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.

Children's exposure assessment: a review of factors influencing Children's exposure, and the data available to characterize and assess that exposure.

We review the factors influencing children's exposure to environmental contaminants and the data available to characterize and assess that exposure. Children's activity pattern data requirements are demonstrated in the context of the algorithms used to estimate exposure by inhalation, dermal contact, and ingestion. Currently, data on children's exposures and activities are insufficient to adequately assess multimedia exposures to environmental contaminants. As a result, regulators use a series of default assumptions and exposure factors when conducting exposure assessments. Data to reduce uncertainty in the assumptions and exposure estimates are needed to ensure chemicals are regulated appropriately to protect children's health. To improve the database, advancement in the following general areas of research is required: identification of appropriate age/developmental benchmarks for categorizing children in exposure assessment; development and improvement of methods for monitoring children's exposures and activities; collection of activity pattern data for children (especially young children) required to assess exposure by all routes; collection of data on concentrations of environmental contaminants, biomarkers, and transfer coefficients that can be used as inputs to aggregate exposure models.

Mass-transport models to predict toxicity of inhaled gases in the upper respiratory tract.

Mass transport (the movement of a chemical species) plays an important role in determining toxic responses of the upper respiratory tract (URT) to inhaled chemicals. Mathematical dosimetry models incorporate physical characteristics of mass transport and are used to predict quantitative uptake (absorption rate) and distribution of inhaled gases and vapors in the respiratory tract. Because knowledge of dose is an essential component of quantitative risk assessment, dosimetry modeling plays an important role in extrapolation of animal study results to humans. A survey of existing mathematical dosimetry models for the URT is presented, limitations of current models are discussed, and adaptations of existing models to produce a generally applicable model are suggested. Reviewed URT dosimetry models are categorized as early, lumped-parameter, and distributed- parameter models. Specific examples of other relevant modeling work are also presented.

The challenge of assessing children's residential exposure to pesticides.

In implementing the Food Quality Protection Act (FQPA) the U.S. Environmental Protection Agency (USEPA) has adopted a policy that the exposure factors and models used to assess and predict exposure to pesticides should generally be conservative. Some elements of exposure assessments for FQPA are screening level--they are both uncertain and conservative. If more realistic assessments are to be conducted, then research is required to reduce uncertainty associated with the factors and models used in the exposure assessments. To develop the strategy for conducting this research, critical exposure pathways and factors were identified, and the quality and quantity of data associated with default assumptions for exposure factors were evaluated. Then, based on our current understanding of the pathways that are potentially most important and most uncertain, significant research requirements were identified and prioritized to improve the data available and assumptions used to assess children's aggregate exposure to pesticides. Based on the results of these efforts, four priority research areas were identified: (1) pesticide use patterns in microenvironments where children spend time, (2) temporal and spatial distribution of pesticides following application in a residential setting, (3) dermal and nondietary ingestion exposure assessment methods and exposure factors, (4) dietary exposure assessment methods and exposure factors for infants and young children. The National Exposure Research Laboratory (NERL) research strategy in support of FQPA is designed to address these priority research needs.

Comparison of inhaled formaldehyde dosimetry predictions with DNA-protein cross-link measurements in the rat nasal passages.

Kimbell and coworkers (Toxicol, Appl. Pharmacol, 121, 253-263, 1993) developed a computational fluid dynamics (CFD) model of a F344 rat nasal passage to quantify local wall mass flux (uptake rate) of inhaled chemical. To simulate formaldehyde uptake, Kimbell et al. assumed that mass transfer of formaldehyde from the air into the nasal lining was fast and complete. This was approximated in the CFD model by setting the formaldehyde concentration at the airway walls to zero. Experimental confirmation of formaldehyde mass-flux predictions is desirable if the CFD model is to be used for predicting formaldehyde dosimetry. The purpose of this study was to see if the CFD model predictions of formaldehyde mass flux are consistent with laboratory data on formaldehyde dosimetry. In this study, a mathematical model of the nasal lining was modified to link CFD dosimetry predictions for inhaled formaldehyde with measured tissue disposition of inhaled gas. This model treats the nasal lining as a single, well-stirred compartment, accounts for formaldehyde reaction via saturable and first-order pathways, and allows comparison of model-predicted DNA-protein cross-links (DPX) with regional DPX measured in formaldehyde-exposed rats. Effective Michaelis-Menten kinetic parameters (Vmax = 3040 microM/min and Km = 59 microM) and a pseudo-first-order rate constant for elimination of formaldehyde by nonsaturable pathways (kf = 6 min-1) were estimated (fit) using an average mass flux derived from experimentally measured uptake of formaldehyde. DPX predictions obtained using the estimated kinetic parameters and linking the CFD model to the nasal-lining model compared well with experimentally measured DPX. The close correlation between predicted and measured DPX in the rat nasal passage supports the CFD model predictions of formaldehyde mass flux at the level of resolution provided by the experimental data.

Estimating contaminant dose for intermittent dermal contact: model development, testing, and application.

Assessments of aggregate exposure to pesticides and other surface contamination in residential environments are often driven by assumptions about dermal contacts. Accurately predicting cumulative doses from realistic skin contact scenarios requires characterization of exposure scenarios, skin surface loading and unloading rates, and contaminant movement through the epidermis. In this article we (1) develop and test a finite-difference model of contaminant transport through the epidermis; (2) develop archetypal exposure scenarios based on behavioral data to estimate characteristic loading and unloading rates; and (3) quantify 24-hour accumulation below the epidermis by applying a Monte Carlo simulation of these archetypal exposure scenarios. The numerical model, called Transient Transport through the epiDERMis (TTDERM), allows us to account for variable exposure times and time between exposures, temporal and spatial variations in skin and compound properties, and uncertainty in model parameters. Using TTDERM we investigate the use of a macro-activity parameter (cumulative contact time) for predicting daily (24-hour) integrated uptake of pesticides during complex exposure scenarios. For characteristic child behaviors and hand loading and unloading rates, we find that a power law represents the relationship between cumulative contact time and cumulative mass transport through the skin. With almost no loss of reliability, this simple relationship can be used in place of the more complex micro-activity simulations that require activity data on one- to five-minute intervals. The methods developed in this study can be used to guide dermal exposure model refinements and exposure measurement study design.