Literature DB >> 12954198

Mechanistic and empirical modeling of skin permeation of drugs.

Fumiyoshi Yamashita1, Mitsuru Hashida.   

Abstract

The skin forms a barrier to the external environment, maintaining body fluids within our system and excluding harmful substances, while the skin is a site of administration of drugs for topical and systemic chemotherapy. It is an important issue to predict the rate at which drugs or other xenobiotics penetrate the skin. In this article, we review modeling approaches for predicting skin permeation of compounds, including both mechanistic and empirical approaches. Mechanistic approaches can give us much information on understanding of skin permeation of the compounds, such as structure-permeability relationship, contribution of each barrier step, mechanism of penetration enhancers, and in vivo-in vitro relationship. On the other hand, empirical modeling can overcome any inaccuracies of mechanistic models caused by the existence of uncertainties and, therefore, give us better predictions from the practical point of view. Artificial neural networks are being available for empirical modeling of complex skin transport phenomenon.

Mesh:

Substances:

Year:  2003        PMID: 12954198     DOI: 10.1016/s0169-409x(03)00118-2

Source DB:  PubMed          Journal:  Adv Drug Deliv Rev        ISSN: 0169-409X            Impact factor:   15.470


  10 in total

1.  Essential oil from Zanthoxylum bungeanum Maxim. and its main components used as transdermal penetration enhancers: a comparative study.

Authors:  Yi Lan; Hui Li; Yan-yan Chen; Ye-wen Zhang; Na Liu; Qing Zhang; Qing Wu
Journal:  J Zhejiang Univ Sci B       Date:  2014-11       Impact factor: 3.066

2.  DDSolver: an add-in program for modeling and comparison of drug dissolution profiles.

Authors:  Yong Zhang; Meirong Huo; Jianping Zhou; Aifeng Zou; Weize Li; Chengli Yao; Shaofei Xie
Journal:  AAPS J       Date:  2010-04-06       Impact factor: 4.009

3.  In vitro percutaneous permeation and skin accumulation of finasteride using vesicular ethosomal carriers.

Authors:  Yuefeng Rao; Feiyue Zheng; Xingguo Zhang; Jianqing Gao; Wenquan Liang
Journal:  AAPS PharmSciTech       Date:  2008-07-23       Impact factor: 3.246

4.  Magnetophoresis in combination with chemical enhancers for transdermal drug delivery.

Authors:  Srinivasa M Sammeta; Michael A Repka; S Narasimha Murthy
Journal:  Drug Dev Ind Pharm       Date:  2011-03-30       Impact factor: 3.225

5.  In Silico Modelling of Transdermal and Systemic Kinetics of Topically Applied Solutes: Model Development and Initial Validation for Transdermal Nicotine.

Authors:  Tao Chen; Guoping Lian; Panayiotis Kattou
Journal:  Pharm Res       Date:  2016-03-08       Impact factor: 4.200

Review 6.  Percutaneous permeation enhancement by terpenes: mechanistic view.

Authors:  Bharti Sapra; Subheet Jain; A K Tiwary
Journal:  AAPS J       Date:  2008-02-08       Impact factor: 4.009

7.  Scalable in silico Simulation of Transdermal Drug Permeability: Application of BIOiSIM Platform.

Authors:  Neha Maharao; Victor Antontsev; Hypatia Hou; Jason Walsh; Jyotika Varshney
Journal:  Drug Des Devel Ther       Date:  2020-06-11       Impact factor: 4.162

8.  Predicting Pharmacokinetic Properties of Potential Anticancer Agents via Their Chromatographic Behavior on Different Reversed Phase Materials.

Authors:  Małgorzata Janicka; Anna Mycka; Małgorzata Sztanke; Krzysztof Sztanke
Journal:  Int J Mol Sci       Date:  2021-04-20       Impact factor: 5.923

9.  Physicochemical properties determining drug detection in skin.

Authors:  Wout Bittremieux; Rohit S Advani; Alan K Jarmusch; Shaden Aguirre; Aileen Lu; Pieter C Dorrestein; Shirley M Tsunoda
Journal:  Clin Transl Sci       Date:  2021-11-28       Impact factor: 4.689

Review 10.  State-of-the-Art Review of Artificial Neural Networks to Predict, Characterize and Optimize Pharmaceutical Formulation.

Authors:  Shan Wang; Jinwei Di; Dan Wang; Xudong Dai; Yabing Hua; Xiang Gao; Aiping Zheng; Jing Gao
Journal:  Pharmaceutics       Date:  2022-01-13       Impact factor: 6.321

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.