VIDEO SESSION
Case Study: An introduction to
Agentic AI in Clinical Data Management
Your data managers already carry most of the review load. Agentic AI can take much of it on, but only if you can trust, trace and reproduce what it produces. Alex Liu of Taiho Oncology and Erik Scalfaro of Rivia walk through where AI fits in a regulated trial and show it working on live study data.
Live Case Study
Rivia x Taiho Oncology
What you'll learn
Where AI fits in clinical data management and how the data manager role changes
The three levels of AI adoption, from standalone assistants to agents you oversee from on top of the loop. Alex explains why data managers are moving from producing review to approving it, as proactive stewards.
What it takes to adopt AI safely and stay compliant in a GxP setting
The three pillars that decide adoption: governance and trust, process and priority, skills and readiness. Plus what ALCOA++ requires of AI output, and why results stay reproducible when models aren't deterministic.
A live demo on trial data, from a single finding to a standing rule
You'll see a CTCAE grading inconsistency between neutropenia AEs and lab values, found by asking in natural language. Then it becomes a standing rule that flags every future case, with a clear path to resolution.
Watch the full session
With Alex Liu of Taiho Oncology and Erik Scalfaro of Rivia, including the live demo. Fill in the form for instant access.


