Suchergebnisse

A transformation of regulatory toxicology is underway to meet the demands of testing increasing numbers of chemicals whilst reducing reliance on in vivo models. This transformation requires a shift from chemical safety assessment largely based on direct empirical observation of apical toxicity outcomes in whole organisms to predictive approaches in which outcomes and risks are inferred from accumulated mechanistic understanding. In the last decade, Adverse Outcome Pathways (AOPs) (Ankley et al., 2010; Ankley and Edwards, 2018) have captured the attention of regulators and researchers alike as a systematic approach for organizing knowledge that may support such inferences (Wittwehr et al., 2017). An AOP is a conceptual structured representation of existing toxicological knowledge describing the causally connected sequence of events, across different levels of biological organization, required to produce an adverse effect when an organism is exposed to a stressor. Specifically, AOPs depict a series of key events (KEs) linking a molecular initiating event (MIE, an interaction between a stressor (e.g., endogenous ligand, xenobiotic) and a biomolecule) to an adverse outcome (AO, at organism or population levels). The causal links between 2 KEs are referred to as key event relationships (KERs). AOPs provide a useful framework to connect mechanistic data to adverse effects on human health or wildlife populations as a basis for the identification of cell- or biochemical-based tests that could fit in Integrated Approaches to Testing and Assessment (IATAs), identifying KEs that could be targeted for the development of New Approach Methods (NAMs), as well as investigating similarities in mechanistic pathways between species. AOPs are also particularly salient for identifying potential Endocrine Disruptors (EDs). Indeed, both the World Health Organization (WHO) and the International Programme on Chemical Safety (IPCS) definition and the scientific criteria adopted by the European Union in 2017 are articulated around three ...

In conjunction with the second International Environmental Omics Symposium (iEOS) conference, held at the University of Liverpool (United Kingdom) in September 2014, a workshop was held to bring together experts in toxicology and regulatory science from academia, government and industry. The purpose of the workshop was to review the specific roles that high-content omics datasets (eg, transcriptomics, metabolomics, lipidomics, and proteomics) can hold within the adverse outcome pathway (AOP) framework for supporting ecological and human health risk assessments. In light of the growing number of examples of the application of omics data in the context of ecological risk assessment, we considered how omics datasets might continue to support the AOP framework. In particular, the role of omics in identifying potential AOP molecular initiating events and providing supportive evidence of key events at different levels of biological organization and across taxonomic groups was discussed. Areas with potential for short and medium-term breakthroughs were also discussed, such as providing mechanistic evidence to support chemical read-across, providing weight of evidence information for mode of action assignment, understanding biological networks, and developing robust extrapolations of species-sensitivity. Key challenges that need to be addressed were considered, including the need for a cohesive approach towards experimental design, the lack of a mutually agreed framework to quantitatively link genes and pathways to key events, and the need for better interpretation of chemically induced changes at the molecular level. This article was developed to provide an overview of ecological risk assessment process and a perspective on how high content molecular-level datasets can support the future of assessment procedures through the AOP framework.