4.5 Article

Profiling the Reproductive Toxicity of Chemicals from Multigeneration Studies in the Toxicity Reference Database

Journal

TOXICOLOGICAL SCIENCES
Volume 110, Issue 1, Pages 181-190

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/toxsci/kfp080

Keywords

pesticides; relational database; reproductive toxicity; toxicity profiling

Categories

Funding

  1. The United States Environmental Protection Agency
  2. Office of Research and Development

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Multigeneration reproduction studies are used to characterize parental and offspring systemic toxicity, as well as reproductive toxicity of pesticides, industrial chemicals and pharmaceuticals. Results from 329 multigeneration studies on 316 chemicals have been digitized into standardized and structured toxicity data within the Toxicity Reference Database (ToxRefDB). An initial assessment of data quality and consistency was performed prior to profiling these environmental chemicals based on reproductive toxicity and associated toxicity endpoints. The pattern of toxicity across 75 effects for all 316 chemicals provided sets of chemicals with similar in vivo toxicity for future predictive modeling. Comparative analysis across the 329 studies identified chemicals with sensitive reproductive effects, based on comparisons to chronic and subchronic toxicity studies, as did the cross-generational comparisons within the multigeneration study. The general pattern of toxicity across all chemicals and the more focused comparative analyses identified 19 parental, offspring and reproductive effects with a high enough incidence to serve as targets for predictive modeling that will eventually serve as a chemical prioritization tool spanning reproductive toxicities. These toxicity endpoints included specific reproductive performance indices, male and female reproductive organ pathologies, offspring viability, growth and maturation, and parental systemic toxicities. Capturing this reproductive toxicity data in ToxRefDB supports ongoing retrospective analyses, test guideline revisions, and computational toxicology research.

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