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Computational Environmental Sciences and Toxicology
Citation:
Wambaugh, J. Computational Environmental Sciences and Toxicology. Presented at NCSU BIO592, Raleigh, North Carolina, April 15, 2019. https://doi.org/10.23645/epacomptox.8104778
Impact/Purpose:
This is a guest lecture to the North Carolina State University BIO592 course April 2019.
Description:
We would like to know more about the risk posed by thousands of chemicals in the environment – which ones should we start with? High throughput screening (HTS) provides one path forward for identifying potential hazard, but the real world is complicated by toxicokinetics, mixtures, variability (and more). Using in vitro methods developed for pharmaceuticals, we can make useful predictions of TK for large numbers of chemicals. Exposure predictions and data are key to risk-based prioritization. Although exposure is a complex system, certain patterns emerge – in particular, near field (in the home) sources of exposure are important. Consensus modeling provides one path forward, but only as good as available data (at best). Exposure-based priority setting allows the identification of the chemicals most likely to be relevant to the public health. The views expressed in this presentation are those of the author and do not necessarily reflect the views or policies of the US EPA.
URLs/Downloads:
DOI: Computational Environmental Sciences and Toxicology
NCSU-BIO592-WAMBAUGH-041519.PDF (PDF, NA pp, 8721.274 KB, about PDF)