AI-Enabled Optimization of Early- Phase Clinical Trials Pilot Program; Request for Information

The commenter, representing an industry entity, supports the proposed pilot program as a way to drive efficiency and industry-wide adoption of real-time clinical trials. They argue that the pilot builds on successful previous standards-based regulatory advancements and will significantly reduce sponsor burden while improving data quality and integrity through AI-enabled automation.

DrKumo Inc., a connected health technology company, submitted joint comments with the Baim Institute for Clinical Research in support of the proposed AI-Enabled Optimization of Early-Phase Clinical Trials Pilot Program. They argue that the pilot should focus on continuous safety-signal detection and dose-escalation decision support, while providing specific recommendations on participant selection, collaboration models, and evaluation metrics to ensure the program's success and scalability.

Panoptive, a clinical trial oversight technology company, supports the FDA's pilot program for AI-enabled clinical trials. They argue that the pilot should focus on the "full oversight loop"—measuring how AI-surfaced signals are converted into accountable human decisions and inspection-ready records—rather than just signal detection speed. They provide specific recommendations on metrics, participant selection, and the need for human-in-the-loop governance to ensure reliability and regulatory compliance.

The commenter proposes a specific technical framework called RT-MSCCS to support the FDA's pilot program for AI-enabled clinical trial optimization. They argue that this system improves safety and efficiency by providing real-time dose escalation monitoring, mitigating alert fatigue, and aligning with NIST AI Risk Management Framework principles while maintaining human oversight.

Representatives from RD Research Services, LLC, Max Output, LLC, and an independent consultant provide detailed feedback on the FDA's AI-enabled clinical trials pilot program. They support the initiative but emphasize the need for robust regulatory engagement, clear liability frameworks, and specific metrics for safety, data integrity, and model performance to protect human subjects.

Syneos Health, a Contract Research Organization (CRO), expresses strong support for the AI-enabled clinical trials pilot program. They provide detailed recommendations on prioritizing oncology and rare disease trials, specific AI use cases like real-time safety monitoring, and methodologies for rigorous comparative evaluation.

The commenter proposes an integrated framework called RT-MSCCS and ARCT to optimize clinical trials using real-time monitoring, AI surveillance, and automated decision support. They argue that this system improves patient safety, reduces administrative burdens for investigators, and ensures regulatory compliance through explainable AI and human-in-the-loop governance.

Presentient Technologies Ltd, a biostatistics technology company, supports the proposed pilot program and proposes using its BRAKES system as a primary tool for early futility detection and real-time safety monitoring. They argue that their technology can improve ethical outcomes for participants and increase trial efficiency while maintaining data integrity through a secure, deterministic algorithm.

Parexel International, a global clinical development partner, supports the proposed AI-Enabled Optimization of Early-Phase Clinical Trials Pilot Program. They advocate for including Contract Research Organizations (CROs) as direct participants, prioritizing specific use cases like safety signal detection and dose-escalation, and establishing rigorous pre-specified metrics for evaluating AI performance and decision quality.

RQM+, a medical technology-focused contract research organization (CRO), supports the FDA's pilot program for AI-enabled optimization of early-phase clinical trials. They provide detailed recommendations on pilot design, infrastructure requirements, evaluation metrics, and advocate for extending the program's principles to medical devices and post-market surveillance.