A skin permeability model of insulin in the presence of chemical penetration enhancer.

摘要: Enhancing transdermal delivery of insulin using chemical penetration enhancers (CPEs) has several advantages over other non-traditional methods; however, lack suitable predictive models, make experimentation the only alternative for discovering new CPEs. To address this limitation, a quantitative structure-property relationship (QSPR) model was developed, predicting permeation in presence A virtual design algorithm that incorporates QSPR models CPE properties used to identify 48 potential Permeation experiments Franz diffusion cells and resistance were performed quantify effect CPEs on permeability skin structure, respectively. Of CPEs, 35 training 13 validation. In addition, 12 reported literature also included validation set. Differential evolution (DE) coupled with artificial neural networks (ANNs) develop non-linear models. The six-descriptor had 16% absolute average deviation (%AAD) set 4 misclassifications Five six descriptors found be statistically significant after sensitivity analyses. results suggest, molecules low dipoles are capable forming intermolecular bonds lipid bi-layers show promise as effective insulin-specific