Issued2026-07-01

Best Practice Guide and Testing & Evaluation Framework for AI-Supported Clinical Trial Protocol Data Extraction and Criteria Mapping

Best Practice Guide / Testing & Evaluation FrameworkVoluntary

Summary

Provides best practices and evaluation methods for AI systems that extract and structure clinical-trial protocol information and map eligibility criteria to patient data, addressing accuracy, traceability, data interpretation, validation, fairness, and responsible workflow integration.

Healthcare Implications

Research organizations, healthcare providers, and developers should validate extraction and mapping against expert-reviewed references, preserve source traceability, test performance on structured and unstructured records, assess subgroup effects, protect patient data, and maintain human review for enrollment and eligibility decisions.

Impact Level

Medium

Keywords

Clinical Quality & Efficacy; Safety & Risk; Transparency & Governance; Privacy & Data; Equity & Bias

Stakeholders

Providers & Health Systems; Patients & Public; Developers & Vendors; Regulators & Government