Prediciton of skin permeability of compounds using IAM chromatographic and calculated descriptors

Although oral delivery remains to date the preferred method of drug administration, transdermal drug delivery systems are gaining in popularity. The skin permeability coefficient (K_d) is an important parameter that helps in the assessment of a compound’s epidermal permeability. This parameter is also important in the context of environmental toxicology, because many harmful substances enter the body through skin.

Transdermal permeation of drugs may be studied using many methods, including in vitro experiments on excised human skin, animal models (pig, rabbit, rat, mouse or shed snake skin), cultured human skin cells, or synthetic membranes. It is also investigated using liquid chromatographic (HPLC or TLC) models on silica, RP-18 or IAM chromatographic supports and the correlations between log K_d and the chromatogaphic data are either linear, or reversed-parabolic.

In this study log K_d values calculated using a well-established Potts' reference model for 50 compounds were correlated with the capacity factors log k_IAM obtained using Immobilized Artificial Membrane (IAM) HPLC chromatography on the IAM.PC.DD2 HPLC column using an aqueous mobile phase buffered in the pH range of pH 6.5-7.5. It was discovered that log k_IAM is a relatively good predictor of log K_d - it accounts for ca. 80% of its total variablity. The correlation, however, improves significantly when Polar Surface Area (PSA) is incorporated as a second independent variable, with a resulting equation accounting for ca. 94% of total variability. The model developed using two combined independent variables: log k_IAM and PSA was applied to a test set of 25 compounds.