Biological Simulation Model for Endocrine Diagnosis
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Solution Overview
Problem
Current methods for evaluating a patient's physiological condition are limited as they focus on symptomatic approaches rather than understanding the underlying physiological mechanisms and dysfunctions that contribute to disease, failing to consider the organism's overall functioning and its ability to respond to external or internal aggressions.
Innovation Solution
The development of a Biological Simulation Model that uses a set of indexes calculated from blood data to evaluate the physiological functioning of the organism, identifying pathological tendencies and imbalances, and providing a diagnostic assistant, Endobiogenic Medical Assistant (EMA™), to assist practitioners in clinical and physiological evaluations, recommending therapeutic actions and tracking patient progress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a symptomatic approach is used to evaluate patient condition, then the evaluation process is simple and quick, but the understanding of underlying physiological mechanisms and root causes is insufficient
Solution Approach 1:
The evaluation system is segmented into multiple functional modules: a data acquisition module that collects biological data from multiple sources, a simulation module that processes data through physiological models, and an analysis module that generates diagnostic insights. This segmentation allows comprehensive physiological analysis while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
A biological simulation model acts as an intermediary between raw biological data and clinical interpretation. The model translates complex physiological relationships into actionable diagnostic information, bridging the gap between detailed physiological mechanisms and practical clinical decision-making without requiring direct complex measurement of all physiological parameters.
2Measurement precision
If comprehensive biological data analysis is performed to identify root causes, then diagnostic accuracy improves, but processing time and computational resources increase
Solution Approach 1:
Physiological models and relationships are pre-computed and stored in the system before actual diagnostic use. When biological data is received, the system performs rapid matching against pre-established physiological patterns and simulations, significantly reducing processing time while maintaining comprehensive analysis capability for identifying root causes.
3Adaptability or versatility
If multiple biological parameters are measured to assess organism functioning, then the comprehensiveness of evaluation increases, but the complexity of data processing and interpretation increases
Solution Approach 1:
The biological simulation model serves multiple functions simultaneously: it integrates diverse biological parameters, simulates physiological processes, identifies pathological mechanisms, and generates diagnostic recommendations. This multi-functionality allows comprehensive evaluation of organism functioning using a single unified system rather than multiple separate analysis tools.
Data Source
AI summary
A method is provided that includes processing biological data using a biological simulation model, including calculating a set of measurements called indexes that measure interrelationships between hormones and/or blood test data; and analyzing from the indexes, the endocrine system by axis and in sequence along an adaptation process. The method includes running a selection algorithm from the indexes to identify biological dysfunctions across the endocrine system and the autonomous nervous system, and recommending corrective actions based on the identified biological dysfunctions. The method includes validating potential organism dysfunctions of the patient through the identified biological dysfunctions, consolidating diagnostic actions including the recommended corrective actions into a single diagnostic, and receiving selection of diagnostic actions therefrom. And the method includes assisting in selection of a therapeutic strategy applicable to each selected diagnostic action, and producing a final ready-to-use prescription with quantified dosage based thereon.