Approaches to AI Validation in Regulated Clinical Systems and the eTMF

About this session

Part of Session 6, Track E: TMF Validation and Governance (Chair: Lisa Mulcahy, Mulcahy Consulting).

As AI becomes embedded in eClinical platforms, organizations must balance innovation with strict regulatory requirements. Unlike deterministic software, AI introduces probabilistic behavior, creating challenges in validation, traceability, and oversight.
This session examines practical approaches to deploying AI in a validated state within regulated environments. Drawing on frameworks such as ICH E6(R3), FDA AI/ML guidance, ISO 42001, and the EU AI Act, it outlines strategies for ensuring compliance across the AI lifecycle.
Topics include validation of non-deterministic models, human-in-the-loop controls, model monitoring and drift prevention, and ensuring transparency and reproducibility. Real-world use cases, including eTMF auto-classification and clinical data automation, demonstrate how organizations can maintain inspection readiness while scaling AI adoption.
Attendees will gain insight into governance models, risk-based validation approaches, and methods to operationalize trustworthy AI without compromising compliance.

Speaker

• JS

  Jay Smith

  TransPerfect

  Speaker