OpenTrials API

OpenTrials API aggregates and indexes publicly available structured data and documents related to clinical trials to support transparency and evidence synthesis in evidence-based medicine.

Key Features:

• Expandable data schema: A versatile, expandable schema for representing multiple document types and structured data for each clinical trial.
• Supported document types: Ingests registry entries, academic abstracts and full texts, regulatory documents, clinical study reports, and supplementary documents such as blank consent forms, case report forms, and protocols.
• Structured results and methods: Hosts structured data on methods and results extracted by systematic reviewers or other researchers.
• Indexing and matching: Aggregates, matches, and indexes trial-related records across multiple sources to create a comprehensive index.
• Web scraping: Uses web scraping to retrieve publicly available documents and metadata.
• Record linkage: Applies basic record linkage techniques to match records across disparate sources.
• Crowd-sourced curation: Incorporates crowd-sourced curation focused on selected drug areas to enhance data coverage.
• Integration of existing sources: Integrates existing sources of structured documents into the aggregated index.

Scientific Applications:

• Discoverability: Increase discoverability of trial-related documents and structured data across registries, publications, and regulatory sources.
• Research and evidence synthesis: Facilitate research and evidence synthesis by centralizing trial documents and structured results for analysis.
• Data consistency assessment: Enable identification of inconsistencies between registry entries, publications, regulatory documents, and submitted results.
• Audits of availability and completeness: Support audits regarding the availability and completeness of trial information and reporting.
• Advocacy for data standards: Support advocacy for improved data standards and higher-quality open data in evidence-based medicine.

Methodology:

Develops a practical data schema and populates the database via web scraping, basic record linkage techniques, crowd-sourced curation focused on selected drug areas, and integration of existing sources of structured documents.