How Can Federated AI/ML Learning Support Genomics and Patient Data Analytics to Enable Precision Medicine at Scale?

This on-demand webinar is part of the FAIR Webinar Series. For more information about the Pistoia Alliance’s FAIR Implementation project, please contact us.

Webinar Summary

Federated Learning is a learning paradigm that enables collaborative learning without centralizing datasets. In this webinar, NVIDIA will present the concept of Federated Learning and discuss how it can help overcome some of the barriers seen in the development of AI-based solutions for pharma, genomics and healthcare.

Following the presentation, there will be a panel debate on other elements that could drive the adoption of digital approaches more widely and help answer currently intractable science and business questions.

15:05 Pistoia Alliance Digital Strategy

• Paul Denny-Gouldson, Pistoia Alliance

15:10 How can federated learning support genomics and enable precision medicine at scale?

• Craig Rhodes, EMEA Industry Lead for Healthcare and Life Science, NVIDIA
• Nicola Rieke, Senior Deep Learning Solution Architect – Healthcare, NVIDIA

15:35 Panel: How do we collect and leverage patient data to develop tools that support digital health, what data is important and what barriers exist?

To include:

• Jennifer Goldsack, CEO Digital Medicine Society (DiMe)
• Tim McCarthy, Head of Digital Medicine & Translational Imaging, Pfizer
• Marissa Dockendorf, Director, Global Digital Analytics & Technologies, Merck

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