Person-Centric Genomic Platform for Customized Gene Panel Design
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current gene panel testing is limited by inflexibility, financial constraints, and lack of user-centricity, often failing to incorporate medical and clinical guidelines, and may provide incomplete or unverified genetic information, especially for small biological sample sizes and rare variants.
Innovation Solution
A person-centric genomics platform that integrates personalized data repositories with knowledge bases to design and select customized gene panels based on individual user data, clinical guidelines, and insurance coverage, using machine learning and natural language processing to provide comprehensive and timely genetic insights for improved cancer management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pre-fabricated commercial gene panels are used, then testing can be performed with standard protocols, but flexibility in gene selection and customization is limited
Solution Approach 1:
The system dynamically generates customized gene panels based on individual patient data, clinical guidelines, and research literature. The panel composition is not fixed but adapts to each patient's specific genetic profile, cancer type, and treatment history, resolving the contradiction between standardization and customization flexibility
Solution Approach 2:
The system performs preliminary data aggregation from multiple sources (patient records, clinical guidelines, scientific literature) before gene panel selection. This pre-processing enables rapid customization without sacrificing thoroughness, allowing flexible gene selection while maintaining systematic rigor
2Loss of information
If comprehensive genetic testing is performed, then complete genetic information is obtained, but financial constraints and insurance coverage limitations are not adequately addressed
Solution Approach 1:
The system performs partial genetic testing by selecting only the most relevant genes for each patient based on their specific cancer type, genetic profile, and clinical context. This avoids unnecessary testing of genes not relevant to the patient's condition, reducing costs while maintaining information completeness for decision-making
Solution Approach 2:
The system incorporates feedback loops that continuously verify insurance coverage and adjust gene panel recommendations accordingly. It aggregates coverage information from multiple insurers and provides real-time feedback on cost implications, enabling comprehensive testing within financial constraints through iterative optimization
3Ease of operation
If genetic testing registry platforms track commercial and population factors, then test selection and comparison is facilitated, but user-centricity and independent verification are lacking
Solution Approach 1:
The system acts as an intermediary between patients, commercial testing platforms, and clinical guidelines. It independently aggregates and verifies data from multiple sources including scientific literature, clinical guidelines, and patient records, then synthesizes this information to provide personalized recommendations rather than simply comparing commercial offerings
Solution Approach 2:
The system performs multiple functions simultaneously: it aggregates patient data, searches clinical guidelines, analyzes scientific literature, verifies insurance coverage, and generates customized gene panels. This multi-functional approach ensures comprehensive data verification while maintaining ease of use through a unified platform
4Ease of operation
If consumer-based genetic testing services are used, then direct-to-consumer testing is available, but sample type limitations and mutation type coverage are restricted
Solution Approach 1:
The system segments the genetic testing process into distinct components: sample collection, DNA extraction, sequencing, and analysis. Each component can be independently optimized and selected based on patient needs and sample availability, allowing flexibility in sample types (saliva, blood, tissue) and mutation detection methods while maintaining consumer accessibility
Data Source
AI summary
Computer based methods, systems, and computer readable media for providing genomic services are provided. A request is received from a user. The request is applied to one or more from a group of a personalized data repository for the user and supporting knowledge bases, wherein the personalized data repository includes genetic test results, health/clinical information, and insurance coverage, and wherein the knowledge bases include information pertaining to genetic tests and clinical guidelines. Data from the applied request is integrated with results from service modules performing one or more from a group of content search, variation interpretation, and report generation to produce results for the request. The personalized data repository and supporting knowledge bases are updated based on the results of the request. Surveillance services are triggered based on one or more events.