Legal Analysis Highlights Impact of FDA AI Clinical Trial Pilot
A legal analysis published by Crowell & Moring says a proposed FDA pilot program on artificial intelligence in early-stage clinical trials could shape future agency expectations for how sponsors validate, document and oversee AI systems used in clinical research.
In a Request for Information (RFI) issued this month, FDA asked stakeholders for feedback on how an AI-enabled optimization pilot program for early-phase clinical trials should be structured, including how regulators should evaluate the reliability, governance and safety of AI tools used in areas such as patient recruitment, dose selection, endpoint assessment and safety monitoring.
According to the analysis, the request signals three broader policy trends: adoption of “trustworthy AI” principles aligned with the National Institute of Standards and Technology AI Risk Management Framework, increased emphasis on early collaboration between sponsors and regulators, and the possible development of standardized expectations for AI use in clinical trials.
“The pilot’s ‘scoreboard’ — the metrics and controls FDA decides are necessary — can become a de facto template for what FDA expects,” the authors write.
The RFI focuses on two primary areas: the design and implementation of the pilot program and the criteria regulators should use to evaluate whether AI improves trial efficiency and decision-making while remaining reliable and appropriately governed.
FDA is seeking feedback on issues including model validity, bias and fairness across demographic groups, explainability, cybersecurity, privacy protections and data governance. The analysis says that focus could expand FDA scrutiny beyond traditional performance measures such as accuracy and sensitivity toward broader governance expectations, including documentation, monitoring, vendor oversight and accountability controls.
The authors also say the agency’s emphasis on early engagement suggests companies developing AI-enabled clinical trial tools may benefit from interacting with FDA earlier in the development process to reduce uncertainty around acceptable use cases and evidentiary expectations.
The analysis notes that the pilot could ultimately help define where FDA considers AI most appropriate in trial conduct, distinguishing between lower-risk applications focused on operational efficiency, such as accelerating enrollment, and higher-risk systems that directly influence clinical decisions, including dose escalation and safety signal detection.
It also predicts that sponsors may seek stronger contractual protections from AI vendors and contract research organizations, including audit rights, version control requirements, cybersecurity assurances and documentation supporting fairness and subgroup performance evaluations.