There’s no shortage of AI models aimed at discovering new drugs these days. Researchers have introduced more than 200 of these foundation models in the last three years, with 40% growth per quarter, according to a new paper published this month in the journal Drug Discovery Today. Pharmaceutical giant Merck and Nvidia recently rolled out a new entry in this growing body with a small-molecule drug model called KERMT. The model is pretrained on more than 11 million molecules, then fine-tuned for various tasks specific to industrial drug discovery workflows, according to Merck. Alan Cheng, Merck’s senior director of data science, told us the model could help scientists better predict how a given molecule will behave in the body, potentially catching problems before researchers invest in months of testing. “Traditionally, scientists spend months running physical and biological tests to understand ADMET properties: absorption, distribution, metabolism, excretion, and toxicity,” Cheng said in an email interview. “These steps are essential because a promising compound can fail late in development if it is toxic or has poor exposure at the therapeutic target.” Here’s more on what Merck and Nvidia have in store.—PK |