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• W2117131208 abstract "The development of methods to predict the transport of molecules across biological membranes, without the need for time-consuming collection of experimental data, is a rapidly growing science. The use of structural characteristics of molecules has been investigated to predict the maximum transport rates of molecules across skin epidermal and intestinal membranes, known as maximum flux and maximum absorbable dose, respectively, although different approaches have been used. The aim of the present study was to determine whether the relationship between polar surface area and number of rotatable bonds of molecules and their permeability through intestinal membranes could be applied to the permeation of solutes through the epidermis following topical application.We used a published dataset of human epidermal maximum flux values for 182 solutes and stepwise regression to determine relationships between structural predictors and maximum membrane transport rates.Results showed that diffusion processes occurring across intestinal and skin epidermal membranes cannot be estimated by the same solute molecular properties, as different combinations of partitioning and diffusion processes appear to be dominating in each type of membrane. The basis of these differences in terms of molecular weight dependence and the usefulness of polar surface area are discussed.Based on available literature, we concluded that transdermal penetration is poorly predicted by parameters derived from intestinal or Caco-2 model membranes. While this approach may be useful for small sets of structurally related compounds, it appears to have limited value for screening and selection of novel structures in the pharmaceutical industry." @default.
• W2117131208 created "2016-06-24" @default.
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• W2117131208 date "2010-06-01" @default.
• W2117131208 modified "2023-09-24" @default.
• W2117131208 title "The application of molecular structural predictors of intestinal absorption to screening of compounds for transdermal penetration" @default.
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• W2117131208 doi "https://doi.org/10.1211/jpp.62.06.0011" @default.
• W2117131208 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/20636862" @default.
• W2117131208 hasPublicationYear "2010" @default.
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