PS19: AI/ML Across the Drug Development Spectrum: Innovation Powered by Statistical Rigor

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the drug development ecosystem-they are rapidly becoming embedded across the entire spectrum, from trial design and patient selection to safety monitoring, regulatory submissions, and post-market evaluation. These technologies promise unprecedented efficiency, adaptability, and precision, yet their adoption raises critical questions about transparency, reproducibility, and regulatory acceptance. This session will convene thought leaders from industry, regulatory agencies, and academia to explore how AI/ML can be responsibly and effectively applied throughout the drug development lifecycle. The discussion will consider the integration of AI/ML into adaptive and innovative trial designs, the use of real-world data to improve trial efficiency, and the application of predictive analytics to enhance safety signal detection and benefit–risk evaluation. Where possible, case studies will be highlighted to illustrate how these methods are being translated into practice and how statistical rigor ensures that results are credible, reproducible, and suitable for regulatory decision-making. By emphasizing both the transformative opportunities of AI/ML and the statistical rigor required for their implementation, this session will demonstrate how statisticians provide the foundation for trustworthy innovation. Attendees will gain insights into methodological advances, practical challenges, and forward-looking strategies that are poised to shape the next era of drug development.