As AI models rapidly advance, their real-world applicability remains limited by fragmented data, regulatory uncertainty, and lack of clinical alignment. This roundtable will bring together clinicians, RWE experts, and data scientists to debate how AI can meaningfully support research questions today, including regulatory-relevant analyses, patient-centric endpoints, and expanded access data generation, while overcoming the challenges of standardisation, accuracy, and trust.

Join this roundtable to discuss:

• Fit-for-Purpose AI Models in RWE: When does AI truly add value, and how can clinicians and data scientists co-define research questions that models can reliably address?
• Regulatory Readiness & Trustworthiness: How should AI algorithms be validated for decision-making, given regulatory bodies’ limited comfort with model-based inferences?
• Data Fragmentation, Bias & Standardisation Gaps: How do we improve data quality and consistency, across wearables, biometrics, unstructured records, to ensure AIdriven insights are reproducible?
• Patient-Centric Evidence Generation with Advocacy Partners: What role can patient groups play in defining outcomes and providing meaningful data for AIenabled research, such as treatment satisfaction or preference studies?