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MIT-Takeda Program heads into fourth year with crop of 10 new projects

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.

Deploying machine learning to improve mental health

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