Researchers have used machine-learning to identify a potential new antibiotic against a challenging species of disease-causing bacteria, they reported in a paper published in Nature Chemical Biology on May 25.
The finding is important because of the rise of antimicrobial resistance and the struggle to identify new classes of antibiotics. It also clarifies how machines can help speed up the identification, discovery, and testing of new antibiotics that the world desperately needs – and potentially reduce the cost of this laborious process.
