Prediction of the in vitro permeability determined in Caco-2 cells by using artificial neural networks

European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences
Paulo PaixãoJosé A G Morais

Abstract

Caco-2 cells are currently the most used in vitro tool for prediction of the potential oral absorption of new drugs. The existence of computational models based on this data may potentiate the early selection process of new drugs, but the current models are based on a limited number of cases or on a reduced molecular space. We present an artificial neural network based only on calculated molecular descriptors for modelling 296 in vitro Caco-2 apparent permeability (P(app)) drug values collected in the literature using also a pruning procedure for reducing the descriptors space. LogP(app) values were divided into a training group of 192 drugs for network optimization and a testing group of another 59 drugs for early stop and internal validation resulting in correlations of 0.843 and 0.702 and RMSE of 0.546 and 0.791 for the training and testing group, respectively. External validation was made with an additional group of 45 drugs with a correlation of 0.774 and RMSE of 0.601. The selected molecular descriptors encode information related to the lipophilicity, electronegativity, size, shape and flexibility characteristics of the molecules, which are related to drug absorption. This model may be a valuable tool for prediction and s...Continue Reading

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Citations

Oct 30, 2012·Journal of Molecular Modeling·Fancui Meng, Weiren Xu
Sep 3, 2013·European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences·Paulo PaixãoJosé A G Morais
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Nov 7, 2013·Drug Development and Industrial Pharmacy·Hadi ValizadehParvin Zakeri-Milani
Oct 15, 2014·Journal of Pharmaceutical Sciences·Naseem CharooJennifer Dressman
Feb 27, 2016·European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences·Adriana Leandra SantoroCarlos Alberto Montanari
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Jul 18, 2017·Molecular Pharmaceutics·Swati NagarKen Korzekwa

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