High throughput and in silico methods are providing the regulatory toxicology community with capacity to rapidly and cost effectively generate data concerning a chemical’s ability to initiate one or more biological perturbations that may culminate in an adverse ecological or human health outcome. Translation of those data into scientifically-defensible predictions of outcome that help support regulatory decision-making depends on the ability to efficiently access and assemble the wealth of accumulated toxicological evidence and biological understanding distributed throughout the scientific community. We propose that this challenge can be met through the assembly and description adverse outcome pathway (AOPs) in a common knowledgebase. Adverse outcome pathways are frameworks for organizing knowledge in a manner that supports the extrapolation of mechanistic data, often measured at low levels of biological organization, into regulatory outcomes of concern, typically observed at higher levels of biological organization. A set of key principles and conventions for AOP development have been defined. Computational approaches can be leveraged to support the process of AOP discovery, quantitative prediction of dose-response time course behaviors and transitions between key events, and derivation and analysis of complex networks of AOPs. This presentation will provide an introduction to the AOP framework, key principles of AOP development, and highlight the envisioned role of computational approaches in enabling AOP-based approaches to predictive risk assessment. The contents of this abstract neither constitute nor necessarily represent official US EPA views and policies.
Daniel L. Villeneuve, Ph.D
US EPA Mid-Continent Ecology Division
Daniel L. Villeneuve
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High throughput and in silico methods are providing the regulatory toxicology community with capacity to rapidly and cost effectively generate data concerning a chemical’s ability to initiate one or more biological perturbations that may culminate in an adverse ecological or human health outcome. Translation of those data into scientifically-defensible predictions of outcome that help support regulatory decision-making depends on the ability to efficiently access and assemble the wealth of accumulated toxicological evidence and biological understanding distributed throughout the scientific community. We propose that this challenge can be met through the assembly and description adverse outcome pathway (AOPs) in a common knowledgebase. Adverse outcome pathways are frameworks for organizing knowledge in a manner that supports the extrapolation of mechanistic data, often measured at low levels of biological organization, into regulatory outcomes of concern, typically observed at higher levels of biological organization. A set of key principles and conventions for AOP development have been defined. Computational approaches can be leveraged to support the process of AOP discovery, quantitative prediction of dose-response time course behaviors and transitions between key events, and derivation and analysis of complex networks of AOPs. This presentation will provide an introduction to the AOP framework, key principles of AOP development, and highlight the envisioned role of computational approaches in enabling AOP-based approaches to predictive risk assessment. The contents of this abstract neither constitute nor necessarily represent official US EPA views and policies.
Dr. Daniel L. Villeneuve is a research toxicologist at the US EPA Mid-Continent Ecology Division (MED) in Duluth MN, USA. He earned a BS in Biology and Water Resources from the University of Wisconsin-Steven Point and a Ph.D. in Zoology/Environmental Toxicology from Michigan State University and has worked at MED since 2004. Dr. Villeneuve serves as a project lead for laboratory and field research aimed at the development adverse outcome pathway knowledge and application of that knowledge to support regulatory toxicology. Dr. Villeneuve’s current research is focused on the use of systems biology and ecotoxicogenomic approaches to extend fundamental understanding of the ways in which chemical stressors can interact with the hypothalamic-pituitary-gonadal (HPG)-axis to produce reproductive toxicity in fish and other vertebrates. Dr. Villeneuve has over 15 years of experience conducting freshwater ecotoxicology research and has been recognized with 14 US EPA Scientific and Technological Achievement Awards, two Bronze Medal awards, and is a US National Academy of Sciences and Kavli Foundation Kavli Fellow. He has authored or co-authored over 120 peer-reviewed papers in the field of ecotoxicology and serves as an associate editor of Environmental Toxicology and Chemistry and an international expert advisor on Molecular Screening and Toxicogenomics to the Organization for Economic Cooperation and Development (OECD).