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Mathematical modelling of transdermal permeation of chemicals with special focus on the hair follicle pathway.

Kattou, Panayiotis (2018) Mathematical modelling of transdermal permeation of chemicals with special focus on the hair follicle pathway. Doctoral thesis, University of Surrey.

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Abstract

The assessment of the follicular penetration of chemicals into the human skin is of high importance to topical and transdermal drug delivery, personal care, as well as risk assessment of chemical exposure. This is due to the significant contribution of the hair follicles to the penetration of chemicals through the epidermal barrier. The purpose of this work is to develop a two-dimensional pharmacokinetic model which will provide quantitative elucidation of the impact of the follicular pathway, in addition to the transcellular and intercellular routes, on a wide range of chemicals. The follicular pathway is modelled by diffusion in the sebum, which is assumed to completely fill the gap between the inner and outer root sheath. The model is capable of predicting the transdermal permeation kinetics by using built-in equations to estimate the input parameters (e.g. the partition and diffusion coefficients in various skin components). The model has been quantitatively or qualitatively compared to 18 experimental studies, and has demonstrated good predictive capability against the majority of the experimental data. Simulations across a wide chemical space have indicated that the follicular pathway has a greater impact on the penetration of lipophilic than hydrophilic chemicals. Additionally, the larger the molecular weight of the chemical, the greater the impact the hair follicle has on its penetration. The follicular impact has been quantified in various ways (e.g. amount penetrated, bioavailability, permeability difference). The developed model can provide new insight and detailed information regarding chemicals’ disposition and localised delivery in lipid, corneocytes, viable dermis, dermis and the hair follicle.

Item Type: Thesis (Doctoral)
Divisions : Theses
Authors :
NameEmailORCID
Kattou, Panayiotis
Date : 31 January 2018
Funders : BBSRC, Unilever
Copyright Disclaimer : Copyright © P. Kattou 2017
Contributors :
ContributionNameEmailORCID
http://www.loc.gov/loc.terms/relators/THSChen, TaoT.Chen@surrey.ac.uk
http://www.loc.gov/loc.terms/relators/THSLian, Guopingg.lian@surrey.ac.uk
Depositing User : Panayiotis Kattou
Date Deposited : 01 Feb 2018 08:55
Last Modified : 01 Feb 2018 08:55
URI: http://epubs.surrey.ac.uk/id/eprint/845509

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