AI Scans 400,000 Reddit Posts to Find Hidden Side Effects of Ozempic-Type Drugs

Researchers at the University of Pennsylvania have used artificial intelligence to comb through more than 400,000 Reddit posts. They uncovered patient-reported side effects of GLP-1 drugs that may not be fully captured in clinical trials or official regulatory data. The study, published in the journal Nature Health, examined five years of posts from nearly 70,000 Reddit users discussing semaglutide (Ozempic, Wegovy, Rybelsus) and tirzepatide (Mounjaro, Zepbound).

Two symptom categories stood out for closer study: reproductive symptoms, including changes in menstrual cycles, and body-temperature problems such as chills and hot flashes. Nearly 4% of the Reddit users in the sample reported menstrual irregularities. The researchers say that figure would likely be higher in a female-only sample. The team stresses the findings show only an association — not proof the drugs caused these symptoms.

"Some of the side effects we found, like nausea, are well known, and that shows the method is picking up a real signal," said Sharath Chandra Guntuku, the study's senior author and a research associate professor in computer and information science at Penn Engineering. About 44% of users described at least one side effect, most commonly gastrointestinal problems.

Translating patients' everyday symptom descriptions into standardized medical terms, such as those in the Medical Dictionary for Regulatory Activities (MedDRA), was previously too labour-intensive at this scale. Large language models such as GPT and Gemini now let researchers process huge volumes of informal text much faster, said first author Neil Sehgal. Co-author Lyle Ungar first used social media to search for drug side effects in 2011.

The researchers caution that Reddit users skew younger, more male and more US-based than the overall population taking GLP-1 drugs, so the findings are not representative. Clinical trials remain the gold standard for safety, the team said, but online conversations can surface patient concerns faster once a drug reaches mass use.