AI Helps Stanford Computer Scientists Predict Side Effects of Drug Combinations
Stanford News
By Nathan Collins
Stanford University's Marinka Zitnik, Monica Agrawal, and Jure Leskovec have developed an artificial intelligence system that can predict potential side effects from the use of combinations of drugs. Their Decagon system could potentially inform clinicians' decisions about which drugs to prescribe and help scientists identify better drug combinations for disease treatment. The researchers compiled a massive network defining more than 19,000 human proteins' interactions with each other and with drugs, then designed a deep learning technique to detect patterns in how side effects crop up based on how drugs target different proteins. They designed Decagon to deduce side-effect patterns and anticipate previously unobserved consequences from taking two drugs together. While Decagon currently only considers side effects associated with pairs of drugs, the team wants to broaden their results to include more complex regimens. ... "
Saturday, July 14, 2018
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