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Mechanistically-based environmental and human health risk assessm | 16612
Journal of Drug Metabolism & Toxicology

Journal of Drug Metabolism & Toxicology
Open Access

ISSN: 2157-7609

+44-20-4587-4809

Mechanistically-based environmental and human health risk assessment: Towards a multi-species, multi-level omics-driven solution for an effective management of chemical risks


International Conference on Toxicogenomics and Drug Monitoring

August 25-27, 2015 Valencia, Spain

Benjamin Pi�?±a

IDAEA-CSIC, Spain

Posters-Accepted Abstracts: J Drug Metab Toxicol

Abstract :

The implementation of environmental quality standards for chemicals has created an enormous waiting-list of chemicals to be assessed for potential environmental and human health hazards. Next-generation assays, both cost effective and timely, are urgently needed to cope with this situation. State of the art omic technologies for performing high-throughput toxicity tests on phylogenetically distant models are one of the most promising approaches in this field. Adverse outcome pathways (AOPs) have been recently proposed as frameworks to link direct, molecular-level initiating events to adverse outcomes at higher levels of biological organization. Once identified, AOPs can be used to develop high-throughput omic technology-based predictive assays, providing valuable information for human and environmental risk assessment. By comparing AOPs across species it would be possible to identify specific and shared mechanisms of toxicity, and hence use this information in understanding and managing environmental risks. New predictive assays and testing strategies are being developed for regulatory (eco)toxicology by analyzing the linkages between direct molecular-level initiating events and adverse effects of regulatory relevance using the conceptual framework of AOPs in different alternative, low-cost models, like Daphnia magna or Danio rerio. This multi-species approach is applied to different levels of organization (from molecular to populations) using transcriptomic, metabolomics, histopathological, behavioral and individual and population growth rate responses. The hope of this framework is to provide an integrated set of tools that can be used to aid management-decision making by improving the capability to gauge environmental stress of contaminants, both for ecosystems and for human populations.

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