia-targeted biological therapies, combination therapies, xanthines, and combinations thereof.
  • the respiratory disorder is chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids; anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, and combinations thereof.
  • the respiratory disorder is ACOS
  • the one or more pharmaceutical compositions each comprise at least one compound selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non- steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)- signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • LABAs LAMAs
  • short-acting bronchodilators non- steroid-based anti inflammatories, inhaled corticosteroids,
  • the respiratory disorder is chronic cough associated with GERD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of antacids, promotility drugs, PPIs, and combinations thereof.
  • the respiratory disorder is medication-induced chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of ACE inhibitors, ARBs, proton-pump inhibitors, antiinflammatories, and combinations thereof.
  • the digital therapeutic treatment components include components of therapies selected from the group of therapies consisting of: cognitive behavioral therapy (CBT), mindfulness therapy, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit reversal training, aversion therapy, acceptance and commitment (ACT)-based interventions, psychotherapy, , habit reversal training (HRT), arousal reduction training, rational-emotive therapy, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), relaxation therapy, progressive muscle relaxation (PMR) training, autogenic training (AT), biofeedback therapy, somatic anchoring therapy, hypnotherapy, cognitive defusion, coping techniques, experiential therapy, psychodynamic therapy,
  • CBT cognitive behavioral therapy
  • breathing exercises breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit reversal training, aversion therapy, acceptance and commitment (ACT)-based interventions, psychotherapy,
  • remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components includes obtaining patient data including one or more of: patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient medications data; patient medication adherence data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of: leicester cough questionnaire (LCQ); cough-specific quality of life questionnaire; health related quality of life (HRQOL) questionnaire; quality of life (QoL) questionnaire; visual analog scale for cough severity; cough severity score (CSS); cough severity diary (CSD); numeric rating scale (NRS); tussigenic challenges; a work and social adjustment scale (WSAS)-derived instrument; a clinical disease activity measurement instrument; a patient health questionnaire; a GAD-7 anxiety disorder questionnaire; and combinations thereof.
  • LCQ leicester cough questionnaire
  • HRQOL health related quality of life
  • QoL quality of life
  • CCS cough severity score
  • CSD cough severity diary
  • NFS numeric rating scale
  • tussigenic challenges a work and social adjustment scale (WSAS)-derived instrument
  • WSAS work and social adjustment scale
  • remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components includes utilizing non-survey data obtained from one or more devices selected from the group of devices consisting of electronic health record- associated devices, torso-coupled devices, wearable devices, implanted devices, cardiovascular monitoring devices, sleep monitoring devices, location monitoring devices, social networking tracking devices, spirometer, peak flow meter, high-resolution computed tomography (CT) scanners, cough monitors, audio-recognition devices, electromyography (EMG) devices, accelerometers, plethysmographs, electrocardiographs, the LifeShirt, VitaloJAK, Leicester Cough Monitor (LCM), LR102, hull automatic cough counter, cough counter mobile applications, pulmonary function measuring tools, pulse-oxygen devices, and combinations thereof.
  • CT computed tomography
  • EMG electromyography
  • dynamically modifying one or more of the digital therapeutic treatment components includes one or more of: adjusting the order of administration of the digital therapeutic components; adjusting the order of administration of the non-digital treatment; adjusting the frequency of administration of the digital therapeutic components; adjusting the frequency of administration of the non-digital treatments; adjusting the mode of administration of the digital therapeutic components; adjusting the mode of administration of the non-digital treatments; adjusting the content of the digital therapeutic components; adjusting the content of the non-digital treatments; adjusting the content size of the digital therapeutic components; adjusting the dosage amount of the non-digital treatments; adjusting the dosage schedule of the non-digital treatments; adjusting the presentation of the digital therapeutic components; adjusting the layout of the digital therapeutic components; and increasing personalization of the digital therapeutic components.
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing one or more symptoms associated with a respiratory disorder in a patient comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic comprises: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the one or more symptoms are each independently selected from the group consisting of breathlessness, chronic cough, fatigue, difficulty breathing, chest tightness, coughing, wheezing, dyspnea, dry cough, hacking cough, and combinations thereof.
  • the patient is undergoing or has undergone one or more non-digital therapeutic interventions for said condition.
  • the one or more non-digital therapeutic interventions is provided prior to, contemporaneously with, and/or after administering the digital therapeutic to the patient.
  • the one or more non-digital therapeutic interventions are each independently selected from the group consisting of treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mind-body interventions; treatments utilizing whole system medicine; treatments utilizing one or more surgeries; and combinations thereof.
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators, non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, JAKs-STATs signaling pathways inhibitors, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, antacids, promotility drugs, PPIs, ACE inhibitor
  • the respiratory disorder is selected from the group consisting of COPD, asthma, ACOS, medication-induced chronic cough, chronic cough, and combinations thereof.
  • the chronic cough is associated with one or more other health conditions each independently selected from the group consisting of respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, GERD, and combinations thereof.
  • the medication-induced chronic cough is associated with one or more medications, the one or more medications each independently selected from the group consisting of angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • the respiratory disorder is COPD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)-signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • LABAs LAMAs, short-acting bronchodilators
  • non-steroid-based anti inflammatories inhaled corticosteroids
  • the one or more medications each independently selected from the group consisting of angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • the respiratory disorder is asthma
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids, LABAs, LAMAs, short-acting bronchodilators, leukotriene receptor antagonists, systemic corticosteroids, eosinophilia-targeted biological therapies, combination therapies, xanthines, and combinations thereof.
  • the respiratory disorder is ACOS
  • the one or more pharmaceutical compositions each comprise at least one compound selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled
  • Ill corticosteroids Ill corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)- signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • JKs janus-kinases
  • STATs janus-kinases
  • the respiratory disorder is chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids; anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, and combinations thereof.
  • the respiratory disorder is chronic cough associated with GERD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of antacids, promotility drugs, PPIs, and combinations thereof.
  • the respiratory disorder is medication-induced chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of ACE inhibitors, ARBs, proton-pump inhibitors, anti-inflammatories, and combinations thereof.
  • the respiratory disorder is COPD
  • the one or more symptoms are each independently selected from the group consisting of breathlessness, chronic cough, fatigue, and combinations thereof.
  • the respiratory disorder is asthma
  • the one or more symptoms are each independently selected from the group consisting of difficulty breathing, chest tightness, coughing, wheezing, dyspnea, and combination thereof.
  • the respiratory disorder is ACOS
  • the one or more symptoms are each independently selected from the group consisting of breathlessness, chronic cough, fatigue, difficulty breathing, chest tightness, coughing, wheezing, dyspnea, and combinations thereof.
  • the respiratory disorder is medication-induced chronic cough
  • the one or more symptoms are each independently selected from the group consisting of dry cough, hacking cough, and combination thereof.
  • the respiratory disorder is chronic cough
  • the one or more symptoms are each independently selected from the group consisting of cough associated with one or more other health conditions, vomiting, dyspnea and combinations thereof
  • the one or more other health conditions are each independently selected from the group consisting of respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, GERD, and combinations thereof.
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing one or more side effects associated with a therapeutic intervention for a respiratory disorder in a patient who is undergoing said therapeutic intervention comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the therapeutic intervention for the respiratory disorder includes treatments utilizing one or more pharmaceutical compositions.
  • the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of headache, nausea, upset stomach, itching, diarrhea, cramps, insomnia, mood changes, nervousness, restlessness, difficulty sleeping, vomiting, abdominal pain, gas, tiredness, wheezing, muscle tightening, heart palpitations, stomach pain, joint pain, back pain, cough, fast heartbeat, tiredness, constipation, stomach cramps, agitation, irregular heartbeat, rapid breathing, heartburn, drowsiness, fatigue, skin rash, depression, tinnitus, dizziness, and combinations thereof.
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators, non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, JAKs -STATs signaling pathways inhibitors, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, antacids, promotility drugs, PPIs,
  • the respiratory disorder is selected from the group consisting of COPD, asthma, ACOS, medication-induced chronic cough, chronic cough, and combinations thereof.
  • the chronic cough is idiopathic chronic cough or associated with one or more other health conditions each independently selected from the group consisting of respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, GERD, and combinations thereof.
  • the medication-induced chronic cough is associated with one or more medications, the one or more medications each independently selected from the group consisting of angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • the respiratory disorder is COPD; wherein the therapeutic intervention for the COPD comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)-signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof, and combinations thereof; and wherein
  • the respiratory disorder is asthma; wherein the therapeutic intervention for the asthma comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of inhaled corticosteroids, LABAs, LAMAs, short-acting bronchodilators, leukotriene receptor antagonists, systemic corticosteroids, eosinophilia-targeted biological therapies, combination therapies, xanthines, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions for the asthma are each independently selected from the group consisting of: mood changes, stomach upset, nervousness, restlessness, difficulty sleeping, nausea, cough, agitation, depression, stomach pain, joint pain, back pain, cough, fast heartbeat, tiredness, headache, itching, irregular heartbeat, rapid breathing, abdominal pain, vomiting, mood changes, rapid breathing, , diarrhea, nervousness, and combinations thereof.
  • the therapeutic intervention for the asthma comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of inhaled cor
  • the respiratory disorder is ACOS
  • the therapeutic intervention for the ACOS comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)- signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof; and wherein the one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of LABAs, LAMAs,
  • the respiratory disorder is chronic cough
  • the therapeutic intervention for the chronic cough comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of inhaled corticosteroids; anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions for the chronic cough are each independently selected from the group consisting of mood changes, stomach upset, nervousness, restlessness, difficulty sleeping, tiredness, headache, nausea, vomiting, constipation, difficulty sleeping, itching, diarrhea, stomach cramps, heartburn, constipation, diarrhea, vomiting, headache, drowsiness, constipation, fatigue, headache, stomach pain, skin rash, and combinations thereof.
  • the respiratory disorder is chronic cough associated with GERD
  • the therapeutic intervention for the chronic cough associated with GERD comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of antacids, promotility drugs, PPIs, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions for the chronic cough associated with GERD are each independently selected from the group consisting of diarrhea, constipation, stomach cramps, nausea, vomiting, abdominal pain, gas, indigestion, body aches, insomnia, anxiety, headaches, fatigue, depression, tinnitus, rash, dizziness, and combinations thereof.
  • the respiratory disorder is medication-induced chronic cough
  • the therapeutic intervention for medication-induced chronic cough comprises one or more pharmaceutical compositions, each comprising at least one compound independently selected from the group consisting of ACE inhibitors, ARBs, proton-pump inhibitors, anti-inflammatories, and combinations thereof; and wherein the one or more side effects associated with the one or more pharmaceutical compositions for the medication-induced chronic cough includes cough.
  • DTx for use in improvement of adherence to non-digital therapeutic interventions for respiratory disorders
  • a method of improving patient adherence to a treatment regimen of a therapeutic intervention administered to said patient for the treatment, prevention, amelioration, or reduction in the likelihood of developing a respiratory disorder and/or one or more side effects associated with said therapeutic intervention comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic includes: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’ s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the therapeutic intervention for the respiratory disorder includes treatments utilizing one or more pharmaceutical compositions.
  • the respiratory disorder is selected from the group consisting of COPD, asthma, ACOS, medication- induced chronic cough, chronic cough, and combinations thereof.
  • the chronic cough is an idiopathic chronic cough condition, or associated with one or more other health conditions each independently selected from the group consisting of respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, GERD, and combinations thereof.
  • the medication-induced chronic cough is associated with one or more medications, the one or more medications each independently selected from the group consisting of angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • the one or more side effects associated with the one or more pharmaceutical compositions are each independently selected from the group consisting of headache, nausea, upset stomach, itching, diarrhea, cramps, insomnia, mood changes, nervousness, restlessness, difficulty sleeping, vomiting, abdominal pain, gas, tiredness, wheezing, muscle tightening, heart palpitations, stomach pain, joint pain, back pain, cough, fast heartbeat, tiredness, constipation, stomach cramps, agitation, irregular heartbeat, rapid breathing, heartburn, drowsiness, fatigue, skin rash, depression, tinnitus, dizziness, and combinations thereof.
  • the one or more pharmaceutical compositions each include at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators, non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, JAKs -STATs signaling pathways inhibitors, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, antacids, promotility drugs, PPIs, ACE
  • improving patient adherence to the therapeutic intervention comprises receiving, via one or more of the digital therapeutic treatment components, patient adherence data; identifying patterns related to said patient’s treatment regimen based on symptom changes associated adherence to the treatment regimen and/or symptoms and/or activities that are associated with degree to which said patient adheres to the treatment regimen; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on the patient adherence data and the identified patterns; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the method further comprises: performing, by the therapeutics system, a pre-assessment of the patient; generating, by the therapeutics system, patient profile and preassessment data based on the results of the patient pre-assessment; processing, by the therapeutics system, the patient profile and pre-assessment data to generate patient condition data; processing, by the therapeutics system, the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components; administering one or more of the first therapeutic treatment components to the patient through the user interface of the therapeutics system according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components to generate patient
  • DTx for use in the treatment of comorbidities associated with respiratory disorders
  • a method of treating, preventing, ameliorating, or reducing the likelihood of developing one or more comorbidities associated with a respiratory disorder in a patient comprising: remotely administering a digital therapeutic to said patient, wherein administering said digital therapeutic comprises: providing said patient with a digital therapeutic user interface; administering one or more digital therapeutic treatment components to said patient through the digital therapeutic user interface; remotely monitoring said patient’s interactions with one or more of the digital therapeutic treatment components; dynamically modifying one or more of the digital therapeutic treatment components based at least partly on said patient’s interactions with the digital therapeutic treatment components; and administering one or more of the modified digital therapeutic treatment components to said patient through the user interface of the digital therapeutic.
  • the one or more comorbidities are each independently selected from the group consisting of a generalized anxiety disorder, a social anxiety disorder, a depressive disorder, a cardiovascular disorder, a dermatological disorder, eczema, atopic dermatitis, a sleep disorder, a gastrointestinal disorder, irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), GERD, a respiratory disorder, COPD, asthma, eosinophilic bronchitis, and combinations thereof.
  • a generalized anxiety disorder a social anxiety disorder, a depressive disorder, a cardiovascular disorder, a dermatological disorder, eczema, atopic dermatitis, a sleep disorder, a gastrointestinal disorder, irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), GERD, a respiratory disorder, COPD, asthma, eosinophilic bronchitis, and combinations thereof.
  • the patient is undergoing or has undergone one or more non-digital therapeutic interventions for the respiratory condition.
  • the one or more non-digital therapeutic interventions is provided prior to, contemporaneously with, and/or after administering the digital therapeutic to the patient.
  • the one or more non-digital therapeutic interventions are each independently selected from the group consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mind-body interventions; treatments utilizing whole system medicine; treatments utilizing one or more surgeries; and combinations thereof.
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators, non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, JAKs-STATs signaling pathways inhibitors, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, antacids, promotility drugs, PPIs, ACE inhibitor
  • the respiratory disorder is selected from the group consisting of COPD, asthma, ACOS, medication-induced chronic cough, chronic cough, and combinations thereof.
  • the chronic cough is an idiopathic chronic cough condition, or associated with one or more other health conditions each independently selected from the group consisting of respiratory conditions, non-respiratory conditions, asthma, COPD, chronic bronchitis, obesity, lung cancer, heart failure, eosinophilic bronchitis, pneumonia, GERD, and combinations thereof.
  • the medication-induced chronic cough is associated with one or more medications, the one or more medications each independently selected from the group consisting of angiotensin drugs, proton pump inhibitors, and anti-inflammatories, and combination thereof.
  • the respiratory disorder is COPD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non-steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)-signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 -kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • the respiratory disorder is asthma
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids, LABAs, LAMAs, short-acting bronchodilators, leukotriene receptor antagonists, systemic corticosteroids, eosinophilia-targeted biological therapies, combination therapies, xanthines, and combinations thereof.
  • the respiratory disorder is ACOS
  • the one or more pharmaceutical compositions each comprise at least one compound selected from the group consisting of LABAs, LAMAs, short-acting bronchodilators; non- steroid-based anti inflammatories, inhaled corticosteroids, combination therapies, antibiotics, leukotriene receptor antagonists, xanthines, systemic corticosteroids, mucoactive drugs, eosinophilia-targeted biological therapies, recombinant al -antitrypsin and neutrophil elastase inhibitors, janus-kinases (JAKs)-signal transducers and activators of transcription (STATs) signaling pathways, phosphoinositide-3 - kinase inhibitors, anticonvulsants, antispasmodics, prokinetics, and combinations thereof.
  • LABAs LAMAs
  • short-acting bronchodilators non- steroid-based anti inflammatories, inhaled corticosteroids
  • the respiratory disorder is chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of inhaled corticosteroids; anticonvulsants, antispasmodics, prokinetics, opioids, nasal anticholinergics, tricyclic antidepressants, cough suppressants, antihistamines, and combinations thereof.
  • the respiratory disorder is chronic cough associated with GERD
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of antacids, promotility drugs, PPIs, and combinations thereof.
  • the respiratory disorder is medication-induced chronic cough
  • the one or more pharmaceutical compositions each comprise at least one compound independently selected from the group consisting of ACE inhibitors, ARBs, proton-pump inhibitors, antiinflammatories, and combinations thereof.
  • the respiratory disorder is COPD
  • the one or more comorbidities are each independently selected from the group consisting of cardiovascular disease, eczema, sleep disorders, anxiety, depression, IBS, IBD, and combinations thereof.
  • a seventeenth example of the method which optionally includes one or more of the first through sixteenth examples, wherein the respiratory disorder is asthma, and the one or more comorbidities are each independently selected from the group consisting of GERD, anxiety, depression, atopic dermatitis, and combinations thereof.
  • the respiratory disorder is chronic cough
  • the one or more comorbidities are each independently selected from the group consisting of COPD, asthma, depression, eosinophilic bronchitis, gastroesophageal reflux, GERD, and combinations thereof.
  • Tables 2 - 6 below show side effects caused by medications used in the treatment of various respiratory disorders, and respiratory disorder symptoms and side effects that may be treated with the digital therapeutics systems described herein.
  • Table 2 COPD - Medications/Symptoms treated/Side-effects
  • Table 3 Asthma - Medications/Symptoms treated/Side-effects
  • the conditional branching model shown in FIG. 8 A selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to respiratory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the behavioral therapy techniques implemented in the selected intervention can address problem- focused coping tools and/or emotion-focused coping tools, with additional tailoring for different mental health issues associated with the respiratory or co-morbid condition symptoms of the patient.
  • conditional branching model outputs behavioral activation exercises, cognitive reframing techniques, talent practicing and reinforcement exercises, and/or other exercises to mitigate depression symptoms.
  • conditional branching model outputs exposure-based exercises associated with anxiety sources, anxiety tolerance skill-building exercises, grounding exercises, and/or other exercises to mitigate anxiety symptoms.
  • the conditional branching model outputs problemsolving exercises with respect to controllable vs. uncontrollable stressors, and other exercises to mitigate problem-solving issues.
  • the conditional branching model further receives inputs (e.g., rankings of symptom severity) related to symptoms that the patient wishes to improve (e.g., related to cough management, related to sleep, related to adherence, related to communication, related to social problem solving, related to relapse prevention, etc.), and then based upon the inputs, guides the user through additional cognitive skills tailored to improve symptoms in the manner that the patient desires.
  • inputs e.g., rankings of symptom severity
  • related to symptoms that the patient wishes to improve e.g., related to cough management, related to sleep, related to adherence, related to communication, related to social problem solving, related to relapse prevention, etc.
  • FIG. 8B depicts architecture of the conditional branching model for an anxiety-specific pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the DTx system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to respiratory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8B further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her respiratory health condition.
  • inputs e.g., rankings of symptom severity
  • other symptoms e.g., fatigue, sleep hygiene, worry, etc.
  • FIG. 8C depicts architecture of the conditional branching model for a depression-specific pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the DTx system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to respiratory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8C outputs behavioral activation exercises, cognitive reframing techniques, and reinforcement exercises, and/or other exercises to mitigate depression symptoms.
  • the conditional branching model of FIG. 8C further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problemsolving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her respiratory health condition.
  • FIG. 8D depicts architecture of the conditional branching model for a pathway targeted to anxiety and depression (e.g., with a GAD-7 score greater than or equal to 11) where, the model guides (e.g., through an application associated with the DTx system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to respiratory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8D outputs exposure-based desensitization exercises associated with anxiety sources, anxiety tolerance skillbuilding exercises, grounding exercises, and/or other exercises to mitigate anxiety symptoms.
  • the model also determines if the patient is suffering from respiratory symptoms, and provides the patient with breathing management exercises.
  • the model also then sequentially determines if the user is exhibiting symptoms of depression (e.g., if PHQ-9 score is greater than or less than 10), and addresses depression symptoms sequentially relative to other symptoms (e.g., sleep, communication, medication adherence) based upon symptom severity.
  • FIG. 8E depicts architecture of the conditional branching model for a pathway that is not specific to anxiety or depression where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the DTx system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to respiratory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8E outputs problem-solving exercises with respect to controllable vs. uncontrollable stressors, and other exercises to mitigate problem-solving issues.
  • the conditional branching model of FIG. 8E further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her respiratory health condition.
  • method flow proceeds to operation 232.
  • operation 232 a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient are monitored contemporaneously with delivery of the intervention regimen.
  • an embodiment of the online system in coordination with the network and a client device, can monitor a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient contemporaneously with delivery of the intervention regimen.
  • Monitoring interactions functions to provide intimate understanding of progress of the patient in achieving health goals, and to provide further personalization of and delivery of intervention content at appropriate times, in order to maintain or improve progress of the patient.
  • Monitoring is preferably performed in near- real time or real time, such that actions can be taken to adjust interventions to user states according to just-in time adaptive intervention (JITAI) protocols.
  • JITAI just-in time adaptive intervention
  • monitoring can be performed with any suitable delay (e.g., in relation to achieving better accuracy of assessed states of the patient).
  • Monitoring can be performed using survey components delivered with interactive interventions of the intervention regimen, where the user is prompted and provided with interactive elements that allow the patient to provide self-report data indicating progress statuses. Monitoring can additionally or alternatively be performed with processing of other data streams, where the data streams are associated with system or device usage metrics, social networking behavior extracted from usage of social networking platforms and communication platforms, sensor-derived data, and/or other data. Monitoring can thus occur with any frequency and/or level of intrusiveness.
  • operation 232 can process monitoring data (e.g., real time data, non- real time data, dynamic data, static data) with a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • monitoring data e.g., real time data, non- real time data, dynamic data, static data
  • a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • ecological momentary assessments of the patient can be used for monitoring.
  • client device usage parameters can be used for monitoring. Examples of client device usage parameters can include frequency of application switching, duration of time spent in association with each application login, screen time parameters, data usage associated with different applications and/or types of applications (e.g., social networking, creative, utility, travel, activity-related, etc.) executing on the client device of the patient, time of day of application usage, location of device usage, and other client device usage parameters.
  • the system can process voice data and/or text communication data of the patient for monitoring and modifying interventions and program aspects.
  • voice data can include voice sampling data from which emotional states can be extracted using voice processing models.
  • natural language processing of textual data e.g., from communication platforms, from social networking platforms
  • the client device can be used to provide context for behaviors of the patient and/or assess emotional or cognitive states of the patient.
  • electronic health record data can be used for monitoring.
  • the online system can be configured to receive a notification providing information regarding the type of care the patient has received, and to use this data for monitoring statuses of the patient.
  • the system can include architecture for processing data from other sensors of the client device, devices in the environment of the patient, and/or wearable computing devices can be used for monitoring.
  • device data can include activity data, location data, motion data, biometric data, and/or other data configured to provide context to behaviors associated with the health condition of the patient.
  • motion data from motion of sensors of the client device can indicate that the user is sedentary, and may be experiencing symptoms that can be addressed with components of the intervention regimen.
  • device usage data can indicate that the patient has been using a particular device (e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient), in a fixed location (e.g., from GPS data), and in a prone position (e.g., from motion chip data), and may be experiencing respiratory health condition symptoms that can be addressed with components of the intervention regimen.
  • a particular device e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient
  • a fixed location e.g., from GPS data
  • a prone position e.g., from motion chip data
  • active monitoring of patient states can be used to adjust delivery of intervention regimen modules in order appropriately meet the needs of the patient.
  • Other data and combinations of data can, however, be used for monitoring.
  • process flow proceeds to operation 234.
  • operation 234 in response to at least one of the set of interactions and the health status progression, an action configured to improve wellbeing of the patient with respect to the respiratory health condition is performed.
  • an embodiment of the online system in coordination with the network and a client device can, in response to at least one of the set of interactions and the health status progression, perform an action configured to improve health and wellbeing of the patient with respect to the respiratory health condition.
  • Operation 234 functions to provide further customization of the intervention regimen, in order to improve personalization of delivered content to needs of the patient, in an adaptive manner.
  • Operation 234 can also function to increase engagement between the patient and the intervention regimen, in order to improve effectiveness of provided treatments and increase success of the patient in achieving his/her goals.
  • the action performed according to operation 234 can include one or more of: adjusting order of and/or content of intervention modules provided, where intervention types and content are described above; updating electronic health records (EHRs), personal health records (PHRs), and/or open medical records, for instance by writing to or modifying records whenever new information is generated regarding the user/patient/patient; providing and/or facilitating provision of supplemental interventions (e.g., hypnotherapy, physical exercises, medications, supplements, etc.) beyond standard content of the intervention regimen, for instance, under physician-guidance or treatment recommendations; generating and/or providing notifications to the patient regarding changes in behavior or health statuses; generating and/or providing notifications to entities (e.g., relatives, acquaintances having permission of the patient, health care providers, etc.) associated with the patient regarding changes in behavior or health statuses; and/or any other suitable action.
  • EHRs electronic health records
  • PHRs personal health records
  • open medical records for instance by writing to or modifying records whenever new information is generated regarding the user/patient/patient
  • operation 234 can additionally or alternatively include functionality for increasing engagement of the patient with respect to interactions with content of the intervention regimen.
  • features for increasing engagement and optimal learning can include text-based functionality for self-monitoring and symptom tracking, where the system can process real time text interactions with provision of interactive tasks, which increases likelihood of patient responses.
  • specific descriptions self-reported by the patient can be used in subsequent portions of the intervention regimen to increase personalization of the intervention to drive engagement.
  • features for increasing engagement and optimal learning can include features that mimic therapist/healthcare provider, or social group interactions (e.g., patient testimonials, clinician video content, etc.).
  • features for increasing engagement and optimal learning can include features that link the patient’s specific current problems (e.g., from operation 232) and/or challenges faced by the patient as a trigger to notify the patient to interact with content of the intervention regimen and recommend appropriate skill for improving health states.
  • engagement can be promoted using one or more of: artificial reality tools (e.g., augmented reality platforms, virtual reality platforms) for reducing depression, anxiety, cough, and/or other symptoms; artificial intelligence-based coaching elements for driving interactions with the patient; smart assistants (e.g., AlexaTM, SiriTM, GoogleTM Assistant, etc.) for assisting the patient in relation to task management, gamification elements within intervention regimen-associated applications executing on the client device; gamification elements of other devices (e.g., wearable cough counter devices that issue a daily cough score); smart pill devices and/or medication-dispensing devices that provide insights in an engaging manner in coordination with intervention regimen modules; adjustment of reinforcement schedules (e.g., in relation to reward sensitivity, positive reinforcement, negative reinforcement, etc.) for providing intervention regimen content to the patient; and other elements for increasing engagement.
  • artificial reality tools e.g., augmented reality platforms, virtual reality platforms
  • artificial intelligence-based coaching elements for driving interactions with the patient
  • smart assistants e.g., AlexaTM, SiriTM,
  • features for personalization and promoting engagement can be delivered within modules of the intervention regimen before and/or after monitoring of the patient according to operation 232.
  • method flow proceeds to END operation 236, and the method 200B for providing adaptive interventions for respiratory health conditions is exited to await new instructions
  • FIG. 2C is a flowchart depicting a method 200C for providing adaptive interventions for respiratory health conditions, in accordance with one embodiment.
  • method 200C begins at BEGIN 238, and method flow proceeds to operation 240.
  • operation 240 an interface between a device and a user is established.
  • method flow proceeds to operation 242.
  • operation 242 a set of signals associated with a respiratory or co-morbid condition of the user is received from the interface, wherein the set of signals encodes physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user.
  • a characterization of the respiratory health condition is determined upon processing the set of signals with a model.
  • method flow proceeds to operation 246.
  • content of a treatment comprising a set of components is modulated, wherein the set of components comprises a subset of cognitive behavioral therapy (CBT) components for improving a state of the user.
  • CBT cognitive behavioral therapy
  • method flow proceeds to operation 248.
  • the treatment is administered to the user.
  • method flow proceeds to END operation 250, and the method 200C for providing adaptive interventions for respiratory health conditions is exited to await new instructions
  • the methods 200A, 200B, and/or 200C can further include operations for detecting performance of activities associated with the intervention regimen, by the patient; reinforcing user performance or engagement with the intervention regimen; determining undesired levels of performance or engagement with the intervention regimen; and driving improved engagement with the intervention.
  • the methods 200A, 200B, and/or 200C can include functionality for detecting performance or non-performance of activities (e.g., based on system engagement, based upon sensor-detected measures of activity, etc.).
  • the methods 200A, 200B, and/or 200C can include functionality for reinforcing performance through provision of various rewards (e.g., rests, rewards of monetary value, etc.). If the patient does not perform activities appropriately, the methods 200A, 200B, and/or 200C can include functionality for determining causes of non-performance (e.g., non-engaging content, external factors associated with the patient’s life, etc.) and adjust content delivery, provide modified interventions, and/or adjust reinforcement schedules accordingly.
  • causes of non-performance e.g., non-engaging content, external factors associated with the patient’s life, etc.
  • the methods 200A, 200B, and/or 200C can include functionality for developing and training predictive models for predicting states of the patient during the course of the intervention regimen, in order to improve chances of success in outcomes.
  • the methods 200A, 200B, and/or 200C can thus include functionality for aggregation of training datasets from various data sources described above, and processing training datasets with one or more types of model architecture in order to improve predictions and/or selection of appropriate modules of the intervention regimen for delivery to the patient.
  • Models associated with the methods 200A, 200B, and/or 200C can be defined within architecture of computing systems described above, and include elements for statistical analysis of data and/or machine learning.
  • input to a machine learning module comprises one or more textual words, phrases, or lengthier strings.
  • the input comprises various data elements, such as numerical values corresponding to user responses to a series of questions in a questionnaire (e.g., ranking various symptom severities on a scale).
  • one or more output values of a machine learning module comprise values representing a classification of a particular condition of a user.
  • machine learning modules implementing machine learning techniques are trained, for example using curated and/or manually annotated datasets. Such training may be used to determine various parameters of machine learning algorithms implemented by a machine learning module, such as weights associated with layers in neural networks.
  • machine learning module may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, for example to dynamically update the machine learning module.
  • a trained machine learning module is a classification algorithm with adjustable and/or fixed (e.g., locked) parameters, e.g., a random forest classifier.
  • two or more machine learning modules may be combined and implemented as a single module and/or a single software application.
  • two or more machine learning modules may also be implemented separately, e.g., as separate modules or applications.
  • a machine learning module may be software and/or hardware.
  • a machine learning module may be implemented entirely as software, or certain functions of a ANN module may be carried out via specialized hardware (e.g., via an application specific integrated circuit (ASIC)).
  • ASIC application specific integrated circuit
  • the method can include: generating a combined dataset upon applying a first set of transformations to an aggregate dataset including physiological data, behavioral data, environmental stress data, emotional data, and cognitive data from a set of users exhibiting a form of the respiratory health condition; collecting a treatment dataset comprising treatment outcome labels (e.g., quantitative or qualitative labels describing efficacy of individual treatment components) associated with the subset of behavioral therapy components applied to the set of users; creating a first training dataset comprising the combined dataset and the treatment dataset; and training the model with the first training dataset.
  • treatment outcome labels e.g., quantitative or qualitative labels describing efficacy of individual treatment components
  • the model can be structured and ultimately refined for receiving data objects associated with at least one of physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user, and returning a set of outputs comprising a selection of treatment subcomponents tagged with efficacy indicators.
  • Statistical analyses and/or machine learning algorithm(s) can be characterized by a learning style including any one or more of supervised learning (e.g., using back propagation neural networks), unsupervised learning (e.g., K-means clustering), semi-supervised learning, reinforcement learning (e.g., using a Q-learning algorithm, using temporal difference learning, etc.), and any other suitable learning style.
  • supervised learning e.g., using back propagation neural networks
  • unsupervised learning e.g., K-means clustering
  • semi-supervised learning e.g., reinforcement learning, using a Q-learning algorithm, using temporal difference learning, etc.
  • reinforcement learning e.g., using a Q-learning algorithm, using temporal difference learning, etc.
  • any algorithm(s) can implement any one or more of a regression algorithm, an instance-based method (e.g., k-nearest neighbor, learning vector quantization, self-organizing map, etc.), a regularization method, a decision tree learning method (e.g., classification and regression tree, chi-squared approach, random forest approach, multivariate adaptive approach, gradient boosting machine approach, etc.), a Bayesian method (e.g., naive Bayes, Bayesian belief network, etc.), a kernel method (e.g., a support vector machine, a linear discriminate analysis, etc.), a clustering method (e.g., k-means clustering), an associated rule learning algorithm (e.g., an Apriori algorithm), an artificial neural network model (e.g., a back-propagation method, a Hopfield network method, a learning vector quantization method, etc.), a deep learning algorithm (e.g., a Boltzmann machine, a
  • FIG. 9A, FIG. 9B, FIG. 9C, FIG. 9D, FIG. 9E, FIG. 9F, FIG. 9G, and FIG. 9H are screenshots (901, 902, 903, 904, 905, 906, 907 and 908, respectively) of several portions of an exemplary GUI for a system for treating respiratory health conditions using digital therapeutics, according to one or more embodiments.
  • Screenshot 901 in FIG. 9 A shows a GUI with content summarizing a psychoeducation module just completed and screenshot 902 in FIG. 9B an exemplary scenario for the user to consider before applying a symptom management tool (e.g. unhooking from unhelpful feelings) as shown in FIG. 9C, FIG. 9D, FIG. 9E, FIG. 9F, FIG. 9G and FIG. 9H.
  • a symptom management tool e.g. unhooking from unhelpful feelings
  • FIG. 9 A shows a home screen 901 that provides user access to an initial, first, lesson module.
  • a selectable icon 901 A representing the initial lesson module may be displayed, which a user may select to begin.
  • FIG. 9B shows another screen 902 of a GUI, through which a user may read an example scenario to better understand how to apply a symptom management tool.
  • a user can apply a symptom management tool to a particular situation that exemplifies the lesson being conveyed and track their progress through a sequence of interactive lesson modules.
  • lesson modules are grouped into subsequences referred to as sessions, with each session comprising lessons that are related, e.g., thematically.
  • FIG. 9C, FIG. 9E, FIG. 9F and FIG. 9G allow the user to progressively interact using text box icons (903 A, 905A, 906A, 907A).
  • FIG. 9C, FIG. 9E, FIG. 9F and FIG. 9G allow the user to progressively interact using text box icons (903 A, 905A, 906A, 907A).
  • FIG. 9C, FIG. 9E, FIG. 9F and FIG. 9G allow the user to progressively interact using text box icons (903 A, 905A, 906A, 907A).
  • FIG. 9C, FIG. 9E, FIG. 9F and FIG. 9G allow the user to progressively interact using
  • a screen 908 of a GUI may also comprise a stored profile of the user.
  • a user profile may be populated via various lesson modules that solicit input from the user, for example regarding personal characteristics, thoughts and feelings, symptom logging, identification of stressor situations, stress level tracking, response strategies, lessons learned and completion of diagnostic assessments aimed at characterizing their condition.
  • various patient reported outcome instruments which, for example, measure condition symptom severity, quality of life, etc.
  • a patient/user suffering from respiratory may complete a symptom severity scale evaluation, and/or other evaluations based on other patient reported outcome instruments, described in further detail above.
  • these stored profiles may be retrieved by the user or the DTx system to refresh the lesson module (e.g., randomly or in response to data indicating the user needs reinforcement of the lesson/theme)
  • FIG. 10 A, FIG. 10B, FIG. 10C, and FIG. 10D are screenshots of example user interactions with an initial lesson module for content tailored for a patient with a respiratory condition, according to one or more embodiments.
  • a user may select icon 1002 representing the initial lesson module from their home-screen to begin the initial lesson module.
  • a user may step through content of a lesson module by tapping a selectable graphical button 1004, until they have viewed all screens comprising all graphical content and widgets of the lesson module.
  • a user may be presented with a final screen that provides an indication that they have completed a particular lesson module. The user may select a graphical button 1006 to confirm completion of the particular lesson module. Following completion of an initial lesson module, the user may progress onto a subsequent one.
  • FIG. 11 A and FIG. 1 IB are screenshots showing gate features of an exemplary GUI for a system for treating respiratory conditions using digital therapeutics, in accordance with one or more embodiments.
  • progression onto a next lesson module is not necessarily instantaneous and/or direct. Instead, as described above, gate features may be used to introduce friction and/or to control a rate of progression from one lesson module to a next.
  • FIG. 11 A shows an example soft-gate, wherein a user is not fully prevented from beginning a second lesson module, but is encouraged to delay moving on, and required to provide additional input to do so.
  • Interlesson gate screen 1102 represents a soft-gate, and includes graphical content prompting the user to delay progressing onto the second lesson until the next day.
  • Example screen 1104 also includes delay button 1104a and continue button 1104b graphical widgets, wherein selection of the delay button 1104a graphical widget returns the user to the home-screen.
  • delay button 1104a and continue button 1104b graphical widgets are rendered graphically so as to visually emphasize delay button 1104a, and de-emphasize continue button 1104b, thereby encouraging the user to delay moving on to the second lesson module.
  • a soft-gate is based on time-relationship criteria with respect to a user’s time of completion of the first lesson module.
  • a soft-gate is used to encourage a user to wait until a next day to begin the second lesson module.
  • inter-lesson gate screen 1106 represents a hard-gate and does not allow for continued user progression onto the second lesson module. Instead, inter-lesson gate screen 1106 includes graphical content that encourages the user to take a break and practice particular behavioral skills via a practice module identified by graphical icon 506a.
  • graphical icon 1108a is a graphical widget - e.g., a selectable graphical button.
  • a graphical icon 1108a provides a link to a particular practice module, such that user selection of the graphical icon 1108a causes initiation (e.g., display) of a particular practice module to which it links (e.g., a symptom diary practice module, as shown in the example screen of FIG.1 IB, or other practice modules).
  • an inter-lesson gate screen may comprise a graphical widget that returns a user to a home screen.
  • interlesson gate screen 1106 comprises graphical widget 1108b, displaying text “Okay,” whereupon a user selection of graphical widget 1108b, they are returned to a home screen shown.
  • FIG. 12 A, FIG. 12B, FIG. 12C, and FIG. 12D are screenshots of an exemplary GUI for a symptom diary lesson module, according to one or more embodiments.
  • a sequence of interactive lesson modules may include a symptom diary lesson module that introduces and familiarizes a user with techniques for tracking their respiratory or co-morbid condition symptoms and/or medication side effects.
  • technologies described herein provide a convenient GUI that can (e.g., be demonstrated and/or designed to) facilitate user tracking and/or monitoring of their respiratory or co-morbid condition symptoms and/or medication side effects on a regular basis.
  • a tracking GUI may be included within a same system that provides, and controls user progression through interactive lesson modules, for example as a symptom diary practice module associated with a symptom diary lesson module.
  • access to a symptom diary practice module may be unlocked following completion of a symptom diary lesson module by the user, for example, as shown in FIG. 12C.
  • a selectable icon 1202 representing, and providing access to, the symptom diary practice module may be displayed on a user home-screen.
  • FIG. 13A, FIG. 13B, FIG. 13C, and FIG. 13D are screenshots of example user interactions with a symptom diary practice module, in accordance with one or more embodiments.
  • a symptom diary practice module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the introduction and education module discussed above.
  • a user may use graphical widgets to provide input associated with one or more aspects of their disease, disorder, and/or condition.
  • patient input include, but are not limited to, rating discomfort and stress on a scale (FIG. 13B), providing ratings characterizing additional symptoms specific to their disease, disorder, and/or condition (FIG. 13C) and providing information characterizing their daily meals (FIG. 13D).
  • FIG. 14A, FIG. 14B, FIG. 14C rating discomfort and stress on a scale
  • FIG. 13C rating discomfort and stress on a scale
  • FIG. 13D providing ratings characterizing additional symptoms specific to their disease, disorder, and/or condition
  • FIG. 13D providing information characterizing their daily meals
  • FIG. 14C, and FIG. 14D are screenshots of an exemplary GUI for introducing a personal model lesson module, in accordance with one or more embodiments.
  • a personal model lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the physical illness narrative module discussed above.
  • a sequence of interactive lesson modules includes a personal model lesson module that allows a user to identify cycles of behaviors, thoughts, emotions, and stressors that influence symptoms associated with their particular condition (e.g., from which they are suffering).
  • a personal model lesson module is used to implement, via a GUI, a structured process for conveniently soliciting user input of specific counter-productive behaviors, unhelpful thoughts, and negative emotions that they identify, e.g., in their life and/or as associated with their particular condition.
  • a particular condition from which the user is suffering is a respiratory condition, such as, but not limited to, COPD, asthma, chronic cough, ACOS, medication-induced chronic cough, chronic cough associated with GERD.
  • a personal model lesson module introduces a user to process for creating a personal model, for example so as to orient them and provide content designed to offer helpful motivation.
  • graphical content representing educational material is displayed to a user, for example to introduce them to concept of vicious cycles, and explain how symptoms, stress, and discomfort can create a feedback loop.
  • graphical content corresponding to shared user experiences and/or testimonials is displayed. For example, as shown in FIG. 14D, a user may be prompted to read about another user’s experiences with their respiratory condition and guided behavioral therapy approaches such as those described herein.
  • a user may view exemplary personal models created by and shared by others.
  • Other lesson modules for example any lesson modules described herein and/or additional lesson modules, providing for development of other behavioral therapy skills provided via the technologies described herein may also include content comprising patient experiences and/or testimonials.
  • a personal model lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the physical illness narrative module discussed above.
  • a personal model lesson module may retrieve stored information, previously input by a user. For example, in various embodiments, a user may have previously provided input identifying causes and/or stressors that impact their particular respiratory condition, and previously input user identifications of causes and stressors that impact the user’s respiratory condition may be retrieved and displayed, as shown in FIG. 15B. In some embodiments, a user provides input corresponding to causes and/or stressors associated with their particular respiratory condition via a personal model lesson module. In some embodiments, a user may be provided with a graphical list of selectable elements. In some embodiments, the user is prompted to select a predefined number of counter-productive behaviors, as shown in FIG. 15C. As shown in FIG.
  • the user for each user selected counter-productive behavior, the user is prompted to select one or more unhelpful thoughts related to the counter-productive behavior.
  • unhelpful thoughts are selected from a list of pre-defined thoughts.
  • a user may provide free-form textual input, for example via a text box.
  • negative emotions are selected from a list of pre-defined emotions.
  • a user may provide free-form textual input, for example via a text box.
  • FIG. 16 A, 16B, and 16C are screenshots of an exemplary personal model graphical representation, according to one or more embodiments.
  • a personal model graphical representation comprises text corresponding to user selected counter-productive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between each other, as shown in FIG. 16A and FIG. 16B.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms, previously input by the user and retrieved via the personal model lesson module and/or input within the personal model lesson module, as described herein.
  • a personal model graphical representation is rendered to have a form factor fitting one or more mobile device screens.
  • a personal model graphical representation can be rendered in a narrow, rectangular format, allowing a user to scroll through the rendered diagram to view its content.
  • a personal model graphical representation can be displayed as a zoom-able diagram, such that a user may zoom in and out to view portions of the diagram.
  • a personal model graphical representation can be displayed so as to allow a user to navigate through its content by panning, for example in a two-dimensional fashion.
  • FIG. 17A, FIG. 17B, FIG. 17C, and FIG. 17D are screenshots of an exemplary GUI for a reflections section of a personal model lesson module, according to one or more embodiments.
  • a personal model lesson module includes graphical content prompting a user to review their personal model.
  • a series of questions e.g., from a predefined list of questions, e.g., based on a therapeutic protocol
  • a series of questions are displayed and presented to the user along with their personal model graphical representation, prompting the user to consider their selections, identify links, consider possible changes in their behavior that could be implemented to address their symptoms, and the like.
  • FIG. 17 A, FIG. 17B, and FIG. 17C a sequence of user questions are presented.
  • Graphical content including passages of rendered text, mimicking conversation with a therapist can be displayed.
  • encouraging graphical content is displayed, and the user is returned to a home screen.
  • FIG. 18 A, FIG. 18B, FIG. 18C, and FIG. 18D are screenshots of an exemplary GUI for a symptom management lesson module, according to one or more embodiments.
  • a symptom management lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the respiratory management module discussed above.
  • FIG. 18 A, FIG. 18B, FIG. 18C, and FIG. 18D show an example symptom management lesson module and an associated symptom management goals practice module.
  • a symptom management goals practice module can be unlocked and made accessible to the user, as shown in FIG. 18B.
  • a user may access a symptom management goals module to create goals to manage their respiratory condition symptoms.
  • a user may, e.g., regularly, use a goals module to set goals such as goals pertaining to a regular timing and/or type of food and/or activity (e.g., physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary, etc.).
  • a goals module may provide for setting goals pertaining to medication adherence.
  • FIG. 19 A, FIG. 19B, FIG. 19C, and FIG. 19D are screenshots of an exemplary GUI for a unhelpful thought pattern lesson module, according to one or more embodiments.
  • an unhelpful thought pattern lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the cognitive restructuring and flexibility module discussed above.
  • FIG. 19 A, FIG. 19B, FIG. 19C, and FIG. 19D show an example unhelpful thought pattern lesson module and an associated thought record practice module.
  • a thought record practice module can be unlocked and made accessible to the user.
  • a user may access a thought record practice module to create thought entries tracking their thoughts and associated activities and feelings.
  • completed sessions may be indicated visually to a user.
  • completion of certain lesson modules unlocks various associated practice modules, which are then made accessible to the user via a screen of a GUI.
  • completion of lesson modules may cause population of portions of a user profile, which a user may review via a GUI.
  • completion of a user personal model module as described herein provides for creation of a personal model that identifies a particular user’s individual vicious cycle of related stressors, behaviors, emotions, and thoughts.
  • the data corresponding to a previously created personal model is stored and may be rendered for review and reflection by a user, via a profile screen.
  • interactive lesson modules, associated practice modules, user profile content, and the like may include a variety of other lesson modules, additionally or alternatively to those described herein.
  • various lesson modules and content thereof as described herein may be combined with other content, for example from other lesson modules described herein.
  • embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating respiratory health conditions using digital therapeutics in combination with other therapies in order to ensure that patients receive adequate care, support, and treatment for their respiratory health condition.
  • the inventions covered by the system and method disclosed herein can confer several benefits over conventional systems and methods, and such inventions are further implemented into many practical applications related to improvement of user health.
  • a computing system implemented method for treating respiratory health conditions using digital therapeutics in combination with other therapies comprises: providing a patient with a user interface to a therapeutics system; performing, by the therapeutics system, a pre-assessment of a patient exhibiting one or more health condition symptoms; generating, by the therapeutics system, patient profile and pre-assessment data based on the results of the patient pre-assessment; processing, by the therapeutics system, the patient profile and preassessment data to generate patient condition data; and processing, by the therapeutics system, the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components.
  • the computing system implemented method further comprises administering one or more of the first therapeutic treatment components to the patient through the user interface of the therapeutics system according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components to generate patient interaction data representing the patient’s interactions with the first and second therapeutic treatment components; processing, by the therapeutics system, the patient interaction data to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen; at least partly based on the intervention modification data, dynamically modifying aspects of the patient’s personalized intervention regimen to generate a modified personalized intervention regimen for the patient; and administering one or more of the first therapeutic treatment components in combination with one or more of the second therapeutic treatment components according to the modified personalized intervention regimen for the patient.
  • the therapeutics system is a prescription digital therapeutics (PDT) system.
  • the patient health condition symptoms are associated with one or more of a respiratory condition; and a co-morbid condition.
  • performing a pre-assessment of a patient includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of leicester cough questionnaire (LCQ); cough-specific quality of life questionnaire; health related quality of life (HRQOL) questionnaire; quality of life (QoL) questionnaire; visual analog scale for cough severity; cough severity score (CSS); cough severity diary (CSD); numeric rating scale (NRS); tussigenic challenges; a work and social adjustment scale (WSAS)-derived instrument; a clinical disease activity measurement instrument; a patient health questionnaire; a GAD-7 anxiety disorder questionnaire; and combinations thereof; and combinations thereof, and any other tool or instrument.
  • LCQ leicester cough questionnaire
  • HRQOL health related quality of life
  • QoL quality of life
  • CCS cough severity score
  • CSD cough severity diary
  • NFS numeric rating scale
  • WSAS work and social adjustment scale
  • performing a pre-assessment of a patient includes utilizing non-survey data obtained from one or more devices selected from the group of devices consisting of electronic health record-associated devices, torso-coupled devices, wearable devices, implanted devices, cardiovascular monitoring devices, sleep monitoring devices, location monitoring devices, social networking tracking devices, spirometer, peak flow meter, high-resolution computed tomography (CT) scanners, cough monitors, audio-recognition devices, electromyography (EMG) devices, accelerometers, plethysmographs, electrocardiographs, the LifeShirt, VitaloJAK, Leicester Cough Monitor (LCM), LR102, hull automatic cough counter, cough counter mobile applications, pulmonary function measuring tools, pulse-oxygen devices, and combinations thereof.
  • CT computed tomography
  • EMG electromyography
  • generating the patient profile and pre-assessment data includes obtaining one or more of: patient demographics data; patient electronic health record data; patient physiological health data; patient psychological health data; patient condition data; patient cough data, patient symptoms data; patient medications data; patient illness narrative data; patient goals data; and patient preferences data.
  • generating the patient condition data includes of one or more of: identifying the patient’s condition as a respiratory condition; identifying a co-morbid condition; identifying symptoms of the patient’s respiratory and/or co-morbid condition; identifying a severity of the patient’s cough and other symptoms of the respiratory and/or co-morbid condition(s); identifying the patient’s medication for the respiratory and/or co-morbid condition(s); identifying the patient’ s side effects from medication; identifying the patient’ s dosage information for medications; and identifying a severity of the patient’s medication side effects.
  • generating a personalized intervention regimen includes one or more of: processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to determine a first therapeutic treatment to be administered to the patient; defining a first plurality of therapeutic components associated with the first therapeutic treatment; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the first plurality of therapeutic components to be administered to the patient; generating first therapeutic treatment component data representing the selected one or more of the first plurality of therapeutic components; defining a first plurality of therapeutic protocols to be utilized in administration of the components represented by the first therapeutic treatment component data; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the first plurality of therapeutic protocols to utilize in administration of the components represented by the first therapeutic treatment component data; and generating first therapeutic treatment protocol data representing the selected one or more of the first plurality of therapeutic protocols to utilize in administration of the components represented by the first
  • generating a personalized intervention regimen further includes one or more of: processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to determine a second therapeutic treatment to be administered to the patient in combination with the first therapeutic treatment; defining a second plurality of therapeutic components associated with the second therapeutic treatment; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the second plurality of therapeutic components to be administered to the patient; generating second therapeutic treatment component data representing the selected one or more of the second plurality of therapeutic components; defining a second plurality of therapeutic protocols to be utilized in administration of the components represented by the second therapeutic treatment component data; processing, through the therapeutics system, the patient profile and preassessment data and the patient condition data to select one or more of the second plurality of therapeutic protocols to utilize in administration of the components represented by the second therapeutic treatment component data; and generating second therapeutic treatment protocol data representing the selected one or more of the second plurality of therapeutic protocols to utilize in administration of the components represented by the second
  • generating a personalized intervention regimen further includes one or more of generating, by the therapeutics system, a personalized intervention regimen for the patient, wherein the personalized intervention regimen for the patient defines the first therapeutic treatment component data to be administered to the patient according to the first therapeutic treatment protocol data in combination with the second therapeutic treatment component data to be administered to the patient according to the second therapeutic treatment protocol data.
  • the first therapeutic treatment is a guided behavioral therapeutic treatment, further wherein the guided behavioral therapeutic treatment is administered remotely through a user interface of the therapeutics system.
  • the guided behavioral therapeutic treatment includes components of therapies selected from the group of therapies consisting of cognitive behavioral therapy (CBT), mindfulness therapy, breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene training, laryngospasm behavioral modification, habit reversal training, aversion therapy, acceptance and commitment (ACT)-based interventions, psychotherapy, habit reversal training (HRT), arousal reduction training, rational-emotive therapy, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), relaxation therapy, progressive muscle relaxation (PMR) training, autogenic training (AT), biofeedback therapy, somatic anchoring therapy, hypnotherapy, cognitive defusion, coping techniques, experiential therapy, psychodynamic therapy, and combinations thereof.
  • CBT cognitive behavioral therapy
  • breathing exercises breathing exercises, cough suppression therapy, speech and language pathology therapy, voice therapy, vocal hygiene
  • the second type of therapeutic treatment is a non-behavioral therapeutic treatment including components of non-behavioral therapeutic treatments selected from the group of non-behavioral therapeutic treatments consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mind-body interventions; and treatments utilizing whole system medicine.
  • monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of: leicester cough questionnaire (LCQ); cough-specific quality of life questionnaire; health related quality of life (HRQOL) questionnaire; quality of life (QoL) questionnaire; visual analog scale for cough severity; cough severity score (CSS); cough severity diary (CSD); numeric rating scale (NRS); tussigenic challenges; a work and social adjustment scale (WSAS)-derived instrument; a clinical disease activity measurement instrument; a patient health questionnaire; a GAD-7 anxiety disorder questionnaire; and combinations thereof; and combinations thereof, and any other tool or instrument.
  • LCQ leicester cough questionnaire
  • HRQOL health related quality of life
  • QoL quality of life
  • CCS cough severity score
  • CSD cough severity diary
  • NFS numeric rating scale
  • tussigenic challenges a work and social adjustment scale (WSAS)-derived instrument; a clinical disease activity measurement instrument;
  • monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes utilizing nonsurvey data obtained from one or more devices selected from the group of devices consisting of: electronic health record-associated devices; torso-coupled devices; wearable devices; ingestible devices; implanted devices; smart-pill devices; medication tracking and/or delivery devices; location and/or activity monitoring devices; and social networking tracking devices.
  • devices selected from the group of devices consisting of: electronic health record-associated devices; torso-coupled devices; wearable devices; ingestible devices; implanted devices; smart-pill devices; medication tracking and/or delivery devices; location and/or activity monitoring devices; and social networking tracking devices.
  • monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes obtaining patient data including one or more of: patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient cough/wheezing data, patient medications data; patient medication adherence data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components are monitored remotely, in near- real time, contemporaneously with administration of one or more of the first therapeutic treatment; and the second therapeutic treatment.
  • a request for approval of the intervention modification data is communicated remotely to one or more of a health care practitioner associated with the patient; the patient; a relative of the patient; a caregiver of the patient; and a third party associated with the patient.
  • dynamically modifying aspects the patient’s personalized intervention regimen includes one or more of adjusting the order of administration of the behavioral therapy components; adjusting the order of administration of the non-behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the dosage of the non-behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records; updating the patient’s personal health records; updating the patient’s open medical records; and increasing personalization of the intervention regimen.
  • the patient’s personalized intervention regimen is modified remotely, in near-real time, contemporaneously with administration of one or more of the first therapeutic treatment; and the second therapeutic treatment.
  • a method for providing a prescription digital therapeutics (PDT) system for remotely administering guided behavioral therapy in combination with other types of respiratory conditions comprises: providing a patient with a therapeutics system; performing a preassessment of a patient exhibiting one or more health condition symptoms; generating patient profile and pre-assessment data based on the results of the patient pre-assessment; processing the patient profile and pre-assessment data to generate patient condition data; processing the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components; administering one or more of the first therapeutic treatment components to the patient according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components to generate patient interaction data representing the patient’s
  • a system comprises one or more processors and one or more physical memories, the one or more physical memories having stored therein data; a patient computing system; a user interface provided to the patient computing system, the user interface providing access to a therapeutics system; a therapeutics system which provides remotely located patients and caretakers access to the therapeutics system, the therapeutics system using the one or more processors and one or more physical memories to perform the above described methods/processes.
  • a system comprises one or more processors and one or more physical memories, the one or more physical memories having stored therein data; a patient computing system; a user interface provided to the patient computing system, the user interface providing access to a therapeutics system; a therapeutics system which provides remotely located patients and caretakers access to the therapeutics system, the therapeutics system using the one or more processors and one or more physical memories to perform the above described methods/processes.
  • the systems and methods disclosed herein allow behavioral therapy to be administered to patients suffering from respiratory conditions in a convenient and flexible, yet structured fashion, via a digital therapeutics
  • the invention(s) can employ non-traditional systems and methods for providing interventions to patients exhibiting symptoms associated with one or more health conditions.
  • the invention(s) can deliver psychological-based interventions, such as behavioral therapy-based interventions and other interventions (described in more detail above) to users/patients, by way of a platform having components implemented in a mobile device environment and/or other computer or internet-based architecture.
  • digital therapeutics (DTx) technologies e.g., systems and methods
  • DTx may be used to administer behavioral therapies in combination with a variety of non-behavioral therapies in a controlled fashion, as treatment for one or more conditions described herein.
  • the invention(s) use components of the platform to process large amounts of user data, create individual user baselines (e.g., health, cough/wheezing frequency and/or severity, mood, symptoms, medication side effects, etc. over time), remotely deliver personalized interventions, and remotely monitor user interactions with such interventions in near real-time, i.e. dynamically, in a manner that cannot be practically implemented by the human mind.
  • individual user baselines e.g., health, cough/wheezing frequency and/or severity, mood, symptoms, medication side effects, etc. over time
  • the disclosed method and system for effectively, efficiently, and remotely administering guided behavioral therapy in combination with other types of respiratory therapies requires specific processes that utilize components of the platform disclosed herein to process user data, deliver interventions, and monitor user interactions with such interventions, and as such, does not encompass, embody, or preclude other forms of innovation in the area of healthcare technologies. Further, the disclosed embodiments of systems and methods for dynamically, efficiently, and remotely treating respiratory health conditions using digital therapeutics are not abstract ideas for at least several reasons.
  • health practitioners are provided with a tool to help them generate personalized and adaptive intervention regimens for use in treating respiratory health conditions using digital therapeutics in combination with other therapies, which ensures that patients are provided with personalized and effective assistance, treatment, and care.
  • the method and system disclosed herein is not an abstract idea, and also serves to integrate the ideas disclosed herein into practical applications of those ideas.
  • the present invention also relates to an apparatus or system for performing the operations described herein.
  • This apparatus or system may be specifically constructed for the required purposes, or the apparatus or system can comprise a system selectively activated or configured/reconfigured by a computer program stored on a non-transitory computer readable medium for carrying out instructions using a processor to execute a process, as discussed or illustrated herein that can be accessed by a computing system or other device.
  • the present invention is well suited to a wide variety of computer network systems operating over numerous topologies.
  • the configuration and management of large networks comprise storage devices and computers that are communicatively coupled to similar or dissimilar computers and storage devices over a private network, a LAN, a WAN, a private network, or a public network, such as the Internet.

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Epidemiology (AREA)
  • Public Health (AREA)
  • Primary Health Care (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Social Psychology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Psychiatry (AREA)
  • Hospice & Palliative Care (AREA)
  • Developmental Disabilities (AREA)
  • Child & Adolescent Psychology (AREA)
  • Business, Economics & Management (AREA)
  • General Business, Economics & Management (AREA)
  • Chemical & Material Sciences (AREA)
  • Psychology (AREA)
  • Medicinal Chemistry (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biophysics (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Surgery (AREA)
  • Urology & Nephrology (AREA)
  • Pharmaceuticals Containing Other Organic And Inorganic Compounds (AREA)
  • Medicines That Contain Protein Lipid Enzymes And Other Medicines (AREA)

Abstract

L'invention concerne des systèmes et des méthodes permettant de traiter, d'atténuer, de prévenir ou de réduire la probabilité de développer un trouble respiratoire, un ou plusieurs symptômes et comorbidités associés au trouble respiratoire et/ou un ou plusieurs effets secondaires associés à des interventions thérapeutiques pour traiter le trouble respiratoire à l'aide d'agents thérapeutiques numériques. L'invention concerne en outre des systèmes et des méthodes permettant d'améliorer l'adhésion aux interventions thérapeutiques et d'améliorer les performances des interventions thérapeutiques à l'aide d'agents thérapeutiques numériques.
PCT/US2023/060363 2022-01-20 2023-01-10 Méthodes et systèmes de traitement d'affections respiratoires à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies Ceased WO2023141376A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US202263301260P 2022-01-20 2022-01-20
US63/301,260 2022-01-20

Publications (2)

Publication Number Publication Date
WO2023141376A2 true WO2023141376A2 (fr) 2023-07-27
WO2023141376A3 WO2023141376A3 (fr) 2023-09-28

Family

ID=87349319

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2023/060363 Ceased WO2023141376A2 (fr) 2022-01-20 2023-01-10 Méthodes et systèmes de traitement d'affections respiratoires à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies

Country Status (1)

Country Link
WO (1) WO2023141376A2 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119679395A (zh) * 2024-12-04 2025-03-25 山东大学 一种基于动力学图融合的腺样体肥大辅助检测系统及方法

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
HK1206601A1 (en) * 2012-04-02 2016-01-15 Moderna Therapeutics, Inc. Modified polynucleotides for the production of biologics and proteins associated with human disease
WO2014071512A1 (fr) * 2012-11-06 2014-05-15 Universite Laval Polythérapie et méthodes pour le traitement de maladies respiratoires
US20190083809A1 (en) * 2016-07-27 2019-03-21 Z2020, Llc Componentry and devices for light therapy delivery and methods related thereto

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119679395A (zh) * 2024-12-04 2025-03-25 山东大学 一种基于动力学图融合的腺样体肥大辅助检测系统及方法

Also Published As

Publication number Publication date
WO2023141376A3 (fr) 2023-09-28

Similar Documents

Publication Publication Date Title
DiMatteo et al. Health behavior change and treatment adherence: Evidence-based guidelines for improving healthcare
US20220028529A1 (en) Methods and systems for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics
US20220028528A1 (en) Methods and systems for treating health conditions using prescription digital therapeutics
US20220028541A1 (en) Methods and systems for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies
EP4233071A1 (fr) Méthodes et systèmes pour le traitement d'états de santé à l'aide de thérapies numériques de prescription
Ng et al. Self-determination theory applied to health contexts: A meta-analysis
US20200411185A1 (en) Adaptive interventions for gastrointestinal health conditions
McKibbin et al. Barriers and facilitators of a healthy lifestyle among persons with serious and persistent mental illness: perspectives of community mental health providers
US20230111078A1 (en) Distributed network for modifiable interactive sessions and adherence enhancement thereof
Yang et al. Balancing online pharmacy services for patient adherence: a stimulus-organism-response perspective
Kressbach Breath work: mediating health through breathing apps and wearable technologies
WO2022086783A1 (fr) Méthodes et systèmes pour traiter des troubles gastro-intestinaux et des états de santé inflammatoires à l'aide de thérapies numériques de prescription
WO2023133573A1 (fr) Méthodes et systèmes de traitement d'états de douleur chronique à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies
WO2023141376A2 (fr) Méthodes et systèmes de traitement d'affections respiratoires à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies
WO2024011105A1 (fr) Méthodes et systèmes de traitement d'acouphènes à l'aide d'agents thérapeutiques numériques
WO2023133575A2 (fr) Méthodes et systèmes de traitement d'états de démangeaison chronique à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies
Potter et al. Physician-authored feedback in a type 2 diabetes self-management app: acceptability study
Higgins et al. Smartphone apps for health and wellness
Aughterson Social prescribing for mental health and well-being: mechanisms of action, active ingredients, and barriers & enablers to effective engagement
Kroon Van Diest Intensive outpatient treatment of pediatric rumination syndrome
Cabassa Addressing health inequities in people with serious mental illness: A call to action
Jafari Assessing the Feasibility, Acceptability, Preliminary Efficacy, and Anticipated Clinical Practice Implementation of a Mindful Eating Smartphone Application: A Mixed Methods Analysis among Undergraduate Women with Binge Eating and Clinical Experts.
WO2022086784A1 (fr) Méthodes et systèmes pour traiter des états de santé gastro-intestinaux et inflammatoires faisant appel à des thérapies numériques sur prescription en association avec d'autres thérapies
Aigner Towards Semantic Interoperability for Behavior Change Driven Serious Games and Gamified Mobile Applications–Platform Engineering for Prevention of NCDs
Halpen Shaping Wellness: Clay as an Acceptance Commitment Therapy Modality for Increasing Values-Directed Behavior in Adults With Psychological Distress

Legal Events

Date Code Title Description
NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205 DATED 13/11/2024)

122 Ep: pct application non-entry in european phase

Ref document number: 23743834

Country of ref document: EP

Kind code of ref document: A2