# leegun

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Team:** [gun lee](https://cerebralvalley.ai/u/dlrjsdl200)
- **GitHub:** https://github.com/dlrjsdl200-byte/onlabel
- **Demo video:** https://www.youtube.com/watch?v=JXQKidfVldw
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/73

OnLabel is a self-verifying OTC medication-safety assistant for US consumers. Ask a chatbot "Can I take Tylenol and DayQuil together?" and it's often right on average — but for a medication-safety decision, being right on average isn't enough: it buries the answer in hedged prose, makes you do the math, and recalls numbers from memory that shift when you rephrase.

OnLabel separates language from judgment. Claude writes the answer and extracts the products the user named — but Claude never makes the safety call. Every product resolves to its FDA-grounded active ingredients, and a pure-code verifier builds an ingredient ledger to check active-ingredient duplication (the hidden acetaminophen in Tylenol + DayQuil), cumulative dose vs. the FDA daily maximum, and drug-class overlap. The verdict is composition plus arithmetic — reproducible every time, and every number traces to an FDA label line you can audit.

Why it matters: acetaminophen overdose is the leading cause of acute liver failure in the US, and the overlaps that cause it are exactly what generic AI answers miss. Built by a pharmacist who sees patients arrive with wrong AI advice daily.

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Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/73. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt