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Predicting Skin Permeability by means of Computational Approaches : Reliability and Caveats in Pharmaceutical Studies. / Pecoraro, Beatrice; Tutone, Marco; Hoffman, Ewelina; Hutter, Victoria; Almerico, Anna Maria; Traynor, Matthew.

In: Journal of Chemical Information and Modeling, Vol. 59, No. 5, 28.05.2019, p. 1759-1771.

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@article{fb53fe1871634ae2a5847a4f54f0c145,
title = "Predicting Skin Permeability by means of Computational Approaches: Reliability and Caveats in Pharmaceutical Studies",
abstract = "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.",
keywords = "Drug delivery, In silico prediction, Molecular dynamics, Multilinear regression, Partial least squares, Principle component regression, Quantitative structure-property relationships, Skin permeability",
author = "Beatrice Pecoraro and Marco Tutone and Ewelina Hoffman and Victoria Hutter and Almerico, {Anna Maria} and Matthew Traynor",
note = "{\circledC} 2019 American Chemical Society.",
year = "2019",
month = "5",
day = "28",
doi = "10.1021/acs.jcim.8b00934",
language = "English",
volume = "59",
pages = "1759--1771",
journal = "Journal of Chemical Information and Modeling",
issn = "1549-9596",
publisher = "American Chemical Society",
number = "5",

}

RIS

TY - JOUR

T1 - Predicting Skin Permeability by means of Computational Approaches

T2 - Reliability and Caveats in Pharmaceutical Studies

AU - Pecoraro, Beatrice

AU - Tutone, Marco

AU - Hoffman, Ewelina

AU - Hutter, Victoria

AU - Almerico, Anna Maria

AU - Traynor, Matthew

N1 - © 2019 American Chemical Society.

PY - 2019/5/28

Y1 - 2019/5/28

N2 - 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.

AB - 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.

KW - Drug delivery

KW - In silico prediction

KW - Molecular dynamics

KW - Multilinear regression

KW - Partial least squares

KW - Principle component regression

KW - Quantitative structure-property relationships

KW - Skin permeability

UR - http://www.scopus.com/inward/record.url?scp=85061553009&partnerID=8YFLogxK

U2 - 10.1021/acs.jcim.8b00934

DO - 10.1021/acs.jcim.8b00934

M3 - Article

VL - 59

SP - 1759

EP - 1771

JO - Journal of Chemical Information and Modeling

JF - Journal of Chemical Information and Modeling

SN - 1549-9596

IS - 5

ER -