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Software that read tens of thousands of research papers and then predicted new discoveries about the workings of a protein that’s key to cancer could herald a faster approach to developing new drugs.

The software, developed in a collaboration between IBM and Baylor College of Medicine, was set loose on more than 60,000 research papers that focused on p53, a protein involved in cell growth, which is implicated in most cancers. By parsing sentences in the documents, the software could build an understanding of what is known about enzymes called kinases that act on p53 and regulate its behavior; these enzymes are common targets for cancer treatments. It then generated a list of other proteins mentioned in the literature that were probably undiscovered kinases, based on what it knew about those already identified. Most of its predictions tested so far have turned out to be correct.

This same methodology could be applied to problems in physics. To read more, click here.