Post by Elizabeth Hiblin

🧩 One Thing Doesn't Add UpWe're screening billions of molecules… but still choosing targets almost manually. Every few weeks I read another announcement:"Our AI screened 2 billion molecules.""Our foundation model generated millions of candidates."Impressive numbers. But here's what keeps bothering me. Before those billions of molecules were ever generated, someone had to answer a much simpler question:"Is this target even worth pursuing?" 🧑‍🔬 And surprisingly, that decision often still relies on weeks of literature review, genetics analysis, clinical trial searches, competitive landscaping, internal discussions, and expert judgment. In other words:We've automated one of the most computationally intensive parts of drug discovery. But one of the most strategic decisions still depends on people stitching together evidence from dozens of disconnected sources.Maybe that's why so many AI platforms still feel incomplete.They accelerate chemistry.But chemistry only matters after biology... ___________ 👋 Hi! I'm Elizabeth Hiblin, building AI for Decision Intelligence in drug discovery. I share observations on drug discovery, target validation, AI, and emerging industry trends. 🔗 Сonneсt with me on LinkedIn. #BiotechStartup#AIinResearch #lifescience #BiotechInnovation #TargetIntelligence #BiologicalIntelligence #Therapeutic