From Data To Decisions: How AI Is Reshaping Clinical Development And Trial Execution

As drug development grows more costly and complex, industry leaders are rethinking how clinical trials are designed, executed, and optimized. This session explores how artificial intelligence, real-world data, and advanced analytics are being applied across the clinical development lifecycle to improve trial efficiency, accelerate decision-making, and increase the probability of success.

Experts from Recursion, Roche, and Medable share practical examples of how AI is enabling more precise patient selection, smarter protocol design, improved site identification, and faster evidence generation. The discussion highlights how multimodal datasets, agentic AI, and predictive analytics can help reduce patient burden, streamline operations, and uncover insights that were previously difficult to access. At the same time, speakers emphasize the need to balance innovation with simplicity, ensuring that digital transformation improves the experience for patients and sites rather than adding complexity.

Looking ahead, the conversation examines the emergence of autonomous clinical trial operations, where AI agents support monitoring, data management, and study execution in real time. The result is a vision for a future where clinical development moves faster, learns continuously, and brings therapies to patients sooner.