Interactions of skin thickness and physicochemical properties of test compounds in percutaneous penetration studies.

Simon C Wilkinson, Wilfred J M Maas, Jesper Bo Nielsen, Laura C Greaves, Johannes J M van de Sandt, Faith M Williams

Index: Int. Arch. Occup. Environ. Health 79(5) , 405-13, (2006)

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Abstract

To determine the effect of skin thickness on the percutaneous penetration and distribution of test compounds with varying physicochemical properties using in vitro systems. Studies were carried out in accordance with OECD guidelines on skin absorption tests.Percutaneous penetration of caffeine (log P -0.01), testosterone (log P 3.32), propoxur (log P 1.52) (finite dose in ethanol to water vehicle ratio) and butoxyethanol (log P 0.83) (undiluted finite dose or as an infinite dose 50% [v/v] aqueous solution) through skin of varying thicknesses under occluded conditions was measured using flow through cells for 8-24 h. Saline (adjusted to pH 7.4) was used as receptor fluid, with BSA added for studies with testosterone and propoxur. Following exposure, the remaining surface dose was removed by swabbing and the skin digested prior to scintillation counting.The maximum flux of caffeine was increased with decreasing skin thickness, although these differences were found to be non-significant. The presence of caffeine in the skin membrane was not altered by skin thickness. Maximum flux and cumulative dose absorbed of testosterone and butoxyethanol (in both finite and infinite doses) were markedly reduced with full thickness (about 1 mm thick) skin compared with split thickness skin (about 0.5 mm). Maximum flux of propoxur (dissolved in 60% ethanol) was clearly higher through skin of 0.71 mm than through skin of 1.36 mm, but no difference was found between 0.56 and 0.71 mm. The proportion of propoxur present in the membrane after 24 h increased significantly over the complete range of thicknesses tested (0.56-1.36 mm).A complex relationship exists between skin thickness, lipophilicity and percutaneous penetration and distribution. This has implications for risk assessment studies and for the validation of models with data from different sources.