Abstract
An adverse outcome pathway (AOP) is a conceptual framework that organizes existing knowledge concerning biologically plausible, and empirically supported, links between molecular-level perturbation of a biological system and an adverse outcome at a level of biological organization of regulatory relevance. Systematic organization of information into AOP frameworks has potential to improve regulatory decision-making through greater integration and more meaningful use of mechanistic data. However, for the scientific community to collectively develop a useful AOP knowledgebase that encompasses toxicological contexts of concern to human health and ecological risk assessment, it is critical that AOPs be developed in accordance with a consistent set of core principles. Based on the experiences and scientific discourse among a group of AOP practitioners, we propose a set of five fundamental principles that guide AOP development: (1) AOPs are not chemical specific; (2) AOPs are modular and composed of reusable components-notably key events (KEs) and key event relationships (KERs); (3) an individual AOP, composed of a single sequence of KEs and KERs, is a pragmatic unit of AOP development and evaluation; (4) networks composed of multiple AOPs that share common KEs and KERs are likely to be the functional unit of prediction for most real-world scenarios; and (5) AOPs are living documents that will evolve over time as new knowledge is generated. The goal of the present article was to introduce some strategies for AOP development and detail the rationale behind these 5 key principles. Consideration of these principles addresses many of the current uncertainties regarding the AOP framework and its application and is intended to foster greater consistency in AOP development.
Original language | English |
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Pages (from-to) | 312-320 |
Number of pages | 0 |
Journal | Toxicol Sci |
Volume | 142 |
Issue number | 2 |
DOIs | |
Publication status | Published - Dec 2014 |
Keywords
- adverse outcome pathway
- extrapolation
- knowledgebase
- predictive toxicology
- regulatory toxicology
- Animals
- Biomedical Research
- Databases
- Factual
- Humans
- Models
- Biological
- Toxicology