Biomarker Configuration Profiles for Adaptive Therapeutic Plans
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Solution Overview
Problem
Current bioinformatic data systems are inefficient due to the collection and processing of unnecessary data, which consumes resources and fails to tailor therapeutic plans to individual user needs, lacking the ability to learn and apply personalized health insights effectively.
Innovation Solution
A system that dynamically adapts and displays personalized therapeutic plans by using biomarker configuration profiles to select relevant data sources, generate biomarkers, and update therapeutic plans based on user-specific bioinformatic data, optimizing data processing and reducing unnecessary data collection and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If current systems collect all information related to the user, then comprehensive data is available for analysis, but processing efficiency decreases and network bandwidth is wasted
Solution Approach 1:
The system extracts and processes only the specific biomarker data relevant to the therapeutic plan, separating useful information from unnecessary data. The biomarker configuration profiles define precisely which data sources and parameters are needed, eliminating the collection of all user information while maintaining the ability to generate accurate therapeutic recommendations.
Solution Approach 2:
Different data sources are configured with different levels of precision and collection frequency based on their relevance to specific therapeutic plans. The system applies local quality control by adjusting data collection parameters according to the specific biomarker requirements of each therapeutic configuration, rather than uniformly collecting all data at maximum precision.
2Reliability
If current systems process all collected data, then complete analysis is possible, but power consumption and processing time increase
Solution Approach 1:
The system extracts only the essential biomarker parameters needed for therapeutic analysis, avoiding processing of unnecessary data. The biomarker configuration profiles specify exactly which data elements require processing, enabling complete analysis of relevant markers while eliminating power consumption associated with processing irrelevant information.
Solution Approach 2:
The system performs partial processing by focusing computational resources only on the subset of data that is clinically relevant to the therapeutic plan. Rather than processing all collected data exhaustively, the system applies processing only where needed to generate the required biomarkers, reducing overall power consumption while maintaining analysis reliability.
3Loss of information
If current systems collect unnecessary data, then no data is missed, but network bandwidth is clogged with unnecessary communications
Solution Approach 1:
The system extracts and transmits only the biomarker data that is relevant to the therapeutic plan, eliminating unnecessary data communications. The biomarker configuration profiles define the precise data subset that needs to be collected and transmitted, preventing network bandwidth waste while ensuring no clinically relevant information is lost.
4Device complexity
If systems lack personalized therapeutic plans, then implementation is simpler, but treatment effectiveness for individual needs decreases
Solution Approach 1:
The system uses universal biomarker configuration profiles that can be applied across multiple therapeutic plans and user types. These profiles serve as reusable templates that define data collection and processing parameters, enabling the system to generate personalized therapeutic plans without requiring custom configurations for each case, thus balancing simplicity with personalization capability.
Solution Approach 2:
The system dynamically adapts the therapeutic plan based on the user's specific biomarker data and therapeutic configuration. The biomarker configuration profiles enable the system to flexibly adjust data collection parameters and therapeutic recommendations according to individual needs, providing personalization while maintaining a standardized underlying framework.
Data Source
AI summary
A system and method for an adjustable bio-stream self-selecting system. Through a plethora of inputs, the system associates therapeutic recipes and associated biomarker in a personalized approach to recommending an individual to a specific therapeutic program. Therapeutic programs operate in accordance with personalized inputs suggested by the user and through digital markers and biomarkers, which trigger new recommendations by “knowing” the individual. Each bio-stream contains information utilized within these biomarkers to trigger additional therapy recommendations. Because of the complexity of the plurality of inputs, these biomarkers are managed in a way that enables low latency detections, low bandwidth needs, low processing needs, and less battery needs. The pre-processing of these biomarkers helps additional therapy management and precision medicine across larger global population needs of the system.