Clinical Trials and the Role of Artificial Intelligence

Clinical trials sit at the center of how new medical therapies move from early scientific promise to safe, effective, and available treatment. Every stage of that journey — designing a protocol, finding the right participants, monitoring their safety, analyzing the resulting evidence, and ultimately gaining regulatory approval — has traditionally depended on expert judgment applied to data that arrives slowly and in fragments. Artificial intelligence is changing what's possible at each of these stages, not by replacing the clinicians, statisticians, and regulators who make the consequential decisions, but by giving them a far richer, faster, and more complete picture on which to base those decisions.

This book is organized to follow the clinical trial lifecycle roughly in order — from protocol design through recruitment, monitoring, data management, statistics, safety, decentralized trial infrastructure, precision medicine, real-world evidence, and finally regulatory science itself. A theme recurs throughout, stated plainly in the closing pages of the final chapter and worth stating here as well: AI expands what can be observed, predicted, and analyzed in clinical research, but clinical judgment and accountability for decisions affecting patient welfare remain, deliberately, a human responsibility. Every application described in the chapters that follow is built around that principle.