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A vision and strategy for exposure modelling at the U.S. EPA Office of Research and Development
Citation:
Egeghy, P. A vision and strategy for exposure modelling at the U.S. EPA Office of Research and Development. Cosmetics Europe Long-Range Science Strategy Workshop, Brussels, Belgium, Brussels, BELGIUM, September 21, 2015.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Traditional, hazard-driven, single-chemical risk assessment practices cannot keep pace with the vast and growing numbers of chemicals in commerce. A well-defined, quantitative, and defensible means of identifying those with the greatest risk potential is needed, with exposure considerations providing a critical context for allocation of limited resources. Elevating the role of exposure science in this process, however, requires the development and application of efficient and reliable computational models that make full use of the rich and growing sources of accessible exposure-relevant information. The U.S. EPA Office of Research and Development’s vision for exposure modeling, which we are calling “computational exposure science,” expands the knowledge and current methods used in the field of exposure assessment by bringing in novel data sources and new computational technologies. Computational exposure science represents a frontier of environmental science that is emerging and quickly evolving. This presentation defines the burgeoning discipline, describes a framework for implementation, and reviews some key ongoing research elements that are advancing the science with respect to exposure to chemicals in consumer products. The fundamental elements of computational exposure science include development of reliable, computationally efficient predictive exposure models; identification, acquisition, and application of data to support and evaluate these models; and generation of improved methods for extrapolating across chemicals. Computational exposure science, linked with comparable efforts in toxicology, is ushering in a new era of risk assessment that greatly expands our ability to evaluate chemical safety and sustainability to protect public health.