“All of these drugs fail due to certain reasons—they do not meet the criteria that we expected them to meet along some points in that clinical trial cycle,” he says. “What if we could identify them earlier, without having to go through multiple phases of clinical trials and then discover, ‘Hey, that doesn’t work.’”
The speed and accuracy of AI can give researchers the ability to quickly identify what will work and what will not, Gopal says. “That’s where the large AI computational models could help predict properties of molecules to a high level of accuracy—to discover molecules that might not otherwise be considered, and to weed out those molecules that, we’ve seen, eventually do not succeed,” he says.
Download the full report.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.