Predicting Skin Permeability by means of Computational Approaches: Reliability and Caveats in Pharmaceutical Studies

Beatrice Pecoraro, Marco Tutone, Ewelina Hoffman, Victoria Hutter, Anna Maria Almerico, Matthew Traynor

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
243 Downloads (Pure)


The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experimental conditions, data set building rationales, and skin site of origin and hydration, still prevent us from obtaining a definitive predictive skin permeability model. This review wants to show the main advances and the principal approaches in computational methods used to predict this property, to enlighten the main issues that have arisen, and to address the challenges to develop in future research.

Original languageEnglish
Pages (from-to)1759-1771
Number of pages13
JournalJournal of Chemical Information and Modeling
Issue number5
Early online date18 Jan 2019
Publication statusPublished - 28 May 2019


  • Drug delivery
  • In silico prediction
  • Molecular dynamics
  • Multilinear regression
  • Partial least squares
  • Principle component regression
  • Quantitative structure-property relationships
  • Skin permeability


Dive into the research topics of 'Predicting Skin Permeability by means of Computational Approaches: Reliability and Caveats in Pharmaceutical Studies'. Together they form a unique fingerprint.

Cite this