2009
DOI: 10.1002/aic.12048
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Modeling transdermal permeation. Part I. Predicting skin permeability of both hydrophobic and hydrophilic solutes

Abstract: In this study, we present a modeling study on the prediction of transdermal permeability of both hydrophobic and hydrophilic solutes, using our recently reported mechanistic model of mass transfer in complex media, where the heterogeneous structure of the stratum corneum is represented by "bricks-and-mortar" model. The partition and diffusion properties of solutes in lipid matrix and corneocytes are calculated separately, without fitting to the modeled skin permeability data. Skin permeability has been predict… Show more

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Cited by 50 publications
(46 citation statements)
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“…In general, available QSARs are based on the assumption that the intercellular lipid pathway is the main route of permeation and are applicable to hydrophobic compounds, with the skin permeability of hydrophilic compounds being underpredicted, typically by 2-6 orders of magnitude. 102 In addition to QSARs, classification models have also been developed, using, for example, Classification And Regression Tree (CART) methodology. 103 Simple rules of thumb to distinguish between ''good'' and ''bad'' penetrants on the basis of readily available physicochemical properties (e.g., molecular weight, melting point) have been proposed by Magnusson et al (2004).…”
Section: In Silico Methodsmentioning
confidence: 99%
“…In general, available QSARs are based on the assumption that the intercellular lipid pathway is the main route of permeation and are applicable to hydrophobic compounds, with the skin permeability of hydrophilic compounds being underpredicted, typically by 2-6 orders of magnitude. 102 In addition to QSARs, classification models have also been developed, using, for example, Classification And Regression Tree (CART) methodology. 103 Simple rules of thumb to distinguish between ''good'' and ''bad'' penetrants on the basis of readily available physicochemical properties (e.g., molecular weight, melting point) have been proposed by Magnusson et al (2004).…”
Section: In Silico Methodsmentioning
confidence: 99%
“…41 The model has been applied to predict skin permeability of a large data set and it is shown that the prediction is significantly improved by including the transcelluar pathway which contribute to more than 95% of transdermal permeation of highly hydrophilic solutes. 42 In this study, the model is further applied to predict transdermal permeation and absorption of topically administered solutes in vivo. We first discuss the validation of the model against two sets of experimental data published elsewhere: the in vivo tape striping data of 4-cyanophenol 29 and confocal Ramon spectroscopic data of transretinol.…”
Section: Introductionmentioning
confidence: 99%
“…Due to the lack of precise information about the vehicle, sensitivity analysis was conducted to investigate the impact of vehicle properties (partition and diffusion coefficients). The diffusion and partition properties of nicotine in stratum corneum were calculated in the same way as previously verified (14). The fraction of nonionised nicotine at pH 7.4 and binding to plasma …”
Section: Model Demonstration: Clinical Studies Of Nicotinementioning
confidence: 99%
“…Wang et al (11,12) reported a more predictive two-dimensional model, in which the diffusion and partition coefficients were obtained from fundamental principles, and only the trans-bilayer mass transfer coefficient was fitted to deduce a correlation with the molecular weight. A similar two-dimensional approach was taken by Lian and coworkers (13,14), where data-fitting was only used to derive a correlation for calculating the diffusion coefficient in corneocytes, and the prediction accuracy was significantly improved when compared with the Wang's model in (11,12). With consideration of the two-dimensional microscopic skin structure, both models (11,12,13,14) demonstrated the importance of the trans-cellular diffusion pathway through the stratum corneum.…”
Section: Introductionmentioning
confidence: 99%
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