AI uncovers hidden Ozempic side effects across 400,000 Reddit posts
Researchers utilized large language models to analyze over 400,000 Reddit posts discussing GLP-1 medications like semaglutide and tirzepatide, uncovering underreported patient experiences such as menstrual changes, body temperature fluctuations, and fatigue. By translating colloquial social media conversations into standardized MedDRA terminology, the study demonstrates how computational social listening can rapidly surface early adverse-event signals that may be overlooked in traditional clinical trials. For medical, pharmacy, and data science educators, this work highlights the potential and limitations of using real-world unstructured data to complement formal pharmacovigilance.
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