Pre-Clinical SIG Webinar: AI agents for drug discovery and development
Date: Tuesday 23rd September 2025
Time: 16:00 - 17:00 GMT+1
Location: Online via Zoom
Who is this event intended for?
Statisticians interested in learning about the application of AI in Drug Discovery
What is the benefit of attending?
To learn more about how AI Agents can be implemented into Drug Discovery.
Overview
A 1 hour event, with a presentation and time for Q&A.
AI agents are large language models equipped with tools that can autonomously tackle challenging tasks. This talk will explore how generative AI agents can enable biomedical discovery.
Registration
Registration is free for both PSI Members & Non-Members.
To register for this event, please click here.
Speaker details
Speaker
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Biography
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Abstract
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James Zou
Associate professor of Biomedical Data Science at Stanford University
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James Zou is an associate professor of Biomedical Data Science, CS and EE at Stanford University. He works on developing cutting-edge AI for biomedical applications. His group developed many widely used innovations including EchoNet AI (FDA cleared for assessing cardiac function), Gradio (used by over a million developers), and SyntheMol (NY Times 2024 Good Tech). He has received a Sloan Fellowship, the Overton Prize, an NSF CAREER Award, two Chan-Zuckerberg Investigator Awards, a Top Ten Clinical Achievement Award, several outstanding paper awards at AI conferences, and faculty awards from Google, Amazon, Adobe and Apple.
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AI agents are large language models equipped with tools that can autonomously tackle challenging tasks. This talk will explore how generative AI agents can enable biomedical discovery. I’ll first introduce the Virtual Lab—a collaborative team of AI scientist agents conducting in silico research meetings to tackle open-ended R&D projects. As an example application, the Virtual Lab designed new nanobody binders to recent Covid variants that we experimentally validated. Then I will present CellVoyager, a computational biology agent that analyzes complex genomics data to derive new insights.
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