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Artificial intelligence model finds potential drug molecules a thousand times faster

MIT researchers developed a geometric deep learning model that is more accurate and over 1,000 times faster at finding potential drug-like molecules than the fastest state-of-the-art computational models, reducing the chances and costs of failures in an industry where 90 percent of drug candidates fail clinical trials.
Pat Walters Artificial Intelligence Laboratory Drug Administration International Conference On Machine Learning Collaborative Research Department Of Electrical Engineering
Source: mit.edu

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