QSAR modeling of chemical penetration enhancers using novel replacement algorithms

The applications of transdermal delivery are limited because of the resistance of the skin to drug diffusion. Only potent drugs, with molecular weight less than 500 Da, are suitable to cross the skin barrier. Chemical Penetration Enhancers (CPEs) are used to promote the absorption of solutes across the dermal layers. In this investigation, a Quantitative Structure-Activity Relationship (QSAR) model is applied to relate chemical penetration enhancer structures with the flux enhancement ratio through a statistical approach. A database, consisting of 61 non-polar CPEs, is selected for the study. Each compound is represented by 777 QSAR descriptors, which encode the physical characteristics of the CPE and its structure. Selection replacement techniques are used to choose the eight most important descriptors. The enhancement ratio, an evaluation of the effect of the CPE, correlates well with this subset of features. The QSAR model can be adopted to predict factors that need to be adjusted to improve permeation of the drug through the skin. Three QSAR models are developed using different algorithms: forward stepwise regression (FSR), replacement (RM) and enhanced replacement (ERM) techniques. The first two methods yield equations with poor predictive power. The enhanced replacement method gives the best results, which meet cross-validation criteria: q^2 = 0.79, 0.63 and 0.76 for the training set, test set and combined data, respectively. These results meet the predetermined criteria.

Name thesis:degree_name

Master of Science in Pharmaceutical Bioprocessing - (M.S.)

Discipline thesis:degree_discipline

Chemical, Biological and Pharmaceutical Engineering

Year

2013

Author dc:creator

• Qiu, Hui

Contributors dc:contributor

• Laurent Simon
• Piero M. Armenante
• Carol A. Venanzi

• Transdermal delivery
• Chemical penetration enhancers
• Chemical penetration enhancer structures
• Chemical Engineering
• Pharmaceutics and Drug Design

Repository record dc:identifier

https://digitalcommons.njit.edu/theses/162

OAI identifier oai:identifier

oai:digitalcommons.njit.edu:theses-1161