Dr. Vinay Pawar is Scientific Director, Data & AI, in Novo Nordisk's R&D External Innovation group, based in Copenhagen. He leads strategic partnerships that bring large-scale human-cohort resources, multi-omics data and generative AI into Novo Nordisk's discovery pipeline — with a focus on diabetes, obesity and other cardiometabolic diseases. His current work spans cohort partnerships such as UK Biobank, AGD, PRECISE-SG100K and Variant Bio, alongside AI collaborations with Insilico Medicine and OpenAI. Trained as a molecular Immunologist, Vinay also holds an Adjunct Faculty position at the Department of Laboratory Medicine, Karolinska Institute, Stockholm, where he stays close to teaching and translational research.
Actionability of data in drug discovery depends on the completeness of underlying datasets and the analytical infrastructure to generate meaningful insights. This is amplified in the era of AI-driven interpretation, where models are only as powerful as the data they're trained on. As drug discovery teams adopt rapidly advancing approaches like machine learning for target identification, virtual cell modeling, and multiomic profiling, access to large-scale, diverse datasets with complete metadata has become a strategic imperative. This panel examines how hyperscale initiatives like the Alliance for Genomic Discovery (350,000+ whole genomes and 50,000+ linked proteomes) and the Illumina Billion Cell Atlas are providing the foundational data infrastructure for next-generation drug discovery. Panelists will bring expertise spanning functional genomics, machine learning, ADME, antibody developability and more to discuss what it takes to build AI-ready datasets, the importance and challenges of integrating across diverse datasets and infrastructures, and how both proprietary and pre-competitive collaboration are impacting today’s R&D landscape.