Artificial intelligence (AI) is revolutionizing clinical research by enhancing protocol generation, operational efficiency, and participant recruitment/engagement. Through predictive analytics and digital twins, AI streamlines protocols, optimizes inclusion criteria, and minimizes risk. AI also strengthens safety monitoring by identifying early adverse event patterns across diverse datasets, enabling proactive responses. For sponsors and sites, AI supports ongoing access to training and streamlines standard operating procedure development by analyzing past performance and recommending standardized practices. It automates data collection, reducing manual errors and accelerating timelines. In recruitment, machine learning matches ideal candidates using electronic health records and real-world data, while adaptive algorithms personalize recruiting messaging to improve enrollment rates. Together, these innovations reshape the trial landscape, making studies faster, safer, and more inclusive without compromising data integrity or participant protection. Examples reviewed include seen and unseen real-world AI impacts.

CEU: 1.00 ACRP

Speakers:

• Alain Alvarez Legra, Director for Clinical Research Coordinators, Bolanos Clinical Research

• Karen Lindsley, DNP, MSN, RN, CCRC, CDCES, Manager of Regulatory Knowledge and Support, Clinical and Translational Science Alliance of Georgia, Emory University