Hot Topics from ACDM
About ACDM Hot Topics
These are held online as ‘discussions’ focussing on a topic in Data Management. They are free for ACDM members (small fee for Non-Members).
A person is identified to lead each session, together with a Chair, they drive the discussion with those who join call. Sometimes the sessions are recorded and/or summarised and shared with ACDM members.
From Risk to Real-World Readiness: Five Big Questions for AI in Clinical Data Science |
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| Date: | October 27, 2026 |
| Type: | Hot Topic |
| Session Lead: | ACDM Data Science DMEG |
| Location: | Online – 14:00 London GMT/15:00 Paris CET/09:00 New York EDT |
| Learning Objectives: | |
| Who is this suitable for? | ACDM members and non-members who would like to join an open discussion concerning a Hot Topic in Data Management. |
| Outline content | At the ACDM26 Data Science DMEG session, the discussion explored the AI/ML leap through five connected lenses: regulatory compliance, data governance and integrity, model transparency and validation, risk management, and operational and ethical considerations. The next challenge is no longer simply identifying the risks. It is deciding what ‘ready’ looks like when an AI-enabled process moves from an experiment into a clinical data workflow. This hot topic discussion will test five questions that organisations are now confronting: What evidence is sufficient to trust an AI-enabled workflow? How should changing models and autonomous agents be controlled? Is the underlying clinical data genuinely ready for AI? Who remains accountable across sponsors, CROs and technology vendors? And which measures should determine whether a use case is scaled, redesigned or stopped? The session will connect regulatory expectations with operational realities and invite participants to compare approaches, challenge assumptions and identify the minimum controls needed to move from promising pilots to defensible use in clinical data science. ABOUT THE DATA SCIENCE DMEG The Data Science DMEG explores the fast-moving field of data science in clinical research. The group focuses on the practical application of advanced analytics, machine learning, and artificial intelligence to clinical trials, aiming to improve data quality, optimise trial efficiency, and uncover deeper insights. By drawing on the collective expertise of its members, the group identifies best practices, shares real-world case studies, and provides guidance on integrating data science into research strategies. It also works to connect traditional data management methods with innovative data science tools, helping the clinical research community make the most of new technologies. The Data Science DMEG helps shape the future of clinical data management. |
| Price (Member) | £0 (+VAT) |
| Price (Non-Member) | £50 (+VAT) |
| Link for Booking: |  |