Panel Discussion:
Gaining a competitive advantage in drug discovery through linked, multi-dimensional data at scale
Tuesday, 6 October 2026 | 17:25-18:05
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.
Moderator
Andrew Harris
Senior Director, Business Development, Corporate & Venture Development, Illumina
Speakers
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Dr. Vinay Pawar Novo Nordisk A/S, Director Digital Science External Partnership, |
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Dr. Ivan Kryukov Bayer Bayer, Senior Genomic Data Scientist |
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Dinesh Divakaran, PhD, MBA Illumina, Global Head of Data Business Development |
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Meet the Illumina Team
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