An artificial intelligence-based tool developed by researchers in the U.K. is helping doctors identify people at risk of developing atrial fibrillation. Data from the ongoing Find-AF pilot study shows that the algorithm can comb through patients’ electronic health records and detect red flags which could indicate whether they are at risk of developing the heart condition.

Finding an effective medication for patients with major depressive disorder is notoriously difficult, with 70% of patients failing to respond to the first drug prescribed and 30% not responding to the first four medications. Complicating matters, genetic mutations can increase psychotropic drug-related adverse events, including hospitalizations. A recent study indicates Myriad Genetics Inc.’s Genesight test can help minimize the risk of these negative events, with a reduction of nearly 40% in psychiatric-related hospitalizations and prescription of medications with significant gene-drug interactions.

Researchers have identified a druggable pocket on the phosphatase Wip1, which regulates the tumor suppressor TP53 as well as DNA damage repair proteins. The work, which was published in Frontiers in Molecular Biosciences on April 18, 2023, by researchers from the University of Pennsylvania, could lead to therapeutics targeting Wip1. And the computational deep learning methods used to identify the pocket are broadly useful for identifying what the authors call “cryptic” pockets.