Abstract
In this study, a quantitative structure-pharmacokinetic relationship (QSPkR) model for the volume of distribution (Vd) values of 126 anti-infective drugs in humans was developed employing multiple linear regression (MLR), artificial neural network (ANN) and support vector regression (SVM) using theoretical molecular structural descriptors. A correlation-based feature selection (CFS) was employed to select the relevant descriptors for modeling. The model results show that the main factors governing Vd of anti-infective drugs are 3D molecular representations of atomic van der Waals volumes and Sanderson electronegativities, number of aliphatic and aromatic amino groups, number of beta-lactam rings and topological 2D shape of the molecule. Model predictivity was evaluated by external validation, using a variety of statistical tests and the SVM model demonstrated better performance compared to other models. The developed models can be used to predict the Vd values of anti-infective drugs.
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CITATION STYLE
Louis, B., & Agrawal, V. K. (2012). Quantitative structure-pharmacokinetic relationship (QSPkR) analysis of the volume of distribution values of anti-infective agents from J group of the ATC classification in humans. Acta Pharmaceutica, 62(3), 305–323. https://doi.org/10.2478/v10007-012-0024-z
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