Closing the data loop in AI-driven drug discovery

Drug discovery is a costly, high‑risk endeavor, with development costs roughly doubling every nine years as described by Eroom’s Law. The piece examines how AI can accelerate the process by closing the data loop, potentially shortening timelines and lowering risk. It outlines challenges and opportunities in integrating continuous data into pharmaceutical research.

Summary written by Kernelia from the original article by MIT Technology Review. The story and its rights belong to its author.