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Advances on a Decision Analytic Approach to Exposure-Based Chemical Prioritization
Authors:Matthew D Wood  Kenton Plourde  Sabrina Larkin  Peter P Egeghy  Antony J Williams  Valerie Zemba  Igor Linkov  Daniel A Vallero
Institution:1. U.S. Army Engineer Research and Development Center, Environmental Laboratory, Concord, MA, USA;2. Brigham and Women's Hospital, Boston, MA, USA;3. Contractor to U.S. Army Engineer Research and Development Center, Environmental Laboratory, Concord, MA, USA;4. U.S. Environmental Protection Agency, National Exposure Research Laboratory, RTP, NC, USA;5. U.S. Environmental Protection Agency, National Computational Toxicology Center, RTP, NC, USA;6. U.S. Environmental Protection Agency, National Exposure Research Laboratory, RTP, NC, USA

Duke University, Department of Civil & Environmental Engineering, Durham, NC, USA

Abstract:The volume and variety of manufactured chemicals is increasing, although little is known about the risks associated with the frequency and extent of human exposure to most chemicals. The EPA and the recent signing of the Lautenberg Act have both signaled the need for high-throughput methods to characterize and screen chemicals based on exposure potential, such that more comprehensive toxicity research can be informed. Prior work of Mitchell et al. using multicriteria decision analysis tools to prioritize chemicals for further research is enhanced here, resulting in a high-level chemical prioritization tool for risk-based screening. Reliable exposure information is a key gap in currently available engineering analytics to support predictive environmental and health risk assessments. An elicitation with 32 experts informed relative prioritization of risks from chemical properties and human use factors, and the values for each chemical associated with each metric were approximated with data from EPA's CP_CAT database. Three different versions of the model were evaluated using distinct weight profiles, resulting in three different ranked chemical prioritizations with only a small degree of variation across weight profiles. Future work will aim to include greater input from human factors experts and better define qualitative metrics.
Keywords:Engineering risk analytics  expert elicitation  exposure science  multicriteria decision analysis  screening prioritization
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