ES3037959A1 - TF-LIO predictive system for encapsulation, preservation, and targeted release of bioactive ingredients by self-adjusted dielectric freeze-drying (Machine-translation by Google Translate, not legally binding) - Google Patents

Abstract

The TF-LIO system is an advanced, multidisciplinary, predictive platform for the functional encapsulation of bioactive compounds. It features an integrated multi-index dielectric computational model (aLIO, Sbio, ΔG__encap, IEL, Rlib), an adaptive inverse design strategy, real-time dielectric self-tuning using embedded ARM Cortex-M4 firmware, and cryptographic traceability based on SHA-256 algorithms. The method enables the design of functional capsules through computational simulation, optimizing structural stability, media compatibility, and release kinetics under varying physiological conditions (pH 5.5-8.5, salinity 20-45‰, temperature 20-45 °C), without requiring preliminary in vivo testing. This predictive and automatic approach improves the efficiency and reliability of functional bioactives development. The invention has direct application in sectors such as aquaculture, pharmacology, cosmetics, agriculture, bioprinting, and clean-label functional beverages, where it allows the delivery of antioxidants, probiotics, vitamins, nutraceuticals, or sensitive active ingredients, guaranteeing their stability and programmed release. TF-LIO provides a holistic and scalable solution that solves classic technical limitations such as dielectric instability, uncontrolled release, lack of adaptation to the target tissue or medium, and high dependence on empirical testing. Its modular extensibility allows the incorporation of aptamers, aligning the invention with personalized medicine and precision targeted release strategies. The system is designed in accordance with international standards such as EFSA QPS, FDA GRAS, EMA ICH Q8, and Regulation (EU) 2021/1379/EC, which facilitates its regulatory validation and industrial projection. Its modular architecture, low energy consumption, and compatibility with recycled biopolymers provide a sustainable competitive advantage. Overall, TF-LIO presents itself as a versatile, robust, and evolving platform technology, capable of transforming bioactive encapsulation in regulated and demanding sectors, with disruptive potential in global markets with high scientific, technological, and environmental demands. (Machine-translation by Google Translate, not legally binding)

Description

DESCRIPTION

TF-LIO predictive system for encapsulation, preservation and targeted release of bioactives by self-adjusting dielectric lyophilization

Summary of the invention

The TF-LIO system constitutes an advanced and multidisciplinary predictive platform for the functional encapsulation of bioactive compounds, characterized by the integration of a multi-index dielectric computational model (aLIO, Sbio, AG_encap, IEL, Rlib), an adaptive inverse design strategy, real-time dielectric self-tuning using embedded ARM Cortex-M4 firmware, and cryptographic traceability based on SHA-256 algorithms.

The method allows for the design of functional capsules through computational simulation, optimizing structural stability, compatibility with the medium, and release kinetics under varying physiological conditions (pH 5.5–8.5, salinity 20–45%, temperature 20–45 °C), without requiring preliminary in vivo trials. This predictive and automated approach improves the efficiency and reliability of functional bioactive development.

The invention has direct application in sectors such as aquaculture, pharmacology, cosmetics, agriculture, bioprinting and clean label functional beverages, where it allows the delivery of antioxidants, probiotics, vitamins, nutraceuticals or sensitive actives, guaranteeing their stability and programmed release.

TF-LIO provides a holistic and scalable solution that addresses classic technical limitations such as dielectric instability, uncontrolled release, lack of adaptation to target tissue or medium, and high dependence on empirical assays. Its modular extensibility allows for the incorporation of aptamers, aligning the invention with personalized medicine and precision targeted drug delivery strategies.

The system is designed in accordance with international standards such as EFSA QPS, FDA GRAS, EMA ICH Q8, and Regulation (EU) 2021/1379/EC, facilitating its regulatory validation and industrial scalability. Its modular architecture, low energy consumption, and compatibility with recycled biopolymers provide a sustainable competitive advantage.

Overall, TF-LIO presents itself as a versatile, robust and evolutionary platform technology, capable of transforming the encapsulation of bioactives in regulated and demanding sectors, with disruptive potential in global markets with high scientific, technological and environmental demand.

Description of the invention: TF-LIO system

1. Nature and purpose of the invention

The present invention relates to a predictive computational system for the functional encapsulation of bioactive compounds, called TF-LIO (Thermodynamic-Electromechanical for Dielectric Lyophilization). This system integrates a multi-index mathematical model, a firmware with real-time self-tuning, and an intelligent encapsulating formulation device, designed to produce biofunctional capsules with controlled release, high structural stability, and cryptographic traceability.

TF-LIO transforms the physicochemical principles of encapsulation into a digital, self-adaptive, and scalable platform that reduces experimental testing, improves industrial reproducibility, and enables customized design of delivery systems.

2. Functional architecture of the TF-LIO system

The TF-LIO system is composed of the following modules:

•Input sensors: Capacitive sensors connected by I2C/SPI that capture key environmental variables in real time (pH: 5.5-8.5; temperature: 20-45°C; salinity: 20-45%o).

•Central processing unit: ARM Cortex-M4 microcontroller with embedded firmware, operating on deterministic RTOS, optimized for calculating dielectric indices and performing structural adjustments.

• Simulation-assisted reverse design module: Optimization engine that, starting from a target release profile, backward calculates the ideal encapsulation parameters using dielectric and kinetic simulations.

•Dielectric self-adjustment: Algorithm that corrects deviations in IEL, K_p and q_mtx in cycles of 0.42 seconds, ensuring operational robustness and replicability.

•Dielectric lyophilization module: Final manufacturing phase that stabilizes the capsule in a dry state with the possibility of double lyophilization for targeted aptamers.

3. Multi-index mathematical model

TF-LIO is based on five interrelated functional indices:

•aLIO: Dielectric capacity of the matrix. Values > 0.9 ensure stable support of the bioactive load.

•Sbio: Bioactive-matrix dielectric compatibility. Values > 2.2 predict retention > 94% at 180 days.

•AG_encap: Encapsulation free energy. Guaranteed stability if < -35 kJ/mol (ideal: -42.3 ± 1.5 kJ/mol).

•IEL: System dielectric efficiency. Values > 120 ± 5 reflect optimal encapsulation.

•Rlib(t): Functional release rate as a function of time. It is considered ideal if Rlib < 18.2% in 240 h at pH 8.2.

These parameters are obtained by validated computer simulation and LCR dielectric cell.

4. Firmware and adaptive control

The firmware is developed in C language on RTOS and allows:

• Continuous reading of environmental variables.

• Calculation and monitoring of functional indices.

• Real-time dielectric self-adjustment (< 0.5 s per cycle).

• Secure data recording using SHA-256 algorithm with the possibility of integration into blockchain.

5. Simulation-assisted reverse design module

This module is the core of TF-LIO's predictive intelligence.

It operates in five phases:

1. Input conditions: Rlib_target profile, environmental conditions (pH, T, salinity), material constraints (matrix, n_max, K_p_min).

2. Generation of formulations: Initial stochastic or heuristic sampling.

3. Dielectric and kinetic simulation: Application of the IEL-AG_encap-Rlib(t) model. 4. Multi-objective optimization: Genetic, Bayesian, or backpropagation network algorithms to adjust dielectric strength (k), effective diffusion (D_eff), and osmotic compression (P).

5. Convergence: Ends when £ < 0.05 or the maximum number of iterations is reached.

6. Capsule Manufacturing Process

The TF-LIO system allows the manufacture of biofunctional capsules through:

1. Matrix preparation: Controlled dissolution of biopolymers (chitosan, trehalose, hyaluronic acid) and bioactive loading.

2. Parameter adjustment: Measurement and correction of pH, K_p and n_mtx.

3. Dielectric lyophilization: Dielectric freezing and drying in one or two phases.

4. Functional rehydration: Post-rehydration evaluation of bioactive, K_p and Rlib(t). 5. Packaging and traceability: Blisters with inert atmosphere, cryptographic audit, stability tests (ISO 17025).

7. Validated technical results

• Functional retention: > 94% at 180 days (HPLC-UV).

• Controlled release: Rlib(t) = 18.2 ± 0.5% in 240 h at pH 8.2.

• Dielectric efficiency: IEL > 120 ± 5.

• Predictive accuracy: > 95% ISO 20638 validation.

• Energy efficiency: 12 ± 1 kWh/kg.

• Cost reduction: up to €1,500/ton compared to €5,000/ton for liposomes.

8. Multisectoral applications

TF-LIO is suitable for:

• Aquaculture: Release of bioactive supplements resistant to the gastrointestinal tract.

•Pharmacology: Transport of peptides, enzymes, mRNA or aptamers.

•Cosmetics: Vehicle for lipophilic antioxidants and polyphenols.

•Precision agriculture: Encapsulated biofertilizers with kinetics adjusted to the soil type.

•Bioprinting: Functional microspheres with controlled structural response.

•Clean-label and functional beverages: Non-synthetic and customizable gradual-release systems.

Field of invention

The present invention relates to a predictive system for the functional encapsulation of bioactive compounds, based on multi-index computational simulation and automatic control by means of embedded firmware, designed to preserve stability, modulate release and improve traceability of active ingredients in complex physiological or environmental settings.

It belongs to the technical field of advanced encapsulation assisted by dielectric lyophilization, with special application in the formulation of functional capsules with controlled, enteric or directed release, applicable in sectors that demand high structural efficiency, functional adaptability and strict regulatory compliance.

The invention integrates predictive dielectric models (aLIO, Sbio, AG_encap, IEL, Rlib) with a real-time self-tuning system managed by embedded firmware in ARM Cortex-M4 architecture, with SHA-256 cryptographic traceability, avoiding the need for preliminary in vivo tests and allowing computational validation in accordance with ISO 20638:2018.

International Patent Classification (IPC)

■A23K 20/163- Animal feed compositions with functional active ingredients or medicines.

■A61K 9/50- Controlled or sustained release pharmaceutical preparations.

■A01N 25/28- Microcapsules with active ingredient release for agricultural use. ■B82Y 30/00- Nanotechnology applications in medicine, biotechnology or cosmetics.

■A61K 47/69- Vehicle using polysaccharides such as chitosan, hyaluronate or other biopolymers.

■C07K 7/00- Functional peptides and low molecular weight bioactive compounds. (Future protection with aptamers or other targeted ligands).

Industrial sectors of application

■Aquaculture: Functional capsules for enteric release of nutrients and antioxidants in marine species.

■Pharmacology and biomedicine: Encapsulation of GRAS or biotherapeutic compounds for sustained or targeted release in specific tissues.

■Agriculture: Formulation of biofertilizers or phytonutrients for optimized release in saline, alkaline or degraded soils.

■Cosmetics: Stable vehicle for antioxidants, topical actives or cosmeceutical peptides sensitive to pH or temperature.

■Bioprinting and biotechnology: Functional nanocapsules for cell cultures, grafts, biofabrication matrices or personalized medicine.

■Clean label functional beverages: Vehicle for sensitive natural compounds (e.g., vitamin C, flavonoids, probiotics) with controlled release in the gastrointestinal tract, without synthetic additives.

The invention is adapted to physiological operating ranges (pH 5.5-8.5; salinity 20-45%; temperature 20-45°C), and is ready for industrial scaling in accordance with international regulations: EFSA (QPS), FDA (GRAS), EMA (ICH Q8), and Regulation (EU) 2021/1379. Its modular design, predictive capacity, and low environmental impact position it as a versatile, scalable, and highly innovative encapsulation technology.

Technical problems solved by the invention

The present invention solves a number of persistent technical problems in conventional encapsulation systems used in biotechnology, materials engineering, applied chemistry, pharmaceutical technologies, food science, and targeted release of bioactive compounds. The TF-LIO system introduces an integrated and predictive approach that overcomes structural, kinetic, computational, and regulatory limitations through a multi-index dielectric model, reverse design from target conditions, and embedded firmware with active self-tuning.

1. Dielectric instability of the encapsulating matrix

•Technical problem: Current encapsulating matrices do not allow control of their dielectric properties in the face of environmental variations such as pH, temperature, salinity or pressure, which leads to structural degradation, leakage of the active compound and loss of functionality.

•Solution provided by TF-LIO: Implementation of a multi-index dielectric computational model (Sbio, IEL, AG_encap) that evaluates the physical conditions of the capsule in real time. The system, governed by ARM firmware, activates automatic adjustments to critical parameters such as effective viscosity (nmtx), dielectric conductivity (Kp), and glass transition temperature (Tg).

•Technical effect obtained: Functional stability of the active compound equal to or greater than 94% for 180 days, with losses of less than 6% under thermal and saline stress conditions. It exceeds the average stability of conventional formulations by more than 5 times.

2. Uncontrolled release of the active compound

•Technical problem: Traditional encapsulation systems have erratic, excessively fast or non-adaptable release profiles to the application environment, which compromises therapeutic, functional or agronomic efficacy.

•Solution provided by TF-LIO: The multi-index dielectric model regulates the Rlib(t) function, modeling the release kinetics through the dynamic equilibrium between AG_encap and IEL. The system allows programming the desired profile from the design phase and validating it through simulation according to the iS 20638:2018 standard.

•Technical effect obtained: Progressive and controlled release of 18.2 ± 0.5% in 240 hours, with programmable sequences of latency, activation and saturation, adjustable to multiple physicochemical conditions.

3. Lack of computational self-adjustment

•Technical problem: Current technologies lack autonomous control mechanisms that adjust the encapsulation process in response to external fluctuations or functional deviations during manufacturing or storage.

•Solution provided by TF-LIO: The embedded firmware executes a deterministic control loop and automatic recalibration of dielectric parameters. In the event of deviations from the IEL index, a sequence of up to three self-adjustment cycles is activated.

•Technical effect obtained: Adaptive response with latency less than 0.5 seconds per cycle, maintaining the IEL within the target range (>120 ± 5) and ensuring structural quality without manual intervention.

4. Dependence on empirical trials in early phases

•Technical problem: Validation of functional capsules often requires extensive in vivo or in vitro trials, which are costly and ethically problematic, delaying innovation and increasing technical and economic risk.

•Solution provided by TF-LIO: The computational predictive model allows capsules to be designed directly from the target physiological or environmental conditions, avoiding preliminary empirical validations. The simulations offer >95% agreement with theoretical data.

•Technical effect obtained: Drastic reduction of in vivo/in vitro tests in initial stages, acceleration of technical-regulatory development, and improvement of the sustainability of the process.

5. Lack of specific adaptation to the application environment

•Technical problem: Conventional capsules are not formulated to adapt to specific environments such as gastric mucosa, skin, gills, saline soils or cell culture media, resulting in physicochemical incompatibility, ineffective release and loss of functionality.

•Solution provided by TF-LIO: A reverse design module is integrated, which starts from the target values of pH, T, zeta potential (Z) and salinity to generate an encapsulating formulation with optimized indices (Sbio, AG_encap, IEL) for the intended environment.

•Technical effect achieved: Capsule formulation precisely adapted to the target tissue or environment, with effective functional release, without the need for subsequent reformulations. Applicable to demanding sectors such as personalized medicine, cell culture, or precision nutrition.

State-of-the-art report and comparative analysis of the TF-LIO system

1. Introduction

The encapsulation of sensitive bioactives is a critical challenge in industries such as aquaculture, pharmaceuticals, agriculture, cosmetics, and bioengineering. These compounds, susceptible to degradation by environmental factors such as pH (5.5–8.5), salinity (20–45), and temperature (20–45°C), require encapsulation systems that guarantee stability and controlled release. Current technologies have significant limitations, including high degradation (>30% in 90 days), a lack of robust predictive models for the release rate (Rlib(t)), dependence on costly in vivo assays, and the absence of reverse design from physiological conditions. The TF-LIO (Thermodynamic-Electromechanical for Dielectric Lyophilization) system addresses these shortcomings with a predictive multi-index model, real-time dielectric self-adjustment, implementation in ARM firmware with cryptographic traceability, and functional retention exceeding 94% at 180 days, applicable to a wide range of bioactives.

This chapter analyzes the relevant state of the art, comparing the TF-LIO system with previous technologies to highlight its novelty, inventive step and industrial applicability, in compliance with Articles 4 and 19 of Law 24/2015. The analysis focuses on the encapsulation of bioactives in general, with vitamin C as a representative application example.

2. Relevant state of the art

The state of the art in bioactive encapsulation includes several patents and technologies that address aspects of encapsulation, but none achieve the integration, predictability, and stability offered by TF-LIO. The key references identified are described below:

•WO2018011197A1 (2018): Describes an alginate-based encapsulation technology for bioactives. It features a high release rate (>95% in 2 hours at pH 8.2) and significant stability loss (>30% in 90 days). It does not incorporate a multi-index predictive model, dielectric self-tuning, or cryptographic traceability, limiting its control over release and stability in extreme environments.

•US20160206025A1 (2016): Focuses on the encapsulation of bioactives, but lacks an integrated predictive model that considers thermodynamic and dielectric factors. Its release rate is rapid (>90% in 3 hours), and it does not offer reverse design or real-time control, reducing its accuracy and adaptability.

•WO2020034760A1 (2020): Mentions predictive models for encapsulation, but does not include dielectric control or real-time self-tuning. Its release is less controlled (80% in 5 hours), and it does not address reverse design or cryptographic traceability, limiting its applicability in regulated environments.

•CN105124882A (2015): Describes a partial dielectric encapsulation, but without dynamic self-tuning or reverse design. Its lack of an integrated predictive system limits optimization under variable conditions.

•KR101587564B1 (2016): Addresses ionic degradation in encapsulation, but does not incorporate reverse design or dielectric self-tuning. Its approach is limited and does not allow for predictability or adaptability of the TF-LIO system.

None of these references combine a predictive multi-index model, dielectric self-tuning, reverse design from physiological conditions, or cryptographic traceability, which constitutes a technological gap that TF-LIO fills in an innovative way.

3. Comparative analysis

The TF-LIO system stands out by overcoming the limitations of the prior art, offering significant improvements in stability, predictability, release control, and cost-effectiveness for a wide range of bioactives. Table 1 provides a direct comparison of key parameters, using general metrics applicable to sensitive bioactives:

3.1. Comparison with WO2018011197A1

WO2018011197A1 exhibits uncontrolled release (>95% in 2 hours) and limited stability (loss >30% in 90 days) for encapsulated bioactives. In contrast, TF-LIO achieves controlled release (18.2% in 240 hours) and 94% retention at 180 days, thanks to its multi-index model (Sbio, IEL, AGencap, Rlib(t)) and dielectric self-tuning. The lack of firmware and cryptographic traceability in WO2018011197A1 limits its ability to dynamically optimize encapsulation.

3.2. Comparison with US20160206025A1 and WO2020034760A1

US20160206025A1 lacks a multi-index predictive model, resulting in rapid release (>90% in 3 hours) and low stability (20 days at 40°C). WO2020034760A1, while mentioning predictive models, does not include dielectric control, showing 80% release in 5 hours and limited stability (60 days). TFLIO, with its real-time self-tuning and reverse design, overcomes these limitations, offering precise release and extended stability for various bioactives.

3.3. Comparison with CN105124882A and KR101587564B1

CN105124882A implements partial dielectric encapsulation, but without self-adjustment or reverse design, which restricts its adaptability.

KR101587564B1 addresses ionic degradation, but does not allow for design based on physiological conditions or dynamic control. TF-LIO integrates these capabilities, achieving a more robust and versatile solution applicable to multiple bioactives.

4. Unique features of TF-LIO

The TF-LIO system introduces innovations not present in the state of the art, applicable to a wide range of sensitive bioactives:

•Real-Time Dielectric Auto-Adjustment: The ARM firmware dynamically adjusts parameters such as dielectric conductivity (Kp: 2.2-2.5 S/m), effective viscosity (nmtx: 0.8-1.2 Pas), and glass transition temperature (Tg: 69-75°C), based on IEL thresholds (>120 ± 5), optimizing encapsulation in 0.42 seconds per cycle.

•Integrated Multi-Index Model: The interrelationship of Sbio (compatibility, >2.2), AGencap (thermodynamic stability, <-42.3 ± 1.5 kJ/mol), IEL (dielectric efficiency), and Rlib(t) (release rate, 18.2% in 240 h) allows for a comprehensive predictive design.

•Reverse Design from Physiological Conditions: Allows formulation of capsules from specific requirements (pH 5.5-8.5, salinity 20-45, T 20-45°C), eliminating initial in vivo tests, with a correlation >95% in simulations (ISO 20638:2018).

•Cryptographic Traceability: The integration of SHA256 ensures data integrity and verification, a key differentiator in regulated industries.

•Quantitative Efficiency: Retention >94% at 180 days, cost of €1500/ton (vs.

5000 €/ton liposomal), and energy efficiency of 12 ± 1 kWh/kg.

5. Conclusion

The prior art analysis demonstrates that the TF-LIO system is novel and exhibits inventive activity by overcoming the limitations of existing technologies for encapsulating sensitive bioactives. No other reference combines a multi-index model, dielectric self-tuning, reverse design, and cryptographic traceability, positioning TF-LIO as a superior technical solution. Its ability to achieve 94% functional retention at 180 days, 18.2% controlled release in 240 hours, and a significantly lower production cost (€1,500/ton vs. €5,000/ton for liposomal encapsulation) highlights its competitive advantage.

Furthermore, its compliance with international regulations (EU Regulation 2021/1379, EFSA QPS, FDA GRAS, EMA ICH Q8) and its applicability in sectors such as aquaculture, pharmaceuticals, agriculture, cosmetics, and bioengineering reinforce its industrial potential. Therefore, TF-LIO meets patentability requirements and represents a significant advancement in the encapsulation of sensitive bioactives.

Claims (18)

1. Predictive method for functional encapsulation of bioactive compounds, characterized by integrating a multi-index dielectric computational model and a reverse design approach, comprising: • the calculation of a set of interrelated functional indices, selected from: dielectric capacity index of the matrix (aLIO > 0.9), Dielectric compatibility index of the bioactive (Sbio > 2.2), encapsulation free energy (AG_encap < -35 kJ/mol), dielectric efficiency index (IEL > 120 ± 5), functional release rate (Rlib(t) < 18.2% in 240 h at pH 8.2); • Numerical simulation of the structural and kinetic behavior of the capsule under specific physiological or environmental conditions, including: opH between 5.5 and 8.5, osalination between 20 and 45% or temperature between 20 °C and 45 °C, oy zeta potential (Z) of -15 ± 5 mV; • the automated generation of an optimized encapsulating formulation, with: effective oviscosity (nmtx) between 0.8 and 1.2 PaS, oy dielectric conductivity (Kp) between 2.2 and 2.5 S/m; • the execution of the process using firmware embedded in ARM Cortex-M4 architecture, with cryptographic traceability using the SHA-256 algorithm and real-time dielectric self-adjustment capability; • and a dielectric freeze-drying process to stabilize the matrix and the bioactive, with the possibility of double freeze-drying for incorporation of targeted aptamers. All dielectric parameters are defined according to LCR cell measurements and validated computer simulations. 2. Method according to claim 1, applicable to physiological environments selected from: gastric mucosa, skin, gills, saline soils or cell cultures, dynamically adapting the pH, salinity and temperature parameters to the target medium. 3. Method according to any of claims 1 or 2, wherein ascorbic acid is used as a model compound, obtaining a release rate Rlib(t) < 18.2% at 240 days and a functional retention > 94% at 180 days. 4. Method according to any of claims 1 to 3, wherein the release profile is programmed in three sequential phases: initial latency, controlled activation and terminal saturation, regulated by the dielectric function Rlib(t), with a maximum release rate (Rmax) between 4 and 6 mg/h. 5. Method according to any of the preceding claims, wherein the firmware executes a real-time dielectric self-tuning loop, with: • a response latency of less than 0.5 seconds per cycle, • a maximum of three adjustment cycles for deviations greater than ±5 units in the IEL index, • and, if the deviation persists after the third cycle, the system activates a contingency protocol that includes: or interruption of the process, or cryptographic record of the event, or and issuance of operational alerts via graphical interface remote communication. 6. Method according to any of claims 1 to 5, wherein the functional indices (Sbio, ΔG_encap, IEL) are used as predictors of structural stability, release kinetics and encapsulating efficiency, with validation by simulation in accordance with ISO 20638:2018. 7. Method according to any of claims 1 to 6, applicable to formulations intended for: •aquaculture, with improvement of the specific growth rate (SGR > 2.45%/day) and reduction of post-hypoxic mortality (< 12%); •pharmacology, including GRAS-compliant compounds; •agriculture, through functional biofertilizers; •cosmetics, with topical antioxidants; • Bioprinting and clean-label functional beverages. 8. Method according to any of claims 1 to 7, wherein the performance of in vivo tests is replaced by dielectric simulations validated with an accuracy equal to or greater than 95%, in accordance with ISO 20638:2018. 9. Method according to any of claims 1 to 8, wherein recycled biopolymers are used in the encapsulating formulation, selected from: •chitosan (45% w/w), •trehalose (25%), • hyaluronic acid (5%), in accordance with the environmental standard ISO 14040:2006. 10. Intelligent functional encapsulation device, characterized by incorporating: • an ARM Cortex-M4 microcontroller with embedded firmware capable of running real-time dielectric simulations; • Cryptographic traceability using the SHA-256 algorithm; • capacitive sensors connected via I2C/SPI interface; • a dielectric cell equipped with an LCR meter for analysis of dielectric parameters (nmtx, Kp, Tg, IEL); • and adaptive control capability of the encapsulating formulation through computational self-tuning loops. 11. Device according to claim 10, characterized by incorporating cryptographic traceability using the SHA-256 algorithm, with auditing capability and secure storage of dielectric data. 12. Device according to claim 10 or 11, wherein the firmware enables encrypted bidirectional communication using updated industry protocols (e.g., TLS 1.3 or AES-256), implemented in an integrated stack. 13. Encapsulating composition obtained by the method according to any of claims 1 to 9, comprising: • chitosan (45% w/w), • trehalose (25%), • hyaluronic acid (5%), • and a bioactive ingredient selected from vitamins, polyphenols, peptides, enzymes, aptamers or mRNA. 14. Use of the composition according to claim 13 for the formulation of clean-label functional beverages, with controlled enteric release of the bioactive. 15. Method according to any of claims 1 to 14, characterized by being adapted to operate under extended pH conditions between 2.0 and 10.0 and temperature between 5 °C and 80 °C, by adjusting the encapsulating formulation and recalibrating the computational model dielectric, with structural and kinetic validation by numerical simulation in accordance with ISO 20638:2018. 16. Method according to any of claims 1 to 15, wherein the system firmware incorporates self-learning algorithms that dynamically estimate the osmotic parameters ($_osm), compression (P) and dielectric strength (k), based on operating conditions and usage history, allowing adaptive recalibration of the release model. 17. Method according to any of claims 1 to 16, wherein the encapsulating formulation is configured by pre-established profiles for polymer matrices selected from alginate, PLGA or cellulose, depending on the desired application, with adjustment of the effective viscosity (qmtx) and the release index (Rlib) according to the target environment. 18. Computational algorithm for reverse design for the configuration of intelligent release systems, characterized by receiving as input a desired release profile (Rlib_target), expected environmental conditions (pH, temperature, humidity) and material constraints (matrix type, viscosity, payload), and generating as output an optimized encapsulant formulation and a set of dielectric and osmotic parameters (k, $_osm, P) that satisfy said profile through iterative simulation and multi-objective adjustment.