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Toward Dose Prediction at Point of Design. | LitMetric

Toward Dose Prediction at Point of Design.

J Med Chem

Translational Pharmacokinetics, Pharmacodynamics and Investigative Toxicology, Johnson & Johnson Innovative Medicine, San Diego, California 92121, United States.

Published: December 2024

AI Article Synopsis

Article Abstract

Human dose prediction (HDP) is a useful tool for compound optimization in preclinical drug discovery. We describe here our exclusively in silico HDP strategy to triage compound designs for synthesis and experimental profiling. Our goal is a model that provides a preliminary estimate of the dose for a given exposure target based on chemical structure. First, we construct machine learning models to estimate rat pharmacokinetics, which are subsequently allometrically scaled to estimate human pharmacokinetics. Second, we establish a 10 nM free concentration target for early HDP where potency data are not yet available. Finally, we assess the uncertainty associated with each model and propagate these into the final estimate, providing us with actionable guidance on the level of accuracy of these estimates. We find that this strategy can reduce preparation of compounds with poor properties relative to an unstructured approach, but extensive experimental testing remains required.

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Source
http://dx.doi.org/10.1021/acs.jmedchem.4c02385DOI Listing

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