Biopartitioning micellar chromatography as a predictive tool for skin and corneal permeability of newly synthesized 17β-carboxamide steroids

Abstract

In this paper, human skin and corneal permeability of twenty-two newly synthesized 17β-carboxamide steroids was predicted using biopartitioning micellar chromatography (BMC). These compounds are potential soft glucocorticoids with local anti-inflammatory activity when applied to the skin or eye. BMC systems are used to simulate physicochemical properties of human skin (BMC-skin) and cornea (BMC-cornea). Micellar mobile phase, consisted of 0.04 M solution of polyoxyethylene (23) lauryl ether (Brij 35), was prepared at different pH values - 5.50 (BMC-skin) and 7.50 (BMC-cornea). Retention factors (k), obtained by use of BMC, were calculated for all newly synthesized 17β-carboxamide steroids as well as for parent glucocorticoids (hydrocortisone, prednisolone, methylprednisolone, dexamethasone and betamethasone). Good correlation was obtained between BMC-skin retention factors and permeability coefficients calculated by use of the artificial membrane that simulates stratum corneum of the human skin. Quantitative structure-retention relationship (QSRR) study was performed in order to explain retention factors of these compounds in the tested BMC systems. ANN-QSRR(k), PLS-QSRR(k) and MLR-QSRR(k) models, created by use of BMC-skin retention data, were compared and optimal model (PLS-QSRR(k)) was selected. Molecular descriptors of the selected model indicate that lipophilicity and number of short CC fragments of tested compounds have the strongest influence on the retention in the BMC-skin system and presumably on their in vivo permeability through human skin. The same model can be applied to the BMC-cornea system and the same conclusion can be drawn for corneal permeability. This model could be used as a predictive tool for the synthesis of novel 17β-carboxamide steroids with desirable permeability through human skin or cornea, depending on their potential pharmacological application. © 2014 Elsevier B.V. All rights reserved.