AI Analysis of Reddit Posts Finds Unexpected Symptom Reports Among Users of Unapproved Weight-Loss Drug

An experimental weight-loss drug that has not received regulatory approval is already being obtained online by users, and researchers are now using artificial intelligence to study what they report experiencing. The drug, retatrutide, belongs to a newer generation of GLP-1 medications designed to regulate appetite and body weight. It remains under investigation and is not approved for use.

Scientists at the University of Pennsylvania examined nearly 150,000 Reddit posts and comments from roughly 40,000 users, identifying about 14,000 who claimed to have personally taken an unapproved version of retatrutide. Their study, published in JAMA Network Open, offers the first systematic look at potential side effects reported by people claiming to use the drug.

Among users whose symptoms could be medically classified, increased appetite was the most common complaint. That finding was unexpected, since retatrutide is designed to suppress hunger, and its Phase 2 clinical trials mainly identified digestive problems as the most frequent side effects. Compared with earlier Reddit analyses of semaglutide and tirzepatide, discussions of unapproved retatrutide contained proportionally more mentions of appetite changes, sleep disturbances, elevated heart rate and muscle-related symptoms, and fewer mentions of nausea and digestive complaints.

The researchers stress the findings are not proof of previously unknown side effects. Reddit users differ from clinical trial participants, and their accounts cannot establish whether the drug caused the symptoms. There is also uncertainty about what people are actually taking, since products sold outside regulated medical channels may vary in ingredients, purity and dosage. "We can't say that retatrutide is causing these symptoms, or even that Reddit users are actually taking genuine retatrutide," said co-author Lyle Ungar.

Instead, the work is meant to generate hypotheses for further investigation. "AI helps us find recurring patterns in people's self-reports, including experiences that may be missed by conventional drug-safety monitoring," said senior author Sharath Chandra Guntuku. First author Neil Sehgal said the study offers "the first glimpse into the experiences of a population that is otherwise outside conventional drug safety monitoring." The team hopes other researchers will test the patterns in separate datasets.

Source: Science Daily (Popular)