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In Silico ADME Prediction: Data Sets and Models

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The models available in the literature for the in silico prediction of ADME (absorption, distribution, metabolism, excretion) properties, as well as the data sets used to derive them, are reviewed. Special emphasis is given to describe the latest and most complete models, with the largest and most diverse data sets. Models for human intestinal absorption, oral bioavailability, plasma protein binding, blood-brain barrier permeation, Pglycoprotein substrates and inhibitors, and metabolism are reviewed and discussed. An attempt is made to describe the general picture emerging from each set of models when possible, as well as the issues remaining to address in the different areas for future work. These models are an example of the utility of models and computer simulations for the prediction of pharmacokinetics.
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Keywords: bioavailability; bloodbrain barrier permeation; human intestinal absorption; in silico adme prediction; metabolism; p-glycoprotein; plasma protein binding; qsar

Document Type: Review Article

Affiliations: Department of Cheminformatics, GlaxoSmithKline, Centro de Investigacion Basica, Parque Tecnologico de Madrid, Tres Cantos, E-28760 Madrid, Spain.

Publication date: October 1, 2005

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  • Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.
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