Join Nadia Harhen, General Manager of AI Simulation at SandboxAQ, and Jordan Crivelli-Decker from the Biosim team as they discuss how Large Quantitative Models (LQMs) are revolutionizing drug discovery and materials science by generating synthetic data through physics-based computational chemistry rather than just predicting outcomes like traditional language models. They explain how this approach accelerates drug development timelines, reduces animal testing needs, and enables breakthrough solutions for complex molecular problems that conventional software cannot handle, including work with Nobel laureate Dr. Stanley Prusiner that moved from research to clinical trials in just 18 months. The conversation explores how combining quantum mechanics principles with machine learning creates novel molecular IP across industries from pharmaceuticals to defense applications, bridging the gap between AI capabilities and practical scientific breakthroughs.
