The application and limitations of mathematical modelling in the prediction of permeability across mammalian skin and polydimethylsiloxane membranes

Abstract

While the results of this study indicate that permeation across rodent (mouse and rat) and pig skin is, in a statistical sense, similar, and that the artificial membranes are poor replacements of human or animal skin, the overriding issue raised in this study is the nature of the dataset and how it can influence the results, and subsequent interpretation, of any model produced for particular membranes. The size of the datasets, in both absolute and comparative senses, appears to influence model quality. Ideally, to generate viable cross-comparisons the datasets for different mammalian membranes should, wherever possible, exhibit as much commonality as possible.

Artificial Neural Network in Drug Delivery and Pharmaceutical Research

“…Also, the studies on absorption of toxic compounds through the skin are scarce with animal skin such as rodent and pig as a weak substitute [122]. Similar studies by AgatonovicKustrin et al and Cheng et al have published on use of ANNs in determining the quantitative structure-permeability relationship of penetration across skin or polydimethylsiloxane membranes as the model of skin permeation [123][124][125][126].…”

An equation for the prediction of human skin permeability of neutral molecules, ions and ionic species

“…Various kinds of empirical and mathematical models for the correlation and prediction of human skin permeability, as log Kp, have been reported (Baba et al, 2015;Mitragotri, 2003), and there have been a number of reviews of these models (Chen et al, 2013;Geinoz et al, 2004;Mitragotri et al, 2011;Moss et al, 2011;Neely et al, 2009). It has been known for years that the permeability of ionizable compounds depends on the pH of the donor solution, attributed to the slower rate of permeation of ionic species compared to the corresponding neutral species (Roy and Flynn, 1990;Swarbrick et al, 1984;Waters and Bhuiyan, 2016).…”

Dermal absorption and toxicological risk assessment : pitfalls and promises

“…Zhang et al (2009) observed that J max showed a more or less parabolic relationship with log K OW for similar sized permeants, Magee (1998) (cited in Moss et al, 2002) demonstrated that hydrogen bonding is more important in the most hydrophobic group of chemicals and Moss et al (2011) showed that the relation between measured k p -values and important properties determining permeation is non-linear.…”

“…These novel models are able to predict non-linear processes, and Gaussian process models have been shown to perform better than selected QSPRs (see Moss et al, 2011) as have fuzzy models and artificial neural networks (Russell and Guy, 2009). However, they yet have to prove their practical value (Mitragotri et al, 2011).…”

“…hydrogen bonding (Geinoz et al, 2004;Moss and Cronin, 2002). Furthermore, the k p model to be developed should be non-linear with respect to the relationships between k p and the predictive independent variables, since non-linear models seem to outperform the traditionally developed linear models (Moss et al, 2011;Russell and Guy, 2009). A disadvantage of non-linear models is that more data are needed to develop them than for linear models, and that they are more prone to overfitting.…”