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National Institute of Environmental Health Sciences

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Publication Detail

Title: Potential frameworks to support evaluation of mechanistic data for developmental neurotoxicity outcomes: A symposium report.

Authors: Carlson, Laura M; Champagne, Frances A; Cory-Slechta, Deborah A; Dishaw, Laura; Faustman, Elaine; Mundy, William; Segal, Deborah; Sobin, Christina; Starkey, Carol; Taylor, Michele; Makris, Susan L; Kraft, Andrew

Published In Neurotoxicol Teratol, (2020)

Abstract: A key challenge in systematically incorporating mechanistic data into human health assessments is that, compared to studies of apical health endpoints, these data are both more abundant (mechanistic studies routinely outnumber other studies by several orders of magnitude) and more heterogeneous (e.g. different species, test system, tissue, cell type, exposure paradigm, or specific assays performed). A structured decision-making process for organizing, integrating, and weighing mechanistic DNT data for use in human health risk assessments will improve the consistency and efficiency of such evaluations. At the Developmental Neurotoxicology Society (DNTS) 2016 annual meeting, a symposium was held to address the application of existing organizing principles and frameworks for evaluation of mechanistic data relevant to interpreting neurotoxicology data. Speakers identified considerations with potential to advance the use of mechanistic DNT data in risk assessment, including considering the context of each exposure, since epigenetics, tissue type, sex, stress, nutrition and other factors can modify toxicity responses in organisms. It was also suggested that, because behavior is a manifestation of complex nervous system function, the presence and absence of behavioral change itself could be used to organize the interpretation of multiple complex simultaneous mechanistic changes. Several challenges were identified with frameworks and their implementation, and ongoing research to develop these approaches represents an early step toward full evaluation of mechanistic DNT data for assessments.

PubMed ID: 32068112 Exiting the NIEHS site

MeSH Terms: No MeSH terms associated with this publication

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