In vitro and in silico computational methods for assessing vaginal permeability

Abstract

Objective Vaginal administration is an important alternative to the oral route for both topical and systemic use. Therefore, the development of reliable in silico methods for the study of drugs permeability is becoming popular in order to avoid time-consuming and costly experiments. Methods In the current study, Franz cells and appropriate HPLC or ESI-Q/MS analytical methods were used to experimentally measure the apparent permeability coefficient (P app) of 108 compounds (drugs and non-drugs). P app values were then correlate with 75 molecular descriptors (physicochemical, structural, and pharmacokinetic) by developing two Quantitative Structure Permeability Relationship (QSPR) models, a Partial Least Square (PLS) and a Support Vector Machine (SVM). Both were validated by internal, external and cross-validation. Results Based on the calculated statistical parameters (PLS model A: R 2 = 0.673 and Q 2 = 0.594, PLS model B: R 2 = 0.902 and Q 2 = 0.631, SVM: R 2 = 0.708 and Q 2 = 0.758). SVM presents higher predictability while PLS adequately interprets the theory of permeability. Conclusions The most important parameters for vaginal permeability were found to be the relative PSA, logP, logD, water solubility and fraction unbound (FU). Respectively, the combination of both models could be a useful tool for understanding and predicting the vaginal permeability of drug candidates.