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"Why Open-Source Models Matter for Computational Drug Discovery"

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AI is reshaping every industry—and drug discovery is no exception. Across targets, molecules, and data at massive scale, AI is becoming integral to how modern therapeutics are discovered and developed.

This panel explores how foundational open‑source AI engines like OpenFold and Boltz are being used across the drug discovery workflow, from target discovery and validation to hit identification and lead optimization. Panelists will discuss the growing role of structural modeling, chemoinformatics, and predictive machine learning, including how open models can enable faster structure–activity insights, earlier toxicity prediction, and more efficient decision‑making. The conversation will also touch on antibiotic discovery, where AI is helping researchers break through long‑standing scientific and economic barriers by identifying new mechanisms, molecular scaffolds, and design strategies.

This session is designed for scientists and leaders seeking to understand where open-source AI is delivering real impact today—and why AI is no longer optional for staying competitive in drug discovery.

Offered Free by: Drug Discovery Online
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