A fully computational model for predicting percutaneous drug absorption.

Publication Type:

Journal Article


Journal of Chemical Information and Modeling, Volume 46, Issue 1, p.424-9 (2006)


Animals, Computer Simulation, Drug Design, Permeability, Pharmaceutical Preparations, Reproducibility of Results, Skin Absorption, Structure-Activity Relationship


The prediction of transdermal absorption for arbitrary penetrant structures has several important applications in the pharmaceutical industry. We propose a new data-driven, predictive model for skin permeability coefficients k(p) based on an ensemble model using k-nearest-neighbor models and ridge regression. The model was trained and validated with a newly assembled data set containing experimental data and structures for 110 compounds. On the basis of three purely computational descriptors (molecular weight, calculated octanol/water partition coefficient, and solvation free energy), we have developed a model allowing for the reliable, purely computational prediction of skin permeability coefficients. The model is both accurate and robust, as we showed in an extensive validation (correlation coefficient for leave-one-out cross validation: Q = 0.948, mean standard error: 0.2 for log k(p)).