Adaptive Therapeutic Guidance System for Dynamic Dosing
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Solution Overview
Problem
Current devices fail to provide real-time, dynamic assistance in adhering to therapeutic treatment regimens, as they offer static information based on past effects and do not account for individual variability in drug absorption and adherence, leading to suboptimal dosing and increased risk of under- or overdosing.
Innovation Solution
A system that uses an electronic monitoring device to record and analyze indicative data on medication taking or treatment acts, calculating a corrected data model that considers actual dosing and adherence patterns to provide personalized, real-time guidance on optimal treatment timing and dosing intervals, ensuring the therapeutic effect remains within a safe and effective window.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static information based on past effects is provided, then device complexity is reduced, but measurement precision and reliability of therapeutic guidance deteriorate
Solution Approach 1:
The system transitions from static information provision to dynamic real-time monitoring and adjustment of therapeutic treatment. The system continuously receives actual taking data, updates the data model accordingly, and provides dynamic guidance that adapts to individual patient behavior patterns, thereby improving measurement precision without requiring overly complex device architecture.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where actual medication taking data is continuously monitored, compared against the data model, and used to update future guidance. This feedback loop enables the system to learn from patient behavior patterns and adjust recommendations in real-time, enhancing reliability while maintaining manageable device complexity through algorithmic processing.
2Ease of operation
If static information based on past effects is provided, then ease of operation is improved, but reliability of therapeutic adherence assistance deteriorates
Solution Approach 1:
The system enables patients to self-monitor their medication taking behavior through simple interactions, automatically recording actual taking data and comparing it against personalized guidance. The system serves itself by continuously updating the data model based on accumulated patient data, reducing the need for complex manual interventions while improving reliability through automated adaptive learning.
3Device complexity
If individual variability in drug absorption and adherence is not accounted for, then device complexity is reduced, but manufacturing precision of personalized treatment guidance deteriorates
Solution Approach 1:
The system provides localized personalized treatment guidance tailored to each patient's specific absorption characteristics and adherence patterns. By maintaining a data model that captures individual variability and updating it with patient-specific actual taking data, the system delivers precision treatment guidance without requiring complex hardware modifications for each patient.
Solution Approach 2:
The system dynamically adjusts treatment guidance parameters based on individual patient data, including absorption rates, adherence patterns, and actual taking behavior. By modifying the data model parameters to reflect individual variability, the system achieves precision personalization of treatment guidance while maintaining a unified device architecture that handles diverse patient profiles.
4Reliability
If real-time dynamic assistance is provided, then reliability of therapeutic adherence improves, but device complexity increases
Solution Approach 1:
The system implements a universal platform that handles multiple functions: receiving actual taking data, updating the data model, calculating therapeutic treatment guidance, and providing real-time feedback. By consolidating these functions into a single integrated system with a adaptable data model, the system achieves high reliability for therapeutic adherence assistance while avoiding the need for multiple separate complex devices.
Data Source
AI summary
The present invention relates to the assistance of the taking or the act of a therapeutic treatment for an individual Ii, to a system (1) and to a computer program product for implementing same.