Using AI to surface unreported GLP-1 side effects in Reddit posts
Researchers at Penn Engineering have identified patient-reported symptoms associated with GLP-1s in 400,000 posts from 70,000 user sand highlighted two main classes of symptoms that warrant further study.
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By using AI to analyze more than 400,000 Reddit posts, researchers at Penn’s School of Engineering and Applied Science have identified patient-reported symptoms associated with GLP-1s, the popular weight-loss and diabetes drugs semaglutide and tirzepatide, that may not be fully captured in clinical trials or regulatory documents.
(From left) Lyle Ungar, professor in computer and information science (CIS); Neil Sehgal, doctoral student in CIS; and Sharath Chandra Guntuku, research associate professor in CIS.
(Image: Sylvia Zhang)
The study, published in Nature Health, covers more than half a decade of posts from nearly 70,000 Reddit users and highlights two main classes of symptoms that warrant further study: reproductive symptoms, including irregular menstrual cycles, and temperature-related complaints, such as chills and hot flashes.
“Some of the side effects we found, like nausea, are well known, and that shows that the method is picking up a real signal,” says Sharath Chandra Guntuku, research associate professor in computer and information science (CIS) at Penn Engineering and the study’s senior author. “The underreported symptoms are leads that came from patients themselves, unprompted, and clinicians could potentially pay attention to them.”
“Clinical trials generally identify the most dangerous side effects of drugs,” says Lyle Ungar, professor in CIS and a co-author on the study. “But they can fail to find what symptoms patients are most concerned about; even though social media is not necessarily representative, a large collection of posts may reflect additional concerns.”
The researchers caution that their findings are not causal. “We can’t say that GLP-1s are actually causing these symptoms,” says Neil Sehgal, the study’s first author and a doctoral student in CIS advised by Guntuku and Ungar. “But nearly 4% of the Reddit users in our sample reported menstrual irregularities, which would be even higher in a female-only sample. We think that’s a signal worth investigating.”
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