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ICCVAM Biennial Report 2014-2015

ICCVAM Biennial Report 2014-2015
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https://ntp.niehs.nih.gov/go/795452

Research and Development: Tox21 Activities

The interagency Tox21 research initiative uses in vitro high throughput screening (HTS) assays to test a broad variety of substances and considers data from those screens collectively to assess effects on biological pathways related to toxicity. Data from Tox21 testing will be used to develop a better understanding of adverse outcome pathways, enabling the eventual use of in vitro assay data to predict the adverse effects of chemical exposures in vivo. The goals of Tox21 are to efficiently prioritize chemicals for in vivo testing and to use results from validated HTS assays to identify endpoints for targeted in vivo testing.

  • A crowdsourcing initiative known as the DREAM Toxicogenetics Collaboration tested how well the effects of a toxic compound could be predicted in different people. Hundreds of computational biologists from all over the world developed approaches to predicting the toxicities of environmental compounds. The collaboration showed that computational methods could be used to predict some toxic effects on populations; however, these methods are not yet sensitive enough to predict such effects in individuals. The collaboration resulted in the development of algorithms useful for environmental risk assessment as well as new methods for improving some areas of hazard evaluation and assessment.
  • Scientists from Tox21 partner agencies developed a list of genes to use for evaluating transcriptional changes in human cells or tissues in response to chemical exposures in a high throughput format. The “S1500+” gene list, containing approximately 2750 genes, was derived through bioinformatic approaches, experimental data, and public nominations. These genes may also be useful for biomarker development and basic research efforts.
More information about Tox21 can be found on participating agencies’ websites: NIEHS/NTP, NIH/National Center for Advancing Translational Sciences, and EPA/National Center for Computational Toxicology.
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