Common Painkillers Linked to Superbugs, Study Warns

Scientists have issued a warning that commonly used painkillers such as ibuprofen (Advil) and acetaminophen (Tylenol) may unintentionally drive the spread of antibiotic-resistant superbugs, deepening an already critical public health challenge. The findings, published in a new study, suggest these everyday medications, when used alongside antibiotics, could accelerate the genetic changes that make bacteria like E. coli more resistant to treatment.

Researchers at the University of South Australia conducted experiments in which they exposed E. coli to ciprofloxacin, a common antibiotic, alongside ibuprofen and paracetamol. The results showed that these painkillers not only individually contribute to resistance but significantly amplifies it when used together. The study emphasizes the growing risk in settings like elder care facilities, where patients often receive multiple drugs, increasing the chance of resistant superbugs emerging.

Experts warn that while the overuse of antibiotics remains a major driver of resistance, the role of other medications—such as NSAIDs and antidepressants—is gaining attention. The World Health Organization has already classified antimicrobial resistance (AMR) as a top global health threat, with drug-resistant bacteria directly causing around 1.27 million deaths in 2019 and linked to nearly five million more. If current trends continue, projections suggest AMR-related deaths could rise to nearly 40 million by 2045.

The study highlights a particular concern in elder care and hospital settings, where patients are often prescribed multiple medications simultaneously. In these environments, the combination of drugs—whether painkillers, sleeping aids, antihistamines, or antidepressants—creates a perfect storm for the development of superbugs. The researchers emphasize that while these pharmaceuticals are vital for patient comfort, their widespread use may inadvertently exacerbate the resistance problem.

Dr. Marc Siegel, a Fox News medical analyst, explained the implications of the study.