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BiotechOS — an operating system for running a drug-discovery pipeline. What we built: A system that reads a drug program's real inbox — CRO emails, quotes, invoices, contracts, assay reports — and turns every message into a concrete action a human just approves. A classifier routes each email to a specialized processor that extracts exactly what that document type needs; nothing changes state until a human signs off. On top sits a molecule layer (registry gate → Molecule Database with live pass/fail against a Target Product Profile → deep-dive → structure modeling to design new analogs) and a memory layer: a time-stamped record of every fact, a self-linking entity graph, and an immutable decision log, all partitioned by program. What we found: Most of a preclinical program's operational load — procurement, finance, legal, data QC, molecule tracking — is coordination that frontier AI plus domain-specific software can absorb, with the human kept as the approver, not the operator. Why it matters: AI and outsourcing have collapsed the cost of doing the science, but not the headcount needed to coordinate it. BiotechOS attacks that coordination tax directly, so one person can run a whole pipeline, not just a project.

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