The Prediction of Skin Permeability by Using Physicochemical Data

Abstract

A database on physicochemical properties and skin permeation compiled by Health Canada was analysed by using linear regression analysis. The correlation between permeability coefficient (K p ) and the octanol–water partition coefficient (K ow ) has been improved by grouping the compounds according to their respective molar volumes. Linear regression analysis of the individual groups has demonstrated a positive correlation for the majority of the groups, with the compounds in the lowest molar volume range (≤ 75Å 3 ) having the best correlation (r 2 = 0.86), and the compounds in the highest molar volume range (≥ 30lÅ 3 ) being the least well-correlated (r 2 = 0.55). Due to the diversity of the chemicals used in this analysis, and the statistically significant correlations obtained, this model could permit the prediction of skin permeation of a wide variety of chemical compounds. Although of a simplistic nature, and not yet experimentally validated, this quantitative structure-activity relationship may be useful for predicting human skin permeability coefficients for compounds that fall within the constraints of this data set.