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Construction and curation of a large ecotoxicological dataset for the EcoTTC
Citation:
Beasley, A., M. Barron, S. Belanger, J. Brill, D. De Zwart, M. Embry, B. Farr, A. Kienzler, T. Norberg-King, H. Sanderson, R. Sternberg, AND P. Wilson. Construction and curation of a large ecotoxicological dataset for the EcoTTC. SETAC North America 37th Annual Meeting, Orlando, FL, November 06 - 10, 2016.
Impact/Purpose:
This abstract presentation will summarize the development of a large aquatic toxicity dataset focused on applications to ecological thresholds of toxicological concern (eco-TTC). It is important because it demonstrates a database development approach applicable to tens of thousands of chemicals, and the eco-TTC concept has applicability to EPA's derivation of water quality criteria.
Description:
The Ecological Threshold for Toxicological Concern, or ecoTTC, has been proposed as a natural next step to the well-known human safety TTC concept. The ecoTTC is particularly suited for use as an early screening tool in the risk assessment process, in situations where chemical hazard data is poor, or when an appropriate QSAR is unavailable. EcoTTCs are developed using statistical distributions of Predicted No-Observed Effect Concentrations (PNECs) to reflect the breadth and depth of the ecotoxicological dataset beneath. Therefore, the diversity and quality of the underlying dataset is crucial to the future utility of the ecoTTC. A database consisting of approximately 110,000 unique ecotoxicological records has been created based on recent assessments of published data and international chemical management programs. Stepwise data selection strategies, query systems and curation techniques are applied to ensure a transparent, methodical process towards a final dataset on which to found development of ecoTTCs. Reference-sourced toxicity data is associated with physical chemistry data and taxonomic information for the tested chemical. The resulting dataset contains information on 6200 unique CAS numbers for 1900 species in three taxonomic groups for use in ecoTTC development and associated metadata mining.