video1.0<iframe src="https://www.loom.com/embed/4e9ab966e3c848828d0ebbe9b33c7b47" frameborder="0" width="1670" height="1252" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12521670Loomhttps://www.loom.com12521670https://cdn.loom.com/sessions/thumbnails/4e9ab966e3c848828d0ebbe9b33c7b47-4bfecf7d832629a2.gif185.317🔗 Try it live: https://claude.ai/code/artifact/b4a412b5-2eeb-4447-992c-0771fad5398c 💻 Code (open source): https://github.com/rpinho/louis Louis is a drug-target discovery assistant for autoimmune disease that grades every answer by trust and learns from lab results. It runs on a genome-scale CRISPRi screen of human CD4⁺ T cells — the Marson–Pritchard autoimmune map — which no lab can use raw: you need a bioinformatician, and you can't tell if an answer is trustworthy. Louis fixes that. It returns graded, checkable evidence and flags non-peer-reviewed signal — it even stress-tests its own flagship pick, taking DOT1L from grade A down to C. It designs the next experiment (a two-arm go/no-go knockdown) and updates grades when bench results come back, as with HDAC7 for Th17-driven colitis. And it reads the bleeding edge: off-allowlist signal about a target like DOCK2 — from X, Bluesky, and conference abstracts — surfaced as signal, never as evidence. Built with Claude Code, Claude Opus, and Claude Science for the Built with Claude: Life Sciences hackathon (Builder track).