Design of skin penetration enhancers using replacement methods for the selection of the molecular descriptors

Laurent Simon, Beshoy Abdelmalek

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Transdermal delivery of certain drugs is challenging because of skin barrier resistance. This study focuses on the implementation of feature-selection algorithms to design chemical penetration enhancers. A database, consisting of 145 polar and nonpolar chemicals, was chosen for the investigation. Replacement, enhanced replacement and stepwise algorithms were applied to identify relevant structural properties of these compounds. The descriptors were calculated using Molecular Modeling Pro™ Plus. Based on the coefficient of determination, the replacement methods outperformed the stepwise approach in selecting the features that best correlated with the flux enhancement ratio. An artificial neural network model was built to map a subset of descriptors from sixty-one nonpolar enhancers onto the output vector. The R2 value improved from 0.68, for a linear model, to 0.74, which shows that the improved framework might be effective in the design of compounds with user-defined properties.

Original languageEnglish (US)
Pages (from-to)343-353
Number of pages11
JournalPharmaceutics
Volume4
Issue number3
DOIs
StatePublished - Sep 2012

All Science Journal Classification (ASJC) codes

  • Pharmaceutical Science

Keywords

  • Neural networks
  • Replacement methods
  • Skin penetration enhancer

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