A Data-Mining Approach for the Quantitative Assessment of Physicochemical Properties of Molecular Compounds in the Skin Flux

Abstract

This paper aimed to provide an insight into the mechanism of transdermal penetration of drug molecules with respect to their physicochemical properties, such as solubility (S), the presence of enantiomer (ET) and logarithm of octanol-water partition coefficient (log P), molecular weight (MW), and melting point (MP). Propionic acid derivatives were evaluated for their flux through full-thickness skin excised from hairless mice upon being delivered from silicone-based pressure-sensitive adhesive (PSA) matrices in the presence or absence of various enhancers. The skin fluxes of model compounds were calculated based on the data obtained using the method engaged with the diffusion cell system. The statistical design of experiments (DoE) based on the factorial approach was used to find variables that have a significant impact on the outcomes. For the prediction of skin flux, a quantitative equation was derived using the data-mining approach on the relationship between skin permeation of model compounds (~125 mg/ml) and involved physicochemical variables. The most influential variables for the skin flux of propionic acid derivatives were the melting point (0.97) followed by the presence of enantiomer (0.95), molecular mass (0.93), log P values (0.86), and aqueous solubility (0.80). It was concluded that the skin flux of molecular compounds can be predicted based on the relationship between their physicochemical properties and the interaction with cofactors including additives and enhancers in the vehicles.

Keywords: data-mining; physicochemical properties; quantitative assessment; skin flux.