Millions of people are now taking GLP-1 medications such as semaglutide and tirzepatide.
And they’re talking about them.
A lot.
On Reddit, people taking medications commonly known by brand names such as Ozempic, Wegovy, Mounjaro and Zepbound are sharing everything from how much weight they’ve lost to what happened after dinner.
For researchers, all that online chatter creates an interesting possibility:
Could social media help us detect potential drug side effects?
That’s the question behind a recent study led by researcher Neil K. R. Sehgal, who joined me on Causes or Cures to talk about what his team found.
What can 410,000 Reddit posts tell us?
Neil and his colleagues used artificial intelligence to analyze more than 410,000 Reddit posts mentioning semaglutide or tirzepatide.
That’s far more information than a group of researchers could realistically read and categorize manually.
Among people who reported taking the medications, researchers found many of the side effects we already associate with GLP-1 drugs, particularly gastrointestinal symptoms.
But some potentially less-recognized patterns also emerged.
These included reports involving fatigue, menstrual changes, and temperature-related symptoms such as chills and hot flashes.
And that’s where this gets interesting.
It’s also where we need to be careful.
A Reddit post can’t prove a drug caused something
Someone saying “I started taking this drug and then this happened” is not the same thing as demonstrating that the drug caused it.
People taking GLP-1 medications may have other medical conditions. They may be taking other medications. Their diet may have changed. They may have read about a symptom online and become more likely to notice or report it.
And Reddit users aren’t a random sample of everyone taking these drugs.
That’s why Neil and I spend part of the conversation discussing the distinction between a signal and causation.
If an unexpected symptom begins appearing repeatedly among people taking the same medication, researchers may want to investigate it.
That’s a signal.
It’s essentially science saying:
Huh. That’s interesting. We should probably look at that.
It is not science saying:
We have proven the drug caused it.
That’s an important distinction, particularly with medications attracting as much attention as GLP-1s.
Why don’t clinical trials catch every side effect?
Before medications reach the market, randomized clinical trials provide enormously valuable information about safety and effectiveness.
But clinical trials can’t tell us everything.
They involve a limited number of participants followed for a limited period of time under controlled conditions. Once a medication reaches the broader population, it may eventually be used by millions of people who are considerably more diverse than the people enrolled in the original trials.
Rare or unexpected effects can become easier to spot when the number of people taking a drug becomes very large.
That’s one reason drug safety monitoring continues after a medication reaches the market.
And traditionally, researchers and regulators have relied on sources such as clinical studies, medical records and adverse-event reporting systems to identify potential problems.
But now there’s another enormous source of information sitting in public view:
what patients are saying online.
Could Reddit become an early-warning system for drug safety?
Reddit is messy.
People exaggerate. People misunderstand things. People influence one another. Medical histories aren’t verified.
But it also contains something researchers don’t always get from traditional medical datasets: enormous numbers of people spontaneously describing what they’re experiencing in their own words.
AI makes it possible to examine those conversations at a scale that wasn’t previously practical.
That doesn’t mean Reddit replaces clinical trials or traditional pharmacovigilance.
It could potentially complement them.
A strange pattern appears online.
Researchers detect it.
Then they ask whether the same pattern appears in electronic health records, adverse-event databases, prospective studies or other sources.
In other words, social media might not give us the answer.
It might help us figure out which questions we should be asking.
And given how quickly millions of people can begin taking a new medication, that’s a pretty interesting possibility.
In my conversation with Neil K. R. Sehgal, we talk about how his team used AI to analyze hundreds of thousands of Reddit posts, what they found about semaglutide and tirzepatide, how researchers separate online noise from potentially meaningful safety signals, and whether social media could become another tool for monitoring medications once they’re being used in the real world.
Listen to the full episode of Causes or Cures:
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