A free AI tool speeds up the search for new antibiotics

McMaster University’s ESKAPE model lets researchers screen compounds for antibacterial potential, helping speed up drug discovery. Drug-resistant infections kill more than a million people each year. But big pharmaceutical companies have largely abandoned the quest for new antibiotics, because the research and development needed to discover them is time-consuming and expensive. Autumn Arnold, a PhD student in the Stokes Lab at McMaster University in Canada, came up with a fix: an AI model that predicts which chemical compounds might kill dangerous bacteria. The model, called ESKAPE, is free to use: Researchers upload a list of compounds and get a prediction of their antibacterial activity. “All you need is an internet connection,” said Jonathan Stokes, a microbiologist who runs the lab. Researchers retain ownership of their discoveries, and don’t have to share the compounds they submit. “We have this perfect storm with rising resistance, a really lean antibiotic pipeline, and enormous economic headwinds,” Stokes said. “It’s going to cost you $1 billion to make a new drug, and you’re never going to make your money back.” So far, researchers have screened more than 12 million molecul