Vasudev Bhupathi, MS, is a Global Director of Pharmacovigilance at Moderna, based in Cambridge, Massachusetts, with nearly two decades of leadership experience in clinical safety and pharmacovigilance across vaccines, infectious diseases, oncology, neurology, and other complex therapeutic areas. He has led safety oversight for global clinical development programs and has extensive expertise in signal detection and evaluation, aggregate safety assessment, lifecycle benefit–risk management, real-world evidence integration, scientific literature surveillance, and regulatory safety strategy. His work focuses on transforming complex and diverse safety data into timely, clinically meaningful, and actionable insights throughout the product lifecycle. He is particularly interested in advancing the responsible use of artificial intelligence, automation, and digital technologies in pharmacovigilance to improve data integration, literature intelligence, safety signal prioritization, and longitudinal risk evaluation. His approach emphasizes human-in-the-loop decision-making, ensuring that technological efficiency is balanced with clinical judgment, scientific rigor, model interpretability, data quality, regulatory compliance, and patient protection. Vasudev is also an active author, speaker, and contributor to professional discussions on modernizing global safety surveillance, strengthening benefit–risk decision-making, and building more proactive, scalable, and patient-centered pharmacovigilance systems.
The presentation will explore how artificial intelligence and automation can strengthen long-term safety surveillance by supporting the identification and prioritization of delayed, cumulative, rare, and emerging safety risks across the product lifecycle. It will also emphasize the importance of a human-in-the-loop approach, in which AI-generated insights are evaluated through clinical judgment, scientific interpretation, and appropriate safety governance. The discussion will include how Human–AI collaboration can support the integration of clinical trial data, spontaneous safety reports, scientific literature, registries, and real-world evidence to improve signal evaluation, aggregate safety assessment, and benefit–risk decision-making.