4.1 Article

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

Journal

NEUROTOXICOLOGY AND TERATOLOGY
Volume 78, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ntt.2020.106865

Keywords

Neurotoxicology; Developmental neurotoxicology; Mechanistic toxicology; Risk assessment

Funding

  1. EPA [R835738] Funding Source: Medline
  2. NCRR NIH HHS [G12 RR008124] Funding Source: Medline
  3. NICHD NIH HHS [R21 HD060120] Funding Source: Medline
  4. NIEHS NIH HHS [R01 ES025541, P30 ES007033, R01 ES021534] Funding Source: Medline
  5. NIGMS NIH HHS [SC1 GM111172] Funding Source: Medline
  6. NIMHD NIH HHS [G12 MD007592] Funding Source: Medline
  7. EPA [R835738, 814008] Funding Source: Federal RePORTER

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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.

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