DIA and the Tufts Center for the Study of Drug Development (Tufts CSDD), in collaboration with 16 biopharmaceutical companies and CROs, conducted a study to map current use of and experience with artificial intelligence (AI) and machine learning (ML), and their ability to reduce time across activities, in the drug development lifecycle. “We benchmarked various applications of AI and ML to 36 activities within clinical operations and development. We focused on design and planning, execution, and regulatory submissions, and looked at time reductions from investments in the use of AI and ML in a typical development program,” explains Tufts CSDD Director of Sponsored Research Mary Jo Lamberti in this interview with Stephanie Rosner (Scientific Program Manager for AI, DIA). “We expect to see higher levels of full implementation across all activities over the next few years.”