Virtual Design of Chemical Penetration Enhancers

Abstract

This study focused on identifying new potential chemical penetration enhancers (CPEs) for transdermal drug delivery. A computer-aided molecular design (CAMD) algorithm was developed by integrating a new genetic algorithm and non-linear QSPR models to develop a reliable virtual screening algorithm for generation of potential CPEs. Structure-based predictive models for prediction of skin sensitization and skin irritation were developed using reliable experimental data for a wide range of molecular species to estimate the toxic potential of the generated chemical compounds. Non-linear neural network algorithms with superior capabilities were used for model development.