AI Insight
Researchers from Hungarian scientific institutions have published a review in Nature Reviews Microbiology proposing a five-step decision-making framework to predict antibiotic resistance during early drug development stages. The framework aims to identify which antibiotics bacteria are most likely to develop resistance against before the drugs reach patients. This approach could help pharmaceutical developers refine promising antibiotic candidates and avoid investing in drugs that will quickly become ineffective due to bacterial resistance.
Why it matters
Antibiotic resistance is a growing global health threat that renders previously effective treatments useless. By identifying resistance vulnerabilities early in development, this framework could save pharmaceutical companies from costly late-stage failures while ensuring that antibiotics reaching patients remain effective for longer periods, ultimately preserving these critical medicines for future generations.
Understand the Science
What if we could predict early in drug development which antibiotics bacteria are most likely to become resistant to? In a review published in Nature Reviews Microbiology, researchers from the HUN-REN Biological Research Centre, Szeged (HUN-REN BRC Szeged) and the Hungarian Centre of Excellence for Molecular Medicine (HCEMM) in Szeged propose a five-step decision-making framework that could help identify resistance risks early, refine promising drug candidates and prevent costly failures.
Source: Can we stop antibiotic resistance from ruining promising drugs before they reach patients?