Significant progress has been made on predicting dermal
absorption/penetration of topically applied chemicals by developing
quantitative structure permeability relationship (QSPR) models based
on linear free energy relations (LFER). However, all of these efforts
have employed chemicals applied to the skin in aqueous or single
solvent systems, a dosing scenario that does not mimic occupational,
environmental nor pharmaceutical exposure. We have explored two
different approaches to account for chemical mixture / formulation
component effects on skin permeability, one being a computational
approach using QSPR models and the second an experimental approach
using an array of membrane coated fibers (MCF). Both models employ
penetration data obtained from in vitro porcine skin diffusion cells
dosed in mixtures of up to 5 components. The first approach uses
hybrid QSPR equations that describe individual chemical penetration
based on the molecular descriptors for the chemical modified by a
mixture factor (MF) that accounts for the physiochemical properties of
the vehicle/mixture components. The MF is calculated
based on percentage composition of the vehicle/mixture components and
physical chemical properties selected using principal components
analysis. The MCF array approach is based on the similarity in the
absorption mechanisms of the MCF membranes and the stratum corneum of
the skin. A set of probe compounds is used to detect the relative
molecular interaction strengths of chemicals [using the same LFER
framework above] with the vehicle and three MCFs (polydimethylsiloxane
for lipophilic, polyacrylate for polarizable, and CarboWax for polar
interactions). This provides a linkage between the skin permeability
(log kp) and MCF partition coefficients (log Kf). A predictive model
was established via multiple linear regression analysis of the data
matrix of experimentally measured log kp value and log Kf values, as
well as a separate model for predicting mixture effects on changes in
LFER strength coefficients caused by the mixture components for both MCF and
skin. These results suggested that both approaches are capable of
dissecting out the specific physical chemical interactions present
that modulate dermal chemical absorption from a mixture. This approach
holds promise to allow permeability assessments of unknown compounds
to be made using either computational or high-throughput experimental
methods.
For further details see Riviere and Brooks. SAR and QSAR
Environ. Res. 18: 31-44, 2007; Xia et
al. Toxicol. Appl. Pharmacol. 221: 320-328, 2007; Riviere et
al. Toxicol. Sci. 99: 153-161, 2007; Baynes et
al. Chem. Res. Toxicol. 21: 591-599, 2008. (Supported by NIH R01 OH
07555).