Data Integration System for Precision Medicine

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Solution Overview

Problem

Current healthcare data systems face challenges in accessing and analyzing heterogeneous, siloed biomedical data due to incompatible file formats, technical architectures, and security protocols, making it difficult to form cohesive cohorts for precision medicine applications.

Innovation Solution

The system integrates data from various sources by creating data source objects and data pools, using a data integration schema that supports declarative queries across disparate data sources, enabling transformation and analysis of biomedical data for diagnostic and treatment purposes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If data from multiple disparate sources are integrated for precision medicine, then the ability to tailor treatment strategies is improved, but the system complexity and difficulty of data access increase

Engineering Contradiction:

Improveability to tailor treatment strategiesVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary layer (data integration system with standardized schemas and APIs) that mediates between disparate data sources and the precision medicine analysis tools. This intermediary handles format conversion, data normalization, and access coordination, allowing treatment personalization without exposing the underlying complexity of multiple proprietary systems

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements a universal data integration platform that can interface with multiple different data sources (EHR systems, genomic databases, imaging systems) through common standardized protocols. This multi-functional interface layer enables the same precision medicine tools to work with diverse data types without requiring separate integration solutions for each source

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Loss of information

If data from multiple locations and formats are collected for cohort analysis, then the comprehensiveness of patient profiles is improved, but the time and effort required for data collection increase

Engineering Contradiction:

Improvecomprehensiveness of patient profilesVSAvoidtime for data collection

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system performs preliminary data normalization and standardization during the data ingestion phase, converting diverse formats into a unified schema before storage. This preliminary processing eliminates the need for time-consuming manual data reconciliation during cohort analysis, as data is already prepared in a consistent format ready for immediate use

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates standardized data copies and representations of patient information across multiple sources, maintaining a unified view of patient profiles. Rather than accessing and reconciling original disparate data sources during analysis, the system queries pre-integrated data copies that already contain normalized information from all sources

Inventive Principle:

Principle #26Copying

3Reliability

If manual data sharing and compilation between silos is performed, then data security requirements can be maintained, but the productivity of cohort identification decreases

Engineering Contradiction:

Improvedata securityVSAvoidcohort identification speed

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system introduces an intermediary data integration layer that handles secure data exchange between silos automatically. This intermediary enforces access controls, authentication, and authorization policies while managing data transfer, eliminating the need for manual security verification processes and enabling automated cohort identification that maintains security requirements

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system replaces manual data compilation processes with automated computational systems that perform data retrieval, integration, and cohort identification through programmed algorithms. This substitution of mechanical manual operations with automated electronic processes maintains security through systematic access control while dramatically increasing productivity in cohort identification

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Adaptability or versatility

If disparate storage systems with different access requirements are used, then data source independence is maintained, but the ease of accessing and analyzing data decreases

Engineering Contradiction:

Improvedata source independenceVSAvoidease of data access

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system segments the data access architecture into distinct layers: source-specific access modules that handle individual data source protocols, a normalization layer that unifies data formats, and a universal query interface that provides consistent access. This segmentation allows each data source to maintain its independence and access requirements while presenting a unified ease of use to end users

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11727010B2System and method for integrating data for precision medicine

Publication Date: 2023.08.15 DATMA INC

AI summary

Methods and systems are provided for a platform and language agnostic method for generating inter-and intra-data type aggregations of heterogeneous disparate data upon which various operations can be performed without altering the structure of the query or resulting distributed data set representation to account for which specific data sources are included in the query.