WEBINAR SCHEDULE

Attendees will get a grounded look at how AI is being applied across the PV workflow right now, the difference between automation and true intelligence in a safety context, and how the scientist's role is evolving from data processor to strategic reviewer and decision-maker. The panel will also address the practical and regulatory considerations of bringing AI into a validated PV environment.

Supplier Assessment, Change Control, and Vendor-Deployed AI

Built for the people accountable when AI touches a trial, across quality, data, operations, and regulatory.

Advances in utilities, automation, and integrated process design shaping next-year readiness

Feasibility has always been part data, part relationship, part guesswork. AI now scores sites on historical enrollment and screen-failure performance, and identifies eligible patients from EHR and claims data before the protocol is final. The gains are real, and so is the problem underneath them: a model trained on which sites enrolled well historically will recommend the same sites that produced the trial populations sponsors are now under pressure to move past.

E6(R3) asks for risk proportionality and gives you no template for it. Central monitoring teams are using AI to detect site-level anomalies, surface patterns that suggest a protocol comprehension problem, and decide which visits need to happen at all. A signal only matters if someone acts on it, and the gap between a flag being raised and a monitor getting on a plane is exactly what an inspector will ask to see.

What emerging technologies and regulatory thinking signal for the year ahead

Techniques for improving documentation clarity and consistency across traditional, digital, and AI-supported validation approaches