Clinical Trials Are Running Agentic AI Faster Than Regulators Can Define It
Agentic AI now handles protocol deviation detection and trial monitoring, but no current framework tests for decision drift across autonomous runs.
Agentic AI now handles protocol deviation detection and trial monitoring, but no current framework tests for decision drift across autonomous runs.
Agentic AI tools for trial design look administrative, but EU AI Act and MDR overlap rules can pull them into conformity assessment regardless of vendor intent.
AI drug discovery has drawn billions in investment but zero FDA approvals, and the bottleneck sponsors need to plan for is evidence, not speed.
Generative AI is accelerating molecule design, but no AI-discovered drug has cleared trials, and regulators have yet to define how AI governs the trials themselves.
Generative AI is accelerating drug candidate design, but no AI-discovered molecule has reached approval because clinical trial execution and its regulatory footing remain unresolved.
FDA's closed RFI on AI-enabled early-phase trials signals a second oversight track distinct from device review, and sponsors are moving faster than either.
FDA's device review architecture and new leadership roles point toward trial-side AI scrutiny, though the timeline and scope remain genuinely unsettled.
AI-driven reanalysis of failed clinical trials is producing new evidence outside the systems built to validate it, and GxP quality frameworks have not caught up.
Sponsors are deploying AI across trial execution with no dedicated regulatory framework, leaving GCP and data integrity obligations to fill the gap alone.
While FDA's device guidance draws attention, a parallel track for AI in early-phase clinical trials and drug development is quietly taking shape.