Skin absorption testing in vitro is a regulatory accepted alternative method (OECD Guideline 428). Different tests can be applied to evaluate the integrity of the skin samples. Here, we compared the pre- or post-run integrity tests (transepidermal electrical resistance, TEER; transepidermal water loss, TEWL; absorption of the reference compounds water, TWF, or methylene blue, BLUE) and additionally focused on co-absorption of a (3)H-labeled internal reference standard (ISTD) as integrity parameter. The results were correlated to absorption profiles of various test compounds. Limit values of 2kΩ, 10 gm(-2)h(-1) and 4.5∗10(-3)cmh(-1) for the standard methods TEER, TEWL and TWF, respectively, allowed distinguishing between impaired and intact human skin samples in general. Single skin samples did, however, not, poorly and even inversely correlate with the test-compound absorption. In contrast, results with ISTD (e.g. (3)H-testosterone) were highly correlated to the absorption of (14)C-labeled test compounds. Importantly, ISTD did not influence analytics or absorption of test compounds. Therefore, ISTD, especially when adjusted to the physico-chemical properties of test compounds, is a promising concept to assess the integrity of skin samples during the whole course of absorption experiments. However, a historical control dataset is yet necessary for a potential routine application.

Dermal absorption is a critical part in the risk assessment of complex mixtures such as agrochemical formulations. To reduce the number of in vivo or in vitro absorption experiments, the present study aimed to develop an in silico prediction model that considers mixture-related effects. Therefore, an experimental ‘real-world’ dataset derived from regulatory in vitro studies with human and rat skin was processed. Overall, 56 test substances applied in more than 150 mixtures were used. Descriptors for the substances as well as the mixtures were generated and used for multiple linear regression analysis. Considering the heterogeneity of the underlying data set, the final model provides a good fit (r² = 0.75) and is able to estimate the influence of a newly composed formulation on dermal absorption of a well-known substance (predictivity Q²_Ext = 0.73). Application of this model would reduce animal and non-animal testings when used for the optimization of formulations in early developmental stages, or would simplify the registration process, if accepted for read-across.