WO2017042831A2

WO2017042831A2 - A system and method of measuring productivity and longevity of human beings based on analysis of their genes in a biological and functional context

Info

Publication number: WO2017042831A2
Application number: PCT/IN2016/050296
Authority: WO
Inventors: Anjum WASEEMA; Shveta GUPTA
Original assignee: Isense Solution Private Ltd
Current assignee: Isense Solution Private Ltd
Priority date: 2015-09-07
Filing date: 2016-09-05
Publication date: 2017-03-16
Anticipated expiration: 2018-03-07
Also published as: WO2017042831A3

Abstract

The invention relates to a BioMachine, a gene-driven distributed cognitive system, for providing reasonably accurate metabolic picture and measure human productivity and longevity of an individual from his/her genes when placed in a most rationalized biological and functional context. BioMachine is transformed using a personalized client software having gene-related intelligence dynamically in sync with cloud service for personal usage data and layered with gene/protein function data tailored to precisely and accurately an individuals' biological identity, to guesstimate his/her functional acumen best judged ever in the context of human productivity and sustainable longevityby and provide to the end user based on the input data. The proposed system is built on distributed /edge computing and Grid computing circuitry to combine knowledge into bio wisdom to be published in a genome wall and then, combine bio wisdom with inputs from continuous and distributed machine learning on digital usage to personalize experience and insights for the user.

Description

A SYSTEM AND METHOD OF MEASURING PRODUCTIVITY AND LONGEVITY OF HUMAN BEINGS BASED ON ANALYSIS OF THEIR GENES IN A BIOLOGICAL AND FUNCTIONAL CONTEXT

FIELD OF INVENTION The present invention generally relates to Life Sciences and Distributed Digital Systems to assist human productivity and longevity in future. More particularly discloses a BioMachine, a gene-driven distributed cognitive system and method of providing reasonably accurate metabolic picture and measure human productivity and longevity of an individual from his/her genes when placed in a most rationalized biological and functional context. BioMachine is aimed to solve present day human crisis made up of ambitions, failures, anxiety, depression and social exclusion. This will happen by making everyone perform to their biological optimum through a personalized productivity threshold. When individuals will be guided by gene-driven distributed cognitive system to a nearest achievable productivity indicator, they shall be able to live peaceful and satisfying life as a sustainable career culmination.

BACKGROUND OF THE INVENTION

Many systems have been around the world to measure and assess the human productivity. However, most human productivity systems currently in practice either ignore or are indifferent to human biological co-ordinates entailing wellness, wisdom, metabolic superiority in terms of predicted work and intellect acumen of a human being. They focus merely on scholastic, professional excellence, skills and experience to achieve organisational development. In most cases, human productivity is assessed based on scholastic and career related indicators. Sometimes, human productivity is also related to nutrition physical fitness and intelligence coefficient of individuals. Biological co-ordinates of human fitness, thriftiness, stress tolerance, accuracy and timeliness of decision making and judgements are hitherto unknown. There are different measures of productivity and the choice among them depends either on the purpose of the productivity measurement and/or data availability. One of the most widely used measures of productivity is Gross Domestic Product (GDP) per hour worked, (published by OECD - The Organisation for Economic Co-operation and Development). Another productivity measure is so called multi factor productivity (MFP) also known as total factor productivity (TFP). It measures the residual growth that cannot be explained by the rate of change in the services of labour, capital and intermediate outputs, and is often interpreted as the contribution to economic growth made by factors such as technical and organisational innovation, (published by OECD). In addition, several statistical offices publish productivity accounting handbooks and manuals with detailed accounting instructions and definitions. Presently, no standard platforms or technologies exist in relation to understanding of human productivity based on human biology. In other words there are no meaningful matches to the systems that use productivity-focused bio-machines.

It has now become sufficiently clear that human genetic traits impact their productivity. Humans have specific genetic traits that indicate the method by which they gain, retain and change the information. Increased information processing capacity, speed and efficiency are result of biological maturation and experience development. Human biology, in particular, the genetic potential entailing productivity and longevity have not been explored as contributors to human activity related index/factors.

The merit of our approach lies in building BioMachine - a gene-driven distributed cognitive system providing reasonably accurate metabolic picture and measure human productivity and longevity of an individual from his/her genes when placed in a most rationalized biological and functional context.

Hence the present disclosure is directed towards improving the efficiency of measuring productivity and longevity of human beings based on analysis of their genes in biological and functional context. In that context, BioMachine is a personalized, distributed computing paradigm layered with gene/protein function data tailored to precisely and accurately capture an individuals' biological identity and guesstimate his/her functional acumen best judged ever in the context of human productivity and sustainable longevity. The proposed BioMachine builds on distributed /edge computing and Grid computing circuitry to combine knowledge into bio wisdom to be published in a genome wall and then, combine bio wisdom with inputs from continuous and distributed machine learning on digital usage to personalize experience and insights for the user. The BioMachine is a method to attempt this in an efficient, accurate and cost-effective way. OBJECTIVES OF THE PRESENT INVENTION

Therefore, the main objective of the present invention is to provide a system and method for measuring productivity and longevity of human beings based on analysis of their genes in biological and functional context.

Another object of the present invention is to provide a system and method that facilitates a service provider or an employer to assess the capability of an individual in a more scientific way.

Yet another objective of the invention is to develop a biological, computational and numeric framework (a BioMachine) to assign a metric of productivity and longevity to each human. One more objective of the invention is to provide a system wherein a unique holistic profile of a given individual in the form of his/her genes, proteins, pathways and biomarkers is integrated in to a computer chip, a circuit, or a program that can be readable to a number of stake holders or service providers such as employers, security providers, insurance companies, matrimonial services, medical doctors, immigration officials and courts etc.

Another objective of the invention is to develop a personal assistant program in future that incorporates the biological identity chip as well as productivity and longevity metrics of an individual to generate/broadcast specific advices as to food, medicines, job opportunities, investment opportunities, travel advice, weather information, and reminders on health check-ups etc. SUMMARY OF THE INVENTION

In accordance with the present invention, BioMachine is a gene-driven distributed cognitive system having deep learning and understanding of inner biological circuitry of a human incorporating human genome, metabolome and microbiome data integrated with available medical history, food habits, ancestry/pedigree, geographical and climatic parameters (rainfall, humidity, temperature, flora and fauna) as well as economic indicators. The BioMachine will aid human living in personal, professional and social settings. The computing device of the BioMachine is transformed using a personalized client software having gene-related intelligence dynamically in sync with cloud service for personal usage data and is layered with gene/protein function data tailored to precisely and accurately an individuals' biological identity to guesstimate his/her functional acumen best judged ever in the context of human productivity and sustainable longevityby and provide to the end user based on the input data. The proposed BioMachine builds on distributed /edge computing and Grid computing circuitry to combine knowledge into bio wisdom to be published in a genome wall and then, combine bio wisdom with inputs from continuous and distributed machine learning on digital usage to personalize experience and insights for the user. The customized client information device used therein is selected from personal computer, smart phone or smart watch. According to another aspect of the invention method of measuring human productivity and longevity of an individual from his/her genes when placed in a most rationalized biological and functional context, by the said BioMachine also is disclosed. The method measuring involves one or more of the following steps:- a) Analysis of the complexity of functional relationships within the human genome making use of advanced Edge and Grid computing approach;

b) Allocating to each human genome a smart agent package which is the representation of an array consisting of sub routine packages together, along with a data description consisting of active agents which are associated with biological pathways and a router agent which helps in inter-agent message passing unique identifiers generated by pathways, that streamlines the information flow within its host as well as initiate external interactions with other agents;

c) Mapping the responsibilities attached to each of the agents to their respective pathway behavior and router agent providing filters so that each of the active agents contribute to bio wisdom;

d) Filtering by the router agent and sorting information coming from all active agents based on the basis of existing understanding of pathway behaviors;

e) Forming the edge computing circuitry by said self-learning agents to mimic a chain of biological pathways in the human body;

f) Compile bio-wisdom f{x) into a collected bin called genome wall which reduces mammoth biological complexity to merely a few digits, by each of said smart agent package from various human genomes;

g) Feeding said bio-wisdom f{x) into a machine learning model built on human functional context;

h) Learning from human living with respect to a) location of living matched with medical conditions in those locations, b) type of work that human did in past and skills/learning levels a human possessed at those stages of life, by said machine learning model;

i) Analyzing the complexity of functional relationships within the human genome and measuring the 'Human Productivity and Longevity Factor (HPLF)' or a biologically inspired wellness index taking into account of Pathways data; microbiome;

Metabolome; candidate's gene polymorphisms; Disease susceptibility coordinates;

Allergy profile; Healthy clinical data; Demographic and family history; Educational and work data; Scholarly and creativity data; Living location data; Biometric/ face scan data; Travel / Climate data; Wealth and investment data; Web usage; Social media profile/ Community feedback.

BRIEF DESCRIPTION OF DRAWING

These and other features, aspects and advantages of the present invention will become apparent to those skilled in the art upon reading the following detailed description of the preferred embodiments, in conjunction with the following accompanying drawings.

Figure 1 : BioMachine - a gene-driven distributed cognitive system.

Figure 2: Scheme to explain how polymorphisms of the candidate genes associated with circadian patterns in humans could impact sleep related phenotypes

Figure 3: Method of measuring productivity and longevity of human beings by Bio- machine- Stage-1

Figure 4: Method of measuring productivity and longevity of human beings by Bio- machine- Stage-2. Figure 5: Flow diagram depicting factors being considered by the Bio-machine to arrive at 'Human Productivity and Longevity Factor'.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides a state of the art system and method for measuring productivity and longevity of human beings based on analysis of their genes in biological and functional context.

BioMachine is aimed to solve present day human crisis made up of ambitions, failures, anxiety, depression and social exclusion. This will happen by making everyone perform to their biological optimum through a personalized productivity threshold. When individuals will be guided by their computing system to a nearest achievable productivity indicator, they shall be able to live peaceful and satisfying life as a sustainable career culmination.

It has now become sufficiently clear that human genetic traits impact their productivity. Humans have specific genetic traits that indicate the method by which they gain, retain and change the information. Increased information processing capacity, speed and efficiency are result of biological maturation and experience development. In that context, BioMachine is a personalized, a gene driven distributed cognitive system layered with gene/protein function data tailored to precisely and accurately capture an individuals' biological identity and guesstimate his/her functional acumen best judged ever in the context of human productivity and sustainable longevity. Referring to Fig.1 , The Biomachine will transform computing devices using a personalized client software having gene-related intelligence dynamically in sync with cloud service for personal usage data and layered with gene/protein function data tailored to precisely and accurately an individuals' biological identity and guesstimate his/her functional acumen best judged ever in the context of human productivity and sustainable longevity and provide to the end user based on the input data. The personal data includes (inherent capabilities) such as those related to identity, demography, health records, biometrical indices and socioeconomic indicators as well as data related to prospective life experiences (reactive tendencies) in order to make it nearly personalized to a client. We propose to incorporate biological information through a consensus genotype based approach that takes in to account the population level portrait of gene structure and function for races, lineages and communities. This system can be further augmented and tailored to build a BioMachine comprised of a customized client device and a personalized cloud dynamically synced with personal data at inclusion (inherent capabilities) such as those related to identity, demography, health records, biometrical indices and socioeconomic indicators as well as data related to prospective life experiences (reactive tendencies) in order to make it nearly personalized to a client.

The proposed human productivity and longevity factor is a variable number that is derived by our BioMachine in respect of every single adult human being. The profile so obtained could be able to provide an accurate, robust and numerically validated leadership score based on positive energy and healthy pathways, tangible career achievements, creative competencies and reactive tendencies of an individual. This information is most likely to reveal a 'human operating system', an unique 360 degree profile which guides behavior in day to day life and in the leadership domain, and impacts decision making. Said 'human operating system' should in future be the driver of all productivity related applications and personal assistants that can match or mimic the decision making pattern and tendencies of their owners/masters.

Referring to Fig -3, advanced Edge and Grid computing approach would facilitate analysis of the complexity of functional relationships within the human genome. Each human genome will be allocated a smart agent package that can streamline the information flow within its host as well as initiate external interactions with other agents. The smart agent package is the representation of an array consisting of sub routine packages together, along with a data description of the data included with them - it consists of active agents which are associated with biological pathways and a router agent which helps in inter-agent message passing unique identifiers generated by pathways. The responsibilities attached to each of the agents can be mapped to their respective pathway behavior and router agent provides filters so that each of the active agents can contribute to bio wisdom. The router agent is also responsible to filter and sort information coming from all active agents based on the basis of existing understanding of pathway behaviors. These self-learning agents form the edge computing circuitry to mimic a chain of biological pathways in the human body and represent the first stage of BioMachine. Each of this smart agent packages from various human genomes then compile bio-wisdom f{x) into a collected bin called genome wall. This will reduce mammoth biological complexity to merely a few digits. Referring to Fig.4, second stage of BioMachine is how this bio-wisdom f(x) feeds into a machine learning model built on human functional context. This machine learning model will learn from human living incl. location of living matched with medical conditions in those locations, type of work that human did in past and skills/learning levels a human possessed at those stages of life. Referring to Fig.5, BioMachine will further include Pathways data; microbiome; Metabolome; candidate's gene polymorphisms; Disease susceptibility coordinates; Allergy profile; Healthy clinical data; Demographic and family history; Educational and work data; Scholarly and creativity data; Living location data; Biometric/ face scan data; Travel / Climate data; Wealth and investment data; Web usage; Social media profile/ Community feedback. The measure of Human Productivity and Longevity could then be used to predict biological wellness/normalcy and longevity of an individual in future based on robust gene-gene/protein-protein interactions. The more robust (multi-enriched/foolproof) pathways, if exist, in some individuals but not in all, could in turn be of high significance to herald productivity co-ordinates and therefore, employers, institutions, insurance providers and government agencies could be the potential stakeholders apart from individuals themselves. The 'Human Productivity and Longevity Factor (HPLF)' or a biologically inspired wellness index (<10: below average; 10: marginal; 10-15: very good; 15-20; excellent; >20: exceptional) based on understanding of BioMachine should be propounded.

Example 1 :

An example here describes the essence of BioMachine. Based on sleep-wake cycle (circadian rhythm) of an individual, that is associated with functional polymorphisms and genotypes of candidate genes (Piggins, 2000; Pedrazzoli et al., 2010), CLOCK, CRY1 , PER1 , PER2, PER3 and Dec2 (He Y, et al., 2009), sleep requirement of a person can be estimated or predicted by the BioMachine in order to decide if computing/browsing sessions could be logged out (auto logout) when it is time for the individual to take rest. This will leave the operator with no option but to retire for a normal sleep cycle. Besides pre-fed genetic data (inherent capabilities), this function can be based on the bio-capture of a person's reactive tendencies such as work load, hours spent online, calendar events, travel itineraries, day-light length sessions and an eventual estimate of fatigue build up.

Estimation of duration of sleep of an individual Referring the Figure 4, the sleep duration of an individual may depend upon polymorphism or transcript level change of circadian genes, their daily working habits and livelihood. • SNP analysis method would be required to carry out a GWAS (Genome-wide association study) (McCarthy and Hirschhorn, 2008) concerning a group or population wherein metadata are important; the metadata of an individual i.e. the daily activity time table etc. would be significant in order to incorporate in association with gene polymorphisms for the BioMachine to predict normal or abnormal sleep cycle

• Circadian clock gene polymorphisms also modulate breast cancer risk as night shift work has been linked to an increased risk of breast cancer suggestive of a role of circadian disruption (Truong et al., 2014; Grundy et al., 2013; Monsees et al., 2012; Rabstein et al., 2014)

• Clock gene polymorphisms have also been linked to sleep disorders, depressive symptoms, male infertility, Alzheimers' disease, alcohol abuse and suicidal behavior (Maglione et al., 2015; Hida et al., 2014; Hua et al., 2014; Hodzik et al., 2013; Chen et al., 2013; Partonen, 2015; Galfalvy et al., 2015). · Clock genes have also been linked to energy metabolism and obesity (Sancar et al., 2014 and Valladares et al., 2015).

Example 2:

In case of hypertensive persons, based on the insertion/deletion of angiotensin- converting enzyme, angiotensinogen M235T, angiotensin II type 1 receptor A1 166C, aldosterone synthase C344T, and mineralocorticoid receptor A4582C etc (Freitas et al., 2007). The BioMachine would be able to determine the emotional stability of individuals while also incorporating blood pressure and pulse (gauged through a hand band) data. Based on emotional profiles, certain sensational news items, market trends and pictures etc. shall be automatically masked by the BioMachine. Certain gene polymorphisms such as SLC6A4 SNP rs16965628 and 5-HTTLPR etc. are associated with cognitive control of emotions in certain individuals (Morey et al., 201 1 ). The BioMachine would be able to be cautious of any mention/ discussion /chat /communication of past traumatic memories etc. Example 3:

Further, oxytocin receptor polymorphism {OXTR) rs53576, a gene previously related to socioemotional sensitivity, in conjunction with cultural norms is important in understanding behavioral outputs in relation to cultural and traditional inputs for an individual to estimate empathy (Kim et al., 2010). For example, emotional suppression is normative in East Asian cultures but not in American culture. BioMachine would be able to evolve real time advisories related to cultural change for such individuals who would carry the above polymorphisms.

Gene functions related to behavioral, neuropsychological, motor and cardiovascular indicators estimated for given communities are used to train BioMachine via intensive machine learning, game theoretical and probability based algorithms to portray nearly accurate 'virtual personalities' that can be maneuvered by a personalized computer interface while also incorporating biometric, demographic and online usage data from a personalized cloud. GWAS data broadly related to cognition, intelligence, dementia, fatigue, systemic disorders, etc., for example, can play crucial roles related to guesstimating productivity indicators.

As some studies point at the association of under productivity to frustration and human crisis, BioMachine can be made in to a 'counselor' watchful of susceptible individuals prone to stress and fatigue, anxiety, obsessive-compulsive disorder, suicidal tendencies and or alienation/exclusion etc. and those who could resort to extreme or fatal decision making (Galfaivy et al., 2015). At the same time, the BioMachine shall be able to keep a tab on the euphoria of highly productive individuals through a human value based system of 'virtual preaching'. A balance of these two predictive functions will be the real essence of sustainable human wellbeing over a longer period (productive longevity).

BioMachine is a personalized system functioning based on, distributed computing paradigm layered with gene/protein function data tailored to precisely and accurately capture an individuals' biological identity and guesstimate his/her functional acumen best judged ever in the context of human productivity and sustainable longevity. Prediction of false positive networks would be avoided. Novel and hitherto undefined pathways should be the key to understand new biological functions that will be enriched only in exceptional individuals. Diversity of pathways predicted from different human genomes would signify personalized and tailor made wellness/ intelligence/ nutrition/ allergy/ disease advice. The BioMachine will further integrate digital data entailing medical history, food habits, ancestry and pedigree, geographical and climatic parameters (rainfall, humidity, temperature, flora and fauna) as well as economic indicators from digital footprint of an individual in the global web, in order to predict integrated wellness profile firmly enshrined in genome derived biological state of art.

The BioMachine has application in following functional areas: a) Personalized PC - complete personalized tasks on behalf of user

b) Food labelling - provide food labels based on human Productivity and Longevity factor

c) Medical prescription - provide personalized medicines

d) Hiring Decision - provide productivity insights into prospective employees e) Insurance Companies - provide longevity insights for insurance coverage f) Government schemes - targeted government interventions in population

g) Immigration and naturalization - understand immigrant impact to country

h) Career plans/ counselling - personalized career moves based on potential i) Drug discovery - provide deep insights into human pathways

j) Hospital products - personalize hospital services based on genetic insights

We have brought out the novel features of the invention by explaining some of the preferred embodiments under the invention, enabling those skilled in the art to understand and visualize our invention. It is also to be understood that the invention is not limited in its application to the details set forth in the above description. Although the invention has been described in considerable detail with reference to certain preferred embodiments thereof, various modifications can be made without departing from the spirit and scope of the invention as described herein above and as defined in the following claims.

Claims

We claim,

1 . A BioMachine, a gene-driven distributed cognitive system, that provides reasonably accurate metabolic picture and measures human productivity and longevity of an individual from his/her genes when placed in a most rationalized biological and functional context comprising of customized client device that is being transformed using a personalized client software having gene-related intelligence dynamically in sync with cloud service for personal usage data and layered with gene/protein function data tailored to precisely and accurately an individuals' biological identity to guesstimate his/her functional acumen best judged ever in the context of human productivity and sustainable longevity and provide to the end user based on the input data.

2. The BioMachine as claimed in claim 1 , wherein said customized client information device is selected from personal computer, smart phone or smart watch.

3. The BioMachine as claimed in claim 1 , wherein it it is built on distributed /edge computing and Grid computing circuitry and to combine knowledge into bio wisdom to be published in a genome wall and then, combine bio wisdom with inputs from continuous and distributed machine learning on digital usage to personalize experience and insights for the user.

4. The BioMachine as claimed in claim 1 , wherein said personal usage data represents inherent capabilities related to identity, demography, health records, biometrical indices and socioeconomic indicators as well as data related to prospective life experiences indicative of reactive tendencies in order to make it nearly personalized to a client.

5. The BioMachine as claimed in claim 1 , wherein it carry out deep learning and understanding of inner biological circuitry of a human incorporating human genome, metabolome and microbiome data integrated with available medical history, food habits, ancestry/pedigree, geographical and climatic parameters (rainfall, humidity, temperature, flora and fauna) as well as economic indicators.

6. The BioMachine as claimed in claim 1 , wherein it is capable of providing a unique holistic profile of a given individual in the form of his/her genes, proteins, pathways and biomarkers integrated in to a computer chip, a circuit, or a program that is readable to a number of stake holders or service providers selected from employers, security providers, insurance companies, matrimonial services, medical doctors, immigration officials and courts.

7. The BioMachine as claimed in claim 1 , wherein it facilities to develop a personal assistant program that incorporates the biological identity chip as well as productivity and longevity metrics of an individual to generate/broadcast specific advices as to food, medicines, job opportunities, investment opportunities, travel advice, weather information, and reminders on health check-ups.

8. The BioMachine as claimed in claim 1 , wherein it derives human productivity and longevity factor, a variable number in respect of every single adult human being and the profile so obtained could be able to provide an accurate, robust and numerically validated leadership score based on positive energy and healthy pathways, tangible career achievements, creative competencies and reactive tendencies of an individual and this information reveals 'human operating system', an unique 360 degree profile which guides behavior in day to day life and in the leadership domain, and impacts decision making as the said 'human operating system' will be the driver of all productivity related applications and personal assistants that can match or mimic the decision making pattern and tendencies of their owners/masters in the future.

9. The BioMachine as claimed in claim 1 , wherein it functions as a 'counselor' watchful of susceptible individuals prone to stress and fatigue, anxiety, obsessive-compulsive disorder, suicidal tendencies and or alienation/exclusion and those who could resort to extreme or fatal decision making and at the same time, it is capable of keeping a tab on the euphoria of highly productive individuals through a human value based system of 'virtual preaching'.

10. A method of measuring human productivity and longevity of an individual from his/her genes when placed in a most rationalized biological and functional context, by the BioMachine as claimed in claim 1 , comprising one or more of the steps of: a) analysis of the complexity of functional relationships within the human genome making use of advanced Edge and Grid computing approach;

d) filtering by the router agent and sorting information coming from all active agents based on the basis of existing understanding of pathway behaviors; e) forming the edge computing circuitry by said self-learning agents to mimic a chain of biological pathways in the human body;

i) analyzing the complexity of functional relationships within the human genome and measuring the 'Human Productivity and Longevity Factor (HPLF)' or a biologically inspired wellness index taking into account of Pathways data; microbiome; Metabolome; candidate's gene polymorphisms; Disease susceptibility coordinates; Allergy profile; Healthy clinical data; Demographic and family history; Educational and work data; Scholarly and creativity data; Living location data; Biometric/ face scan data; Travel / Climate data; Wealth and investment data; Web usage; Social media profile/ Community feedback.

1 1 . The method of measuring human productivity and longevity by the BioMachine as claimed in claim 10, wherein estimating or predicting the sleep requirement of a person is done in order to decide if computing/browsing sessions could be logged out (auto logout) when it is time for the individual to take rest, based on sleep-wake cycle (circadian rhythm) of an individual, that is associated with functional polymorphisms and genotypes of candidate genes, CLOCK, CRY1 , PER1 , PER2, PER3 and Dec2.

12. The method of measuring human productivity and longevity by the BioMachine as claimed in claim 10, wherein normal or abnormal sleep cycle is predicted by carrying out GWAS (Genome-wide association study) in association with gene polymorphisms by SNP analysis method and would be able to evolve real time advisories related to cultural change for such individuals who would carry the above polymorphisms as the GWAS data broadly related to cognition, intelligence, dementia, fatigue, systemic disorders, which play crucial roles related to guesstimating productivity indicators.

13. The method of measuring human productivity and longevity by the BioMachine as claimed in claim 10, wherein the emotional stability of individuals, especially in case of hypertensive persons, is determined based on the insertion/deletion of angiotensin-converting enzyme, angiotensinogen M235T, angiotensin II type 1 receptor A1 166C, aldosterone synthase C344T, and mineralocorticoid receptor A4582C, incorporating blood pressure and pulse (gauged through a hand band) data and based on emotional profiles, certain sensational news items, market trends and pictures and also automatically masks as certain gene polymorphisms such as SLC6A4 SNP rs16965628 and 5-HTTLPR are associated with cognitive control of emotions in certain individuals while being cautious of any mention/ discussion/ chat/communication of past traumatic memories.

14. The method of measuring human productivity and longevity by the BioMachine as claimed in claim 10, wherein it evolve real time advisories related to cultural change for such individuals who would carry the oxytocin receptor polymorphism {OXTR) rs53576, a gene previously related to socioemotional sensitivity, in conjunction with cultural norms in understanding behavioral outputs in relation to cultural and traditional inputs for an individual to estimate empathy.

15. The method of measuring human productivity and longevity by the BioMachine as claimed in claim 10, wherein gene functions related to behavioral, neuropsychological, motor and cardiovascular indicators estimated for given communities are used to train said BioMachine via intensive machine learning, game theoretical and probability based algorithms to portray nearly accurate 'virtual personalities' that is maneuvered by a personalized computer interface while also incorporating biometric, demographic and online usage data from a personalized cloud.

16. The method of measuring human productivity and longevity by the BioMachine as claimed in claim 10, wherein it integrates digital data entailing medical history, food habits, ancestry and pedigree, geographical and climatic parameters (rainfall, humidity, temperature, flora and fauna) as well as economic indicators from digital footprint of an individual in the global web, in order to predict integrated wellness profile firmly enshrined in genome derived biological state of art.

17. The method of measuring human productivity and longevity by the BioMachine as claimed in claim 10, wherein the 'Human Productivity and Longevity Factor (HPLF)' or a biologically inspired wellness index is <10 for below average; 10 for marginal; 1 0-15 for very good; 15-20 for excellent; and >20 for exceptional.

18. The BioMachine as claimed in claim 1 to 9 and the method as claimed in 10 to 17 is capable of using in the functional areas selected from: a) Personalized PC - complete personalized tasks on behalf of user;

b) Food labelling - provide food labels based on human Productivity and Longevity factor;

c) Medical prescription - provide personalized medicines;

d) Hiring Decision - provide productivity insights into prospective employees; e) Insurance Companies - provide longevity insights for insurance coverage; f) Government schemes - targeted government interventions in population; g) Immigration and naturalization - understand immigrant impact to country; h) Career plans/ counselling - personalized career moves based on potential; i) Drug discovery - provide deep insights into human pathways; and

j) Hospital products - personalize hospital services based on genetic insights.