Virtual cell models promise faster, cheaper early-stage drug discovery. However, the industry still lacks a shared way to judge which of these models can actually be trusted on a given problem. In this episode, Kristóf Szalay, CTO and Co-Founder of Turbine, and Gerold Csendes, Scientist at Turbine, set out what virtual cell models can and can't do today, in conversation with host Marilie Fouché. They cover why benchmarking remains fragmented across the field, how pharma teams build confidence in a model before trusting it with real R&D decisions, and how compressing the feedback loop between experiments can cut months out of the discovery process. This episode is sponsored by Turbine. Emerj works with a select group of AI vendors to reach Fortune 500 decision makers through research, media, and direct access. If you want to be considered, download our media kit at emerj.com/AD1

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