Virtual Patient Biomarker Analysis for Confidential Clinical Trials
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Solution Overview
Problem
The limited availability of original clinical trial data due to confidentiality concerns hinders the retrospective analysis of biomarkers, making it difficult to provide clear guidance on optimal treatment regimes for patients.
Innovation Solution
A method and apparatus that utilize hypothetical analysis to generate virtual patient data and classify them as responders or non-responders based on pre-generated survival data, combined with actual patient data from medical images, to compare and output results that guide treatment selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If original clinical trial data is used for biomarker analysis, then the analysis reliability is improved, but data confidentiality and patient privacy are compromised
Solution Approach 1:
The patent creates virtual patient data that copies the statistical characteristics and patterns of real clinical trial data without using actual patient information. Virtual patients are generated with synthetic survival data, medical images, and clinical parameters that replicate the distribution and relationships found in real data, enabling biomarker analysis while maintaining complete patient privacy and data confidentiality.
Solution Approach 2:
The patent introduces virtual patient data as an intermediary between real clinical trial data and biomarker analysis. Instead of directly analyzing sensitive real patient data, the system uses virtual data as a mediator that preserves the statistical properties needed for analysis while eliminating all identifiable patient information, thus resolving the conflict between analysis reliability and data confidentiality.
2Object-affected harmful factors
If virtual patient data is generated instead of using real data, then data confidentiality is maintained, but the quantity of available data for analysis is reduced
Solution Approach 1:
The patent performs preliminary actions by generating comprehensive virtual patient data sets before conducting biomarker analysis. The system pre-generates virtual patients with complete clinical parameters, medical images, survival outcomes, and treatment responses, ensuring sufficient data quantity is available for robust statistical analysis while maintaining data confidentiality from the outset.
Solution Approach 2:
The virtual data generation process creates synthetic patient records that copy the volume, structure, and statistical properties of real clinical trial data. By replicating the data quantity and diversity characteristics of original studies, the system ensures that virtual data provides sufficient statistical power for biomarker analysis without requiring access to actual patient information.
3Quantity of substance
If hypothetical analysis with virtual data is performed, then data availability is improved, but the complexity of the analysis method increases
Solution Approach 1:
The patent segments the complex analysis process into distinct modules: virtual patient generation, data set creation, biomarker extraction from medical images, and comparative analysis. Each module handles a specific aspect of the analysis independently, making the overall complex process more manageable and systematic while improving data availability through virtual patient populations.
Data Source
AI summary
A computing device includes a memory storing at least one program, and a processor configured to perform at least one operation by executing the at least one program, wherein the processor is configured to generate virtual data including information about survival rates of virtual patients included in a first group, based on pre-generated survival data, generate control group data by classifying each of the virtual patients as a responder or a non-responder according to a certain criterion, generate experimental group data based on at least one of medical images and survival data of actual patients included in a second group to which a specific regime has been applied, and output a result of comparison between the control group data and the experimental group data.


