Building the self-driving lab: a roadmap to bigger data and better drugs | TPM podcast

Rafael Rosengarten talks with NVIDIA’s Stacie Calad-Thomson about connecting AI-driven drug discovery to physical laboratory work. They examine why consistent experimental data is essential, how agents and robotics could coordinate experiments, and how scientists’ responsibilities may change as laboratories automate. The discussion distinguishes proposing molecules or experiments from executing them, validating results and deciding the next research step.