AI has designed thousands of potential antibiotics. Will any work?

"Researchers are turning to artificial intelligence (AI) to help design the next generation of antibiotics to combat rising antimicrobial resistance. In minutes, AI can design thousands of chemical compounds with potential antibacterial properties, although there are hurdles to overcome before the first of these medicines can be tested in people. Last week, the US Centers for Disease Control reported that rates of dangerous bacterial infections surged by 69% between 2019 and 2023."

"The standard method of antibiotic discovery involves going into nature and sifting through dirt to find antibacterial compounds, says César de la Fuente, a machine biologist at the University of Pennsylvania, Philadelphia. "That's really painstaking work that relies on trial and error, and it can take many years," he adds. His team has been using AI to discover antibiotics for about a decade."

AI can design thousands of candidate antibiotic compounds in minutes, greatly speeding a process that traditionally relies on environmental screening and lengthy trial-and-error. Dangerous bacterial infections rose 69% in the US from 2019–2023, and Enterobacterales are especially difficult to treat; 1.1 million deaths globally are linked to antimicrobial resistance annually. Machine learning and generative AI are trained on antibacterial and non-antibacterial compounds and on proteomes from animals, plants and bacteria to identify antibacterial protein fragments or create novel molecules. Some teams progress candidates from design to laboratory cell testing within one to two weeks, but most AI-designed antibiotics remain in early development and none have entered human trials yet; safety, efficacy and regulatory hurdles persist.

Read at Nature