Clinical Trial Capacity Data Streaming via API Normalization
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Solution Overview
Problem
The complexity of finding qualified research centers, investigators, and managing clinical trial data poses significant challenges, including data privacy restrictions, diverse data formats, and the high cost and time required for planning clinical trials, which hinder the approval and accessibility of life-saving drugs.
Innovation Solution
A system and method that normalize and stream clinical trial capacity data from various sources, allowing for efficient querying and pre-qualification of assets such as research centers and investigators through an API, eliminating the need for a master database and enabling rapid drug development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a master database is built to store all clinical trial data, then data availability and accessibility are improved, but data privacy restrictions and security risks worsen
Solution Approach 1:
The patent extracts only the necessary normalized data fields from source databases and streams them through an API without creating a master database copy. This allows data access while minimizing data retention and reducing privacy risks associated with storing sensitive clinical trial information centrally.
Solution Approach 2:
The patent introduces an intermediary API layer that mediates between data sources and users. This API normalizes and formats data on-demand, allowing access to clinical trial information without requiring users to access raw databases, thus maintaining security and privacy controls while enabling data availability.
2Loss of information
If data from multiple sources is collected and stored, then data completeness is improved, but device complexity and data management burden worsen
Solution Approach 1:
The patent creates a universal data normalization layer that handles multiple data sources through a single API interface. This multi-functional approach allows the system to ingest, normalize, and provide access to data from various clinical trial sources without requiring separate management systems for each data type or source.
Solution Approach 2:
The patent transforms data from multiple source formats into a standardized normalized format through parameter transformation. By changing the data representation parameters during the normalization process, the system maintains data completeness from diverse sources while presenting a consistent, simplified data structure to users.
3Reliability
If clinical trial planning is done manually with thorough data review, then trial quality and reliability are improved, but time consumption and cost worsen
Solution Approach 1:
The patent performs preliminary data normalization and availability assessment through the API before trial planning begins. By pre-processing and organizing data from multiple sources in advance, the system enables trial planners to quickly access and review relevant information without time-consuming manual data collection and formatting during the planning process.
4Measurement precision
If a comprehensive search system is built to find qualified assets, then search accuracy is improved, but system complexity and maintenance requirements worsen
Solution Approach 1:
The patent creates a virtual copy of the data structure through the API interface rather than duplicating the actual data storage systems. This allows the search functionality to query normalized data representations without requiring complex indexing and storage infrastructure, maintaining search accuracy while reducing system complexity.
Data Source
AI summary
The invention generally relates to computer-based systems to evaluate and market clinical trial research centers. In certain aspects, the invention provides computer-based systems to collect information about clinical research centers. Systems include a tangible, non-transitory memory coupled to a processor operable to retrieve, based on a user's input, an identity of a clinical research center and prompt the user for information relating generally to the center. The system can collect disease-specific information by prompting the user for a selection of a disease and then collecting from the user information identifying an ability of the center to perform one or more tests relating to the disease.