Mobile Health Record Analysis for Genomic Therapy Matching
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Solution Overview
Problem
Current medical records, such as EHRs and EMRs, lack comprehensive integration of patient genetic information and genomic data, leading to limited physician decision-making capabilities, especially in cancer treatment, due to unstructured data and lack of standardized genomic datasets from next-generation sequencing providers.
Innovation Solution
A mobile computing device system that displays summarized medical information, including molecular data, and connects to a cloud server for bioinformatics analysis to identify therapy recommendations, updating the display with clinical trial data for improved cancer treatment decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If physicians rely on traditional EHR/EMR systems, then historical patient status information is available, but comprehensive genomic data integration and real-time therapy identification are limited
Solution Approach 1:
The patent introduces a mobile computing device as an intermediary between traditional EHR systems and genomic data sources. This device integrates multiple data types (clinical history, molecular profiles, genomic sequences) and provides a unified interface for physicians, eliminating the need for direct complex integration between disparate systems while ensuring comprehensive information access.
Solution Approach 2:
The system implements a nested architecture where the mobile computing device contains multiple integrated functional layers: patient identification module, molecular data storage, genomic analysis capabilities, and therapy recommendation engine. Each layer is embedded within the previous one, allowing comprehensive genomic data integration while maintaining a compact, manageable system structure.
2Measurement precision
If comprehensive molecular data is integrated into the mobile device, then therapy identification accuracy improves, but device memory and processing requirements increase
Solution Approach 1:
The system extracts and stores only the most clinically relevant molecular data elements in the mobile device's structured database, such as key genomic mutations, gene expressions, and molecular profiles directly related to cancer therapy selection. Less critical raw sequencing data is processed externally or stored in condensed formats, reducing storage requirements while maintaining diagnostic accuracy.
Solution Approach 2:
The patent transforms raw genomic sequencing data into standardized molecular parameters and structured formats suitable for mobile device storage. By converting unstructured sequence data into discrete molecular profiles with defined parameters (mutation types, expression levels, pathway activations), the system achieves high therapy identification accuracy while optimizing data storage efficiency.
3Productivity
If real-time bioinformatics analysis is performed, then clinical trial matching speed improves, but computational resource requirements increase
Solution Approach 1:
The bioinformatics analysis process is segmented into distinct functional modules within the mobile device: data preprocessing, molecular profile generation, clinical trial matching, and recommendation generation. Each module operates independently with optimized computational requirements, allowing real-time analysis while managing processing power consumption through modular execution.
Data Source
AI summary
A method includes displaying a cohort report; receiving a request to determine a therapy identification; causing information to be transmitted to a remote cloud server; receiving clinical trial data; and updating the cohort report. A computing system includes a processor; and a memory having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to: display a cohort report; receive a request to determine a therapy identification; cause information to be transmitted to a remote cloud server; receive clinical trial data; and update the cohort report. A computer-readable medium having stored thereon a set of computer-executable instructions that, when executed by one or more processors, cause a computer to: display a cohort report; receive a request to determine a therapy identification; cause information to be transmitted to a remote cloud server; receive clinical trial data; and update the cohort report.