How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology.
Average rating
Cast your vote
You can rate an item by clicking the amount of stars they wish to award to this item.
When enough users have cast their vote on this item, the average rating will also be shown.
Star rating
Your vote was cast
Thank you for your feedback
Thank you for your feedback
Authors
Wittwehr, ClemensAladjov, Hristo
Ankley, Gerald
Byrne, Hugh J
de Knecht, Joop
Heinzle, Elmar
Klambauer, Günter
Landesmann, Brigitte
Luijten, Mirjam
MacKay, Cameron
Maxwell, Gavin
Meek, M E Bette
Paini, Alicia
Perkins, Edward
Sobanski, Tomasz
Villeneuve, Dan
Waters, Katrina M
Whelan, Maurice
Type
ArticleLanguage
en
Metadata
Show full item recordTitle
How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology.Published in
Toxicol Sci 2017; 155(2):326-36Publiekssamenvatting
Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24-25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment.PMID
27994170ae974a485f413a2113503eed53cd6c53
10.1093/toxsci/kfw207
Scopus Count
Collections
The following license files are associated with this item:
Related articles
- A Pragmatic Approach to Adverse Outcome Pathway Development and Evaluation.
- Authors: Svingen T, Villeneuve DL, Knapen D, Panagiotou EM, Draskau MK, Damdimopoulou P, O'Brien JM
- Issue date: 2021 Nov 24
- Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology.
- Authors: Groh KJ, Carvalho RN, Chipman JK, Denslow ND, Halder M, Murphy CA, Roelofs D, Rolaki A, Schirmer K, Watanabe KH
- Issue date: 2015 Feb
- A high-level overview of the OECD AOP Development Programme.
- Authors: Chauhan V, Hamada N, Wilkins R, Garnier-Laplace J, Laurier D, Beaton D, Tollefsen KE
- Issue date: 2022
- Adverse outcome pathway: a path toward better data consolidation and global co-ordination of radiation research.
- Authors: Chauhan V, Beaton D, Hamada N, Wilkins R, Burtt J, Leblanc J, Cool D, Garnier-Laplace J, Laurier D, Le Y, Yamada Y, Tollefsen KE
- Issue date: 2022
- Adverse outcome pathways: From research to regulation scientific workshop report.
- Authors: Kleinstreuer NC, Sullivan K, Allen D, Edwards S, Mendrick DL, Embry M, Matheson J, Rowlands JC, Munn S, Maull E, Casey W
- Issue date: 2016 Apr