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Catalog and link chemical profile to models

Description:

EPA’s Office of Chemical Safety and Pollution Prevention (OCSPP) is moving towards more Integrated Approaches to Testing and Assessment (IATA) for human health and ecological risk assessment of pesticides. With mechanistically-based Quantitative Structure-Activity Relationships (QSARs) being identified as an important component in meeting this goal under 40CFR158W, OCSPP proposed revised testing requirements for antimicrobial agents including a new optional guideline for submission of QSAR analyses. OCSPP has also proposed use of QSARs to fill data gaps, particularly for pesticide degradation products, where little or no empirical data are available from the registrant or via empirical data bases. Although reliable QSAR tools exist, most were developed in support of Toxic Substances Control Act (TSCA) legislation, and therefore do not include models that focus on Adverse Outcome Pathways (AOPs) relevant to pesticide parent and/or degradation compounds. Since many of the pesticide active ingredients have a known molecular site of action for the target pest, an AOP approach will be used when developing the models, and will be supported by a taxonomically-based look-up tool for Mode Of Action (MOA). Task will develop an MOA assignment methodology for organic substances, drawing from existing chemical inventories including the ToxCast database, and pesticide active ingredient list. New MOA-based QSAR models will be developed with the goal of reducing uncertainty in toxicity estimation for diverse chemicals for application in OCSPP risk assessments and hazard screenings.

Rationale and Research Approach:

Rationale: The development of acute MOA tools for estimating potency of pesticides and other chemicals in aquatic and terrestrial species is among the highest priority research needs of OCSPP. This work will deliver several high priority tools, including an MOA look-up tool for pesticides Office of Pesticide Programs (OPP), which will be expanded to include ToxCast chemicals. The research will also provide MOA-specific QSAR models to predict acute toxicity in aquatic and wildlife species. This work links to Systems Models by providing a searchable MOA database, and to Dashboards and Life Cycle Considerations by providing new MOA-based QSAR models for deployment. Approach: This cross-Office of Research and Development (ORD) collaboration with scientists from National Center for Computational Toxicology (NCCT), National Center for Environmental Assessment (NCEA), National Exposure Research Laboratory (NERL), National Health and Environmental Effects Research Laboratory (NHEERL), and National Risk Managerment Research Laboratory (NRMRL) will apply their respective expertise and knowledge toward an integrated, transdisciplinary project by developing MOA based tools to support OCSPPs ecological risk assessments. The task will develop a database and lookup tool linking inherent chemical property (ICP) data to MOA information or biological activity, by major taxonomic groups. The task will also curate data for use in model development, and subsequently, develop and validate new predictive QSAR models and tools to fill existing and developing model gaps. The outputs from this research will allow application of ICP to future risk assessment needs, including the evaluation of chemicals and their potential alternatives from a molecular level in order to promote sustainability by reducing or eliminating the use and generation of hazardous substances. Modeling applications that will be developed in this project include a MOA look-up tool and mechanistically-based QSAR models focusing initially on pesticides but expanding to include other chemicals of priority to the Agency, including ToxCast compounds. Critical to the application of the approaches used in this effort, is having an understanding of the domain of applicability of these QSAR models, ICP information of the model sets, and the ability to identify chemicals that have similar MOAs. The MOA look-up tool will be used to help assign MOAs for chemicals, expanding on the existing ASTER software. Further research will be initiated to identify how conserved the acute MOA is across selected taxonomic hierarchy. MOAs assignments will also be used to create more refined QSAR toxicity estimations. Once the MOA prediction models are validated, QSARs will be developed based on these specific MOAs with an initial focus on aquatic species but will later expanding to terrestrial species. These tools will be linked, via the Chemical Safety for Sustainability (CSS) Dashboard, to EPA databases (e.g. ECOTOX, ToxRefDB) allowing risk assessors to estimate relative potency of pesticides and non-pesticides for the index of most sensitive species. This research effort will deliver tools that can be used in the evaluation of new chemicals, which can be used by OCSPP. Also, the models and tools developed here will feed into the tools developed within Life Cycle Considerations to improve their sustainability assessments.

MED Contacts:

Richard Kolanczyk

Publications:

Russom, C.L. 2014. AOP description: Acetylcholinesterase inhibition. (Report to be submitted to the OECD Extended Advisory Group on Molecular Screening and Toxicogenomics; part of the adverse outcome pathway development work plan.)

Martin, T.M., C.M. Grulke, D.M. Young, C.L. Russom, N.Y. Wang, C.R. Jackson, and M.G. Barron. 2013. Prediction of aquatic toxicity mode of action using linear discriminant and random forest models. Journal of Chemical Information and Modeling 53:2229-2239.

Russom, C.L. 2013. US EPA pesticide acute MOA database: Overview of procedures used in compiling the database and summary of results.

Russom, C.L., S.P. Bradbury, S.J. Broderius, D.J. Hammermeister, R.A. Drummond, and G.D. Veith. 2013. Predicting modes of toxic action from chemical structure. Environmental Toxicology and Chemistry 32:1441-1442.

Expected Products:

Date

Product

Contact

  Pending.  

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