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Predictive Ecotoxicology in the 21st Century
Citation:
VILLENEUVE, DAN AND N. GARCIA-REYERO. Predictive Ecotoxicology in the 21st Century. Presented at 49th Annual Meeting of SOT, Salt Lake City, UT, March 07 - 11, 2010.
Impact/Purpose:
Ecological risk assessments have long relied on apical data on survival, growth/development, and reproduction, generated in animal toxicity tests and the application of uncertainty factors and conservative (typically) assumptions as a basis for decision-making. However, advances in science and technology and accumulating knowledge regarding both basic biology and mechanisms of toxicity are making it increasingly feasible to use alternative data/endpoints (e.g., biomarkers, in vitro bioassay results, quantitative structure-activity relationships [QSARs]) as a scientifically credible basis for ecological risk assessment. Two key scientific factors standing in the way of routine consideration of such alternative data types in ecological risk assessment are the lack of established linkages between responses measured at the sub-organismal level and those generally regarded to have demographic significance (e.g., survival, development, reproduction) and the lack of appropriate biologically-based extrapolation tools/models. This presentation provides an overview of a SETAC Pellston workshop that considered ways to address these challenges using existing as well as emerging science and technology. A strategy organized around the identification and description of adverse outcome pathways (AOPs) using both traditional hypothesis-driven experimental data and emerging application of ‘omic’ technologies to reverse engineer toxicologically relevant biology is described. We then envision how AOP-based QSARs, in vitro bioassays, and/or biomarkers, coupled with appropriate quantitative extrapolation tools can be organized into a potential 21st century approach to predictive ecotoxicity testing that supports ecological risk assessment.
Description:
Ecological risk assessments have long relied on apical data on survival, growth/development, and reproduction, generated in animal toxicity tests and the application of uncertainty factors and conservative (typically) assumptions as a basis for decision-making. However, advances in science and technology and accumulating knowledge regarding both basic biology and mechanisms of toxicity are making it increasingly feasible to use alternative data/endpoints (e.g., biomarkers, in vitro bioassay results, quantitative structure-activity relationships [QSARs]) as a scientifically credible basis for ecological risk assessment. Two key scientific factors standing in the way of routine consideration of such alternative data types in ecological risk assessment are the lack of established linkages between responses measured at the sub-organismal level and those generally regarded to have demographic significance (e.g., survival, development, reproduction) and the lack of appropriate biologically-based extrapolation tools/models. This presentation provides an overview of a SETAC Pellston workshop that considered ways to address these challenges using existing as well as emerging science and technology. A strategy organized around the identification and description of adverse outcome pathways (AOPs) using both traditional hypothesis-driven experimental data and emerging application of ‘omic’ technologies to reverse engineer toxicologically relevant biology is described. We then envision how AOP-based QSARs, in vitro bioassays, and/or biomarkers, coupled with appropriate quantitative extrapolation tools can be organized into a potential 21st century approach to predictive ecotoxicity testing that supports ecological risk assessment.