The influence of diffusion cell type and experimental temperature on machine learning models of skin permeability

OBJECTIVES

The aim of this study was to use Gaussian process regression (GPR) methods to quantify the effect of experimental temperature (T_exp ) and choice of diffusion cell on model quality and performance.

METHODS

Data were collated from the literature. Static and flow-through diffusion cell data were separated, and a series of GPR experiments was conducted. The effect of T_exp was assessed by comparing a range of datasets where T_exp either remained constant or was varied from 22 to 45 °C.

KEY FINDINGS

Using data from flow-through diffusion cells results in poor model performance. Data from static diffusion cells resulted in significantly greater performance. Inclusion of data from flow-through cell experiments reduces overall model quality. Consideration of T_exp improves model quality when the dataset used exhibits a wide range of experimental temperatures.

CONCLUSIONS

This study highlights the problem of collating literature data into datasets from which models are constructed without consideration of the nature of those data. In order to optimise model quality data from only static, Franz-type, experiments should be used to construct the model and T_exp should either be incorporated as a descriptor in the model if data are collated from a range of studies conducted at different temperatures.

Effectiveness of hand washing on the removal of iron oxide nanoparticles from human skin ex vivo

In this study, the effectiveness of washing with soap and water in removing nanoparticles from exposed skin was investigated. Dry, nanoscale hematite (α-Fe₂O₃) or maghemite (γ-Fe₂O₃) powder, with primary particle diameters between 20-30 nm, were applied to two samples each of fresh and frozen ex vivo human skin in two independent experiments. The permeation of nanoparticles through skin, and the removal of nanoparticles after washing with soap and water were investigated. Bare iron oxide nanoparticles remained primarily on the surface of the skin, without penetrating beyond the stratum corneum. Skin exposed to iron oxide nanoparticles for 1 and 20 hr resulted in removal of 85% and 90%, respectively, of the original dose after washing. In the event of dermal exposure to chemicals, removal is essential to avoid potential local irritation or permeation across skin. Although manufactured at an industrial scale and used extensively in laboratory experiments, limited data are available on the removal of engineered nanoparticles after skin contact. Our finding raises questions about the potential consequences of nanoparticles remaining on the skin and whether alternative washing methods should be proposed. Further studies on skin decontamination beyond use of soap and water are needed to improve the understanding of the potential health consequences of dermal exposure to nanoparticles.