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A Random Walk Model of Skin Permeation
Author(s) -
Frederick Frasch H.
Publication year - 2002
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/0272-4332.00024
Subject(s) - stratum corneum , permeation , thermal diffusivity , permeability (electromagnetism) , random walk , partition coefficient , thermodynamics , membrane , mass diffusivity , materials science , diffusion , chemistry , chemical physics , mathematics , chromatography , physics , statistics , medicine , biochemistry , pathology
A new mathematical model for permeability of chemicals in aqueous vehicle through skin is presented. The rationale for this model is to represent diffusion by its fundamental molecular mechanism, i.e., random thermal motion. Diffusion is modeled as a two‐dimensional random walk through the biphasic (lipid and corneocyte) stratum corneum (SC). This approach permits calculations of diffusion phenomena in a morphologically realistic SC structure. Two concepts are key in the application of the model to the prediction of steady‐state skin permeability coefficients: ``effective diffusivity'' and ``effective path length,'' meaning the diffusivity and thickness of a homogeneous membrane having identical permeation properties as the stratum corneum. Algebraic expressions for these two variables are developed as functions of the molecular weight and octanol‐water partition coefficient of the diffusing substance. Combining these with expressions for membrane‐vehicle partition coefficient and permeability of the aqueous epidermis enables the calculation of steady‐state skin permeability coefficients. The resulting four‐parameter algebraic model was regressed against the ``Flynn data base'' with excellent results ( R 2 =0.84; SE =0.0076; F =154; N =94). The model provides insight into the contributions of stratum corneum diffusivity and effective path lengths to overall skin permeability and may prove useful in the prediction of non‐steady‐state diffusion phenomena.