4.7 Article

CYPlebrity: Machine learning models for the prediction of inhibitors of cytochrome P450 enzymes

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Summary: Adverse drug interactions account for roughly 2.8% of annual hospitalizations in the United States, with efforts to reduce these interactions often facing challenges in optimizing therapeutic outcomes. Preclinical drug design should consider cytochrome interactions to prevent development failures, but physiochemical and structural properties alone are insufficient to predict cytochrome inhibition accurately. Machine learning approaches offer a more robust and accurate way of predicting CYP inhibition.

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