A drug whose claimed benefits keep expanding, rather than narrowing, is a red flag — not a sign of a broad mechanism
via #403 ‒ Peptides: separating scientific promise from marketing hype
AI-generated writing.
Peter Attia’s five-question framework for any drug, not just peptides: is there a viable mechanism of action, is there evidence of meaningful benefit in humans (not just animal models), do we understand safety/dosing/pharmacokinetics, does the likely benefit justify the risk, and is there a better-characterized way to get the same result? Peptides sort into three tiers — scientifically unsupported, biologically plausible but clinically unproven, and scientifically legitimate — and even landing in the top tier isn’t an endorsement of a specific off-label use, dose, or gray-market version of that molecule.
BPC-157 fails almost every question: its parent protein has never been fully characterized, no receptor or target is established, and after roughly three decades of use there are still no published human RCTs. The tell is that its claimed benefits have kept expanding — wound healing → tendons → ligaments → gut → inflammation → pain → MS — while legitimate drugs like GLP-1 agonists earned each new indication through a separate rigorous trial. Claims that broaden over time without new trial data are a sign of marketing filling the gap where mechanism should be, not evidence of a drug that happens to do everything.
Two other patterns explain why anecdotes are unreliable here: regression to the mean (people start a peptide when symptoms are at their worst, which is exactly when things improve anyway) and confounding from everything else changed at the same time (diet, exercise, other drugs). FDA approval isn’t infallible, but the process front-loads exactly the information gray-market peptides lack — a studied dose and population, a characterized safety profile, and manufacturing controls for identity, purity, and lot-to-lot consistency. The underlying test for any claim: if no possible outcome could disprove it — every disappointing result blamed on dose, timing, or supplier — it’s not a scientific claim anymore.