Antibiotic resistance is one of medicine's most urgent threats, and a new review in Cell Host & Microbe argues that artificial intelligence and rapid whole-genome sequencing could transform how we fight it. By analyzing a pathogen's genetic blueprint, machine learning models can predict which antibiotics a bacterium will resist before treatment even begins. This precision-medicine approach would allow clinicians to select narrow-spectrum therapies that target only the harmful bacterium, sparing the patient's microbiome from collateral damage. The authors also highlight how adjuvant compounds — drugs that enhance antibiotic effectiveness — could be matched to specific resistance profiles. Implementing this strategy requires overcoming real-world challenges, but the framework offers a credible path toward preserving antibiotic efficacy for future generations.
