Beyond Black-Box AI for Drug Discovery: What to do when frontier AI models fail?

🧬 AlphaFold, Boltz-2, and the latest foundation models have changed how researchers approach molecules and proteins, but they have well-documented failure modes in the regimes that matter most for drug discovery. Physics-informed AI offers a complementary path: combining physical rigor with the speed of modern ML to address problems where purely data-driven models fall short. Join us for an evening with founders working at this intersection. We'll dig into where today's AI models break down, what physics-grounded approaches add, and where computational drug discovery goes next. Format 🎙️ Founders' fireside with three startups working at the frontier of drug discovery 💬 Audience Q&A 🤝 Networking with founders, biotech teams, and investors Who should come Biotech and pharma teams doing drug discovery, especially those scaling or outsourcing computational work, evaluating partners, or stress-testing an existing pipeline. Researchers, founders, and investors in the space are welcome too. 📍 San Francisco (venue shared upon approval) 🥂 Light bites + drinks ✨ Capacity is limited, register early. Hosted by Azulene Labs, Bakar Bio Labs and Pebblebed