Popular medications such as semaglutide and tirzepatide have become some of the most talked-about drugs in the world.
These medicines, often used to treat obesity and type 2 diabetes, can help people lose large amounts of weight and improve blood sugar control. Many patients and doctors see them as major breakthroughs because obesity and diabetes affect hundreds of millions of people worldwide.
Drugs in this group are often called GLP-1 medications. They work by copying hormones that help control appetite, digestion, and blood sugar. Many people taking these drugs report feeling less hungry, eating smaller meals, and losing weight over time.
However, as the use of these medications has grown rapidly, scientists have also become interested in understanding their side effects more fully.
Clinical trials usually identify the most serious and dangerous side effects before medicines are approved. But some symptoms may not appear clearly during trials because studies often involve limited numbers of patients and controlled conditions. People may also experience symptoms they never mention to doctors.
Now researchers at the University of Pennsylvania believe artificial intelligence may help uncover additional side effects by analyzing what people discuss online.
Their study, published in Nature Health, examined more than 400,000 Reddit posts written by nearly 70,000 users over more than five years.
The researchers used artificial intelligence tools and large language models to study online conversations about semaglutide and tirzepatide. Their goal was to identify patterns in symptoms people were discussing while taking these medications.
The results revealed several commonly reported side effects, including some that researchers believe deserve further scientific investigation.
Some of the symptoms were already well known. Many users discussed nausea and stomach-related problems, which are already recognized side effects of GLP-1 medications.
But researchers also noticed other symptoms that appear less prominently in official drug information.
One of the most discussed unexpected topics involved menstrual irregularities. Nearly 4% of Reddit users reporting side effects also described changes such as irregular periods, bleeding between menstrual cycles, or unusually heavy bleeding.
Some users also described temperature-related symptoms, including chills, feeling unusually cold, hot flashes, and fever-like sensations.
Fatigue emerged as another major complaint. In fact, tiredness became the second most commonly discussed symptom among Reddit users, even though it receives less attention in many clinical studies.
The researchers stressed that the study does not prove the medications caused these symptoms. Instead, the findings highlight patterns that may deserve closer scientific examination.
Neil Sehgal, a doctoral student involved in the study, explained that the menstrual-related reports may represent a signal worth investigating further.
Researchers believe social media may provide useful insight because patients sometimes discuss symptoms online that they never mention during doctor appointments.
Professor Lyle Ungar from the University of Pennsylvania said online communities often function like a real-time information network where people share experiences and compare notes about medications.
As social media use has expanded globally, scientists increasingly view these platforms as valuable sources of health-related information.
The study also highlights how artificial intelligence is changing medical research.
In the past, analyzing huge numbers of online posts was extremely difficult because people describe symptoms in many different ways. One person may say they feel “freezing,” while another may say they have “chills” or “cold flashes.”
Modern AI systems and large language models such as GPT and Gemini can now process enormous amounts of text much faster and organize these descriptions into standardized medical categories.
According to the researchers, this makes large-scale side-effect analysis far more practical than before.
The study found that around 44% of Reddit users discussed at least one side effect from the medications. Gastrointestinal problems were the most common complaints overall.
Researchers believe some of the newly discussed symptoms may be connected to how GLP-1 drugs affect the hypothalamus, a part of the brain involved in regulating hormones, body temperature, hunger, and metabolism.
Still, the researchers emphasized that much more research is needed before any firm conclusions can be made.
One important limitation is that Reddit users do not represent the entire population. Reddit users are generally younger, more likely to be male, and often based in the United States.
This means the experiences discussed online may not perfectly reflect what all patients experience worldwide.
Researchers also noted that people who post online may be more likely to share unusual or negative experiences.
Despite these limitations, scientists believe social media may become an increasingly useful early warning system for identifying possible drug side effects.
The research team now hopes to expand the work beyond Reddit and study conversations on other social media platforms and in different languages.
They believe this approach may be especially valuable for fast-growing medications and health products where traditional safety monitoring may take longer.
The researchers say online discussions may provide some of the earliest clues about what patients are experiencing in real life.
Overall, the study presents an interesting new approach to drug safety monitoring. The findings suggest artificial intelligence may help researchers identify possible side effects more quickly by analyzing real-world patient conversations online.
Some symptoms, such as menstrual irregularities and body temperature changes, appear important enough to deserve further scientific investigation. However, the study cannot prove the drugs directly caused these symptoms, and social media users do not represent the entire population.
Large clinical studies will still be necessary before doctors can confirm whether these side effects are truly linked to GLP-1 medications. Even so, the research highlights how AI and online health discussions may become powerful tools for future medical monitoring and patient safety.
Source: University of Pennsylvania.
