| What if AI could design a new drug in 30 seconds? That's the future I'm betting on. Maybe 5 years out. Maybe 15. But it's coming. This week I built a tiny piece of it. A reinforcement learning environment where an AI agent designs drug molecules atom by atom. Add a fragment. Swap an atom. Build a scaffold. The environment scores it on real chemistry: Lipinski rules, drug-likeness, synthesis difficulty, target protein binding. Trained Llama-3.2-3B with GRPO. Six hours on a single A10G. Image 1: a molecule the trained model designed. QED 0.94. Same drug-likeness range as FDA-approved oral medications. Image 2: the model's chemistry sense evolving across 150 training steps. You can almost see it figuring out what "drug-like" means. Six hours of GPU time produced something a medicinal chemist would actually look at. What happens at 600 hours? 6000? Genuinely curious what people here think. How far are we from "AI proposes 10,000 candidates, a chemist picks 5" being the routine drug discovery workflow? [link] [comments] |