You are here:
Web-based access to experimental and predicted data for environmental fate, transport and toxicity data
Citation:
Williams, A., T. Martin, V. Tkachenko, K. Mansouri, AND Chris Grulke. Web-based access to experimental and predicted data for environmental fate, transport and toxicity data. Presented at American Chemical Society Fall Meeting, Boston, MA, August 19 - 23, 2018. https://doi.org/10.23645/epacomptox.7100747
Impact/Purpose:
Presentation for the American Chemical Society Fall Meeting 2018
Description:
The EPA CompTox Chemistry Dashboard provides access to data associated with ~760,000 chemical substances. The available data includes experimental and predicted physicochemical properties, environmental fate and transport data, in vivo and in silico toxicity data, in vitro bioassay data, exposure data and a variety of other types of information. The data are under continuous expansion and curation and the experimental data have been used to develop QSAR and QSPR models. A number of these models are available via a web interface so that users can submit a chemical structure and predict properties in real time. The dashboard also provides access to pre-compiled chemical lists and categories, including pesticides, and chemicals detected in the environment via non-targeted mass spectrometry analysis. The data are searchable using chemical identifiers (systematic names, trade names, CAS Registry Numbers), by structure, mass and formula. Batch searches allow for data associated with thousands of chemicals to be obtained in a few seconds, with just a few button clicks, and downloaded to the desktop. This presentation will provide an overview of the Dashboard and its applications to accessing source data associated with agriculturally related chemicals. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
URLs/Downloads:
DOI: Web-based access to experimental and predicted data for environmental fate, transport and toxicity data
WEB-BASED ACCESS TO EXPERIMENTAL AND PREDICTED DATA_30_MINS.PDF (PDF, NA pp, 2502.774 KB, about PDF)