Integrated Approaches to Testing and Assessment

Worth, Andrew; Patlewicz, Grace

doi:10.1007/978-3-319-33826-2_13

Cited by 22 publications

(25 citation statements)

References 71 publications

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“…First, we consider the similarities and distinctions between AOP networks and other types of complex networks that are commonly analyzed using techniques from graph theory (Trudeau 2013) and network science (Lewis 2009). Using 2 example AOP networks, we illustrate the application of a number of topology-based (Supplemental Data, Box 1) network analyses, and how they can guide our understanding of potential interactions among AOPs, as well as assay development and/or design of alternative testing strategies (e.g., integrated approaches to testing and assessment; Worth and Patlewicz 2016). We then discuss how different strategies may be used to identify the most important paths (called "critical paths"; Supplemental Data, Box 1) through AOP networks.…”

Section: Introductionmentioning

confidence: 99%

Adverse outcome pathway networks II: Network analytics

Villeneuve

Angrish

Fortin

et al. 2018

Enviro Toxic and Chemistry

124

139

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Toxicological responses to stressors are more complex than the simple one-biological-perturbation to one-adverse-outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid in the understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present study introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using 2 example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses (or previously undefined emergent patterns of response) are introduced. Along with a companion article (part I), these concepts set the stage for the development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. The present study addresses one of the major themes identified through a Society of Environmental Toxicology and Chemistry Horizon Scanning effort focused on advancing the AOP framework. Environ Toxicol Chem 2018;37:1734-1748. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

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Section: Introductionmentioning

confidence: 99%

Adverse outcome pathway networks II: Network analytics

Villeneuve

Angrish

Fortin

et al. 2018

Enviro Toxic and Chemistry

124

139

View full text Add to dashboard Cite

show abstract

“…29 Other computational approaches, beyond the ab initio risk assessment consideration, that utilise and extend the AOP framework are the development of Integrated Assessment and Testing Approaches (IATAs). 13,18,[30][31][32][33][34][35][36][37][38] The Links Between in Silico Models and the Different Steps of an AOP Figure 1 illustrates that models, or in silico approaches, may potentially be utilised at all stages of the AOP to provide knowledge and information (it should be noted that the structure of the generic AOP shown in Figure 1 is illustrative only and many AOPs do not include exposure or proceed to the ecosystem level). There are many purposes to the use of models within the AOP framework; these include:…”

Section: Introductionmentioning

confidence: 99%

Relationship Between Adverse Outcome Pathways and Chemistry-BasedIn SilicoModels to Predict Toxicity

Cronin

RicharzAndrea-Nicole

2017

Applied In Vitro Toxicology

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The current landscape of Adverse Outcome Pathways (AOPs) provides a means of organising information relating to the adverse effects elicited following exposure to chemicals. As such, AOPs are an excellent driver for the development and application of in silico models for predictive toxicology allowing for the direct relationship between chemistry and adverse effects to be established. Information may be extracted from AOPs to support the creation of (quantitative) structure-activity relationships ((Q)SARs) as well as to increase confidence in grouping and read-across. Any part of an AOP can be linked to these various types of in silico models. There is, however, an emphasis on using information from known Molecular Initiating Events (MIEs) to create models including 2D and 3D structural alerts, SARs and QSARs. MIEs can be classified according to the nature of the interaction e.g. covalent reactivity, oxidative stress, phototoxicity, chronic receptor mediated, acute enzyme inhibition, unspecific, physical and other effects. Different types of MIEs require different approaches to their in silico modelling. Modelling Key Events and Key Event Relationships is useful if they represent the rate limiting step or key determinant of toxicity. Modelling of metabolism and chemical interactions will become part of AOP networks, which are also driving species-specific extrapolation and respective adaptation of models. With more information and data being captured, in silico approaches will increasingly support the application of knowledge from AOPs to build weight of evidence and support risk assessment, e.g. in the context of Integrated Assessment and Testing Approaches (IATAs).

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“…In relation to transition of toxicity testing, AOPs are considered to provide a helpful ‘working hypothesis’ for data weighting and integration in more targeted and efficient testing strategies, commonly referenced as IATA (integrated approaches to testing and assessment) ( Worth & Patlewicz, 2016 ). IATA encompasses an iterative “fit-for-purpose” approach to address a defined question of hazard, safety or risk assessment within a specific regulatory decision context ( Tollefsen et al, 2014 ).…”

Section: Application Of Moa/aop Including Mechanistically Based Toxicmentioning

confidence: 99%

Adverse outcome pathways: Application to enhance mechanistic understanding of neurotoxicity

Bal‐Price

Meek

2017

Pharmacology & Therapeutics

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Recent developments have prompted the transition of empirically based testing of late stage toxicity in animals for a range of different endpoints including neurotoxicity to more efficient and predictive mechanistically based approaches with greater emphasis on measurable key events early in the progression of disease. The adverse outcome pathway (AOP) has been proposed as a simplified organizational construct to contribute to this transition by linking molecular initiating events and earlier (more predictive) key events at lower levels of biological organization to disease outcomes. As such, AOPs are anticipated to facilitate the compilation of information to increase mechanistic understanding of pathophysiological pathways that are responsible for human disease.In this review, the sequence of key events resulting in adverse outcome (AO) defined as parkinsonian motor impairment and learning and memory deficit in children, triggered by exposure to environmental chemicals has been briefly described using the AOP framework. These AOPs follow convention adopted in an Organization for Economic Cooperation and Development (OECD) AOP development program, publically available, to permit tailored application of AOPs for a range of different purposes.Due to the complexity of disease pathways, including neurodegenerative disorders, a specific symptom of the disease (e.g. parkinsonian motor deficit) is considered as the AO in a developed AOP. Though the description is necessarily limited by the extent of current knowledge, additional characterization of involved pathways through description of related AOPs interlinked into networks for the same disease has potential to contribute to more holistic and mechanistic understanding of the pathophysiological pathways involved, possibly leading to the mechanism-based reclassification of diseases, thus facilitating more personalized treatment.

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Integrated Approaches to Testing and Assessment

Cited by 22 publications

References 71 publications

Adverse outcome pathway networks II: Network analytics

Adverse outcome pathway networks II: Network analytics

Relationship Between Adverse Outcome Pathways and Chemistry-BasedIn SilicoModels to Predict Toxicity

Adverse outcome pathways: Application to enhance mechanistic understanding of neurotoxicity

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