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In Silico Prediction of Percutaneous Absorption and Disposition Kinetics of Chemicals

Chen, L, Han, L, Saib, O, Lian, G and Lian, G (2015) In Silico Prediction of Percutaneous Absorption and Disposition Kinetics of Chemicals Pharmaceutical Research, 32 (5). pp. 1779-1793.

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Abstract

© 2014 Springer Science+Business Media. Purpose: To develop in-silico model for predicting percutaneous absorption and disposition kinetics of chemicals in skin layers so as to facilitate the design of transdermal drug delivery systems and skin care products, and risk assessment of occupational or consumer exposure. Methods: A general-purpose computer model for simulating skin permeation, absorption and disposition kinetics in the stratum corneum, viable dermis and dermis has been developed. Equations have been proposed for determining the partition and diffusion properties of chemicals by considering molecular partition, binding and mobility in skin layers. In vitro skin penetration data of 12 chemicals was used to validate the model. Results: The observed and simulated permeation and disposition in skin layers were compared for 12 tested chemicals. For most tested chemicals, the experimental and model results are in good agreement with the coefficient of determination >0.80 and relative root mean squared error <1.20. The disposition kinetic parameters of the maximum concentration and the area under the curve in the viable epidermis and dermis initially increased with hydrophobicity, but reached maxima and then decreased with further increase of hydrophobicity. Conclusions: By considering skin physiological structure and composition, the partition and diffusion properties of chemicals in skin layers are determined. This allows in-silico simulation of percutaneous permeation, absorption and disposition kinetics of wide chemical space. The model produced results in good agreement with experimental data of 12 chemicals, suggesting a much improved framework to support transdermal delivery of drug and cosmetic actives as well as integrated risk assessment.

Item Type: Article
Authors :
NameEmailORCID
Chen, LUNSPECIFIEDUNSPECIFIED
Han, LUNSPECIFIEDUNSPECIFIED
Saib, OUNSPECIFIEDUNSPECIFIED
Lian, GUNSPECIFIEDUNSPECIFIED
Lian, GUNSPECIFIEDUNSPECIFIED
Date : 1 May 2015
Identification Number : 10.1007/s11095-014-1575-0
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 10:57
Last Modified : 28 Mar 2017 10:57
URI: http://epubs.surrey.ac.uk/id/eprint/809471

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