NVIDIA FLARE 2026 Q4 Webinar: Federated Learning in Drug discovery

Agenda 9:00 am -- 9:05 am PT -- door open 9:05 am -- 9:15 am PT -- Talk 1: NVIDIA FLARE lighting talk 9:15 am -- 10:00 am PT -- Talk 2: Apheris AISB Talk + QA 10:00 am -- 10:45 am PT -- Talk 3: Lilly TuneLab Talk + QA 10:50 am -- Closing Meeting Link: Microsoft Teams meeting Join: https://teams.microsoft.com/meet/2770939233648874?p=eZnvXZb31xc861VGzU Meeting ID: 277 093 923 364 887 4 Passcode: Ls3mH2h3 Talk 1: Federated Confidential Computing with NVIDIA FLARE Lightning Talk, introducing the on-prem Federated Confidential Computing Speaker : Chester Chen, Senior Product Manager & Engineering Manager, NVIDIA Talk 2: What Federated Training Delivered: Co-Folding and ADMET Results from Apheris Pharma Networks, Apheris Apheris builds superior drug discovery models through federated data, powered by NVIDIA FLARE. In this talk, we go through our co-folding and ADMET results. For co-folding, we show how we designed the benchmarks for the federated model and how OpenFold3 was trained on five pharma companies’ proprietary structural data, inside their security boundaries, in under ten weeks. For ADMET, we show how the network is set up and how it learns across pharma partners’ private measurements. We also cover how the resulting models compare with public baselines, how purpose-built data generation extends the networks, and how Apheris Foundry lets teams run, customize, and integrate the models in their own environment. Speakers: Robin Röhm is the CEO and Co-Founder of Apheris, where he focuses on building enterprise AI applications and federated data networks for drug discovery. With a background in Medicine, Philosophy, and Mathematics, he brings a multidisciplinary perspective to the scientific and computational challenges of working with distributed, IP-sensitive data. His work centers on enabling pharma companies to run, fine-tune, and benchmark drug discovery models securely within their own environments and to collaborate through governed data networks without