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Schrödinger taps AI to speed drug discovery (Sponsored)

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Robert Abel, chief scientific officer at Schrödinger, says advanced computational tools are changing the pace and accuracy of drug discovery. In a recent episode of The Top Line podcast, Abel outlined three areas where AI and machine learning are making the greatest impact: understanding disease biology, predicting protein structures and designing drug molecules. Schrödinger’s platform uses physics-based simulations alongside AI to evaluate millions of molecules in days, compared with the thousands traditionally synthesized in a year.

Abel pointed to real-world results, including a program that reached a clinical trial candidate in just 10 months — far faster than industry averages. He said the technology also helps overcome challenges such as improving drug selectivity and reducing the need for animal testing, aligning with FDA priorities. Abel will share more insights during his upcoming talk at AAPS PharmSci 360 in San Antonio this November. His session abstract is available here. To hear more about Schrödinger’s work in computational drug discovery, listen to the full interview.

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