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US-EPA CompTox Chemicals Dashboard providing access to QSAR predictions (QSAR2020)
Citation:
Williams, A., C. Grulke, K. Mansouri, T. Martin, I. Shah, AND G. Patlewicz. US-EPA CompTox Chemicals Dashboard providing access to QSAR predictions (QSAR2020). International Workshop on (Quantitative) Structure-Activity Relationships in Environmental and Health Sciences (QSAR2020), Durham, NC, June 08 - 11, 2020.
Impact/Purpose:
Abstract submitted to the 19th International Workshop on (Quantitative) Structure-Activity Relationships in Environmental and Health Sciences scheduled for June 2020 in Durham NC. This presentation will provide an overview of the dashboard discussing our ongoing efforts to assemble curated data, including data from the literature and online databases and the development and delivery of prediction models. Recent efforts include the prediction of mass spectrometry spectral fragmentation patterns for over 750,000 chemical structures to support chemical identification.
Description:
The US-EPA CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) is a web-based application providing access to various types of data associated with ~880,000 chemical substances. These data include in vivo hazard and in vitro bioactivity data, experimental physicochemical and fate and transport data. Stringent curation processes have been applied for the assembly of the data to deliver high-quality datasets to support the development of QSAR models. The models include: logP, water solubility, bioaccumulation factor, bioconcentration factor, and biodegradation and fish biotransformation half-lives delivered via (T.E.S.T) Toxicity Estimation Software Tools and OPERA predictions. The dashboard also provides access to a Generalized Read-Across (GenRA) module. For chemicals of interest that are not already registered in the dashboard real-time predictions based on structural inputs are available. This presentation will provide an overview of the dashboard discussing our ongoing efforts to assemble curated data, including data from the literature and online databases and the development and delivery of prediction models. Recent efforts include the prediction of mass spectrometry spectral fragmentation patterns for over 750,000 chemical structures to support chemical identification. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.