Spectral Reflectance Measurement of Evaporating Chemical Films: Initial Results and Application to Skin Permeation

A compartment model to predict in vitro finite dose absorption of chemicals by human skin

Dermal uptake is an important and complex exposure route for a wide range of chemicals. Dermal exposure can occur due to occupational settings, pharmaceutical applications, environmental contamination, or consumer product use. The large range of both chemicals and scenarios of interest makes it difficult to perform generalizable experiments, creating a need for a generic model to simulate various scenarios. In this study, a model consisting of a series of four well-mixed compartments, representing the source solution (vehicle), stratum corneum, viable tissue, and receptor fluid, was developed for predicting dermal absorption. The model considers experimental conditions including small applied doses as well as evaporation of the vehicle and chemical. To evaluate the model assumptions, we compare model predictions for a set of 26 chemicals to finite dose in-vitro experiments from a single laboratory using steady-state permeability coefficient and equilibrium partition coefficient data derived from in-vitro experiments of infinite dose exposures to these same chemicals from a different laboratory. We find that the model accurately predicts, to within an order of magnitude, total absorption after 24 h for 19 of these chemicals. In combination with key information on experimental conditions, the model is generalizable and can advance efficient assessment of dermal exposure for chemical risk assessment.

Impact of solvent dry down, vehicle pH and slowly reversible keratin binding on skin penetration of cosmetic relevant compounds: I. Liquids

To measure progress and evaluate performance of the newest UB/UC/P&G skin penetration model we simulated an 18-compound subset of finite dose in vitro human skin permeation data taken from a solvent-deposition study of cosmetic-relevant compounds (Hewitt et al., J. Appl. Toxicol. 2019, 1-13). The recent model extension involved slowly reversible binding of solutes to stratum corneum keratins. The selected subset was compounds that are liquid at skin temperature. This set was chosen to distinguish between slow binding and slow dissolution effects that impact solid phase compounds. To adequately simulate the physical experiments there was a need to adjust the evaporation mass transfer coefficient to better represent the diffusion cell system employed in the study. After this adjustment the model successfully predicted both dermal delivery and skin surface distribution of 12 of the 18 compounds. Exceptions involved compounds that were cysteine-reactive, highly water-soluble or highly ionized in the dose solution. Slow binding to keratin, as presently parameterized, was shown to significantly modify the stratum corneum kinetics and diffusion lag times, but not the ultimate disposition, of the more lipophilic compounds in the dataset. Recommendations for further improvement of both modeling methods and experimental design are offered.

Compartmental modeling of skin absorption and desorption kinetics: Donor solvent evaporation, variable diffusion/partition coefficients, and slow equilibration process within stratum corneum

This work expands the recently developed compartmental model for skin transport to model variable diffusion and/or partition coefficients, and the presence of slow equilibration/slow binding kinetics within stratum corneum. The model was validated by comparing it with the diffusion model which was solved numerically using the finite element method. It was found that the new compartmental model predictions agreed well with that of the diffusion model, providing a sufficient number of compartments was used. The compartmental model was applied to two previously published experimental data sets: water penetration and desorption data and the finite dose dermal penetration of testosterone. Significant improvement of the fitting quality for all these data sets was achieved using the compartmental model.