The Development of Quantitative AOPs

Schultz, Irvin R.; Watanabe, Karen H.

doi:10.1007/978-3-319-66084-4_13

Cited by 3 publications

(4 citation statements)

References 37 publications

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“…Quantification of AOPs by the empirical approach described here will typically be more feasible than by mechanistic modeling methods based on systems biology (Schultz and Watanabe 2018), given that our approach requires fewer assumptions and can make use of the data more efficiently (Zgheib et al 2019). In comparison with the other mentioned studies that have applied BN modeling for qAOPs, our study combines different benefits from the other studies.…”

Section: Resultsmentioning

confidence: 99%

“…For species like L. minor , for which mechanistic effect and population models are already developed and are being applied for regulatory purposes (Schmitt et al 2013; Hommen et al 2016), incorporating an additional AO node based on population modeling can be a straightforward next step. Furthermore, Murphy et al (2018) and Schultz and Watanabe (2018) have proposed the use of dynamic energy budget (DEB) for linking quantitative AOPs with population‐level responses, using the individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. In the opposite end, the AOP‐BN can be linked to a stressor source through an aggregate exposure pathway, which is a conceptual framework to characterize relationships between stressor source, exposure route, internal exposure (e.g., toxicokinetics) and resulting target exposure (Hines et al 2018; Tan et al 2018).…”

Section: Discussionmentioning

confidence: 99%

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Quantification of an Adverse Outcome Pathway Network by Bayesian Regression and Bayesian Network Modeling

Moe

Wolf

Xie

et al. 2020

Integr Envir Assess & Manag

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This article is part of the special series "Applications of Bayesian Networks for Environmental Risk Assessment and Management" and was generated from a session on the use of Bayesian networks (BNs) in environmental modeling and assessment in 1 of 3 recent conferences: SETAC North America 2018 (Sacramento), SETAC Europe 2019 (Helsinki), and European Geosciences Union 2019 (Vienna). The 3 sessions aimed at showing the state-of-the art and new directions in the use of BN models in environmental assessment, focusing on ecotoxicology and water quality modeling. This series aims at reflecting the broad applicability of BN methodology in environmental assessment across a range of ecosystem types and scales, and discusses the relevance for environmental management.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Quantification of an Adverse Outcome Pathway Network by Bayesian Regression and Bayesian Network Modeling

Moe

Wolf

Xie

et al. 2020

Integr Envir Assess & Manag

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“…Though qualitative AOPs are relevant for hazard identification, moving towards the use of AOPs in risk evaluations also requires quantitative dose-response and time-course information. A relevant new development in this respect are so-called quantitative AOP (qAOP) approaches that focus on the simulation of the dynamic processes linking a MIE with an adverse outcome using different modelling approaches (Conolly et al, 2017;Schultz and Watanabe, 2018;Zgheib et al, 2019). Such qAOPs can be linked to PB(P)K modelling results.…”

Section: Integration Of Nams For Biokinetics In a Nextgeneration Risk Assessment Frameworkmentioning

confidence: 99%

New approach methodologies (NAMs) for human-relevant biokinetics predictions

Punt

Bouwmeester

Blaauboer

et al. 2020

ALTEX

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Whereas much work has been devoted to the development of in vitro screening methods to capture biological effects (toxicodynamics) of chemicals, insight into the absorption, distribution, metabolism and excretion (i.e., ADME/biokinetics) of chemi- IntroductionThere are clear societal and scientific needs for the development and validation of predictive animal-free methods for safety evaluations to prevent adverse effects in humans caused by exposure

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“…Note that in this article, response-response relationships are defined as mathematical functions determined by a regression analysis, whereas in other publications, e.g., Paini et al (2022) , the response-response relationship is defined more broadly to include biologically based models that quantitatively relate two KEs. The merits and pitfalls of the response-response approach and biologically based modeling have been discussed ( Schultz and Watanabe, 2018 ; Foran et al, 2019 ; Zgheib et al, 2019 ; Spinu et al, 2020 ), but a significant barrier to the development of qAOPs in any form is the availability of quantitative data amenable for mathematical model development.…”

Section: Introductionmentioning

confidence: 99%

From Qualitative to Quantitative AOP: A Case Study of Neurodegeneration

2022

Self Cite

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Adverse outcome pathways (AOPs) include a sequence of events that connect a molecular-level initiating event with an adverse outcome at the cellular level for human health endpoints, or at the population level for ecological endpoints. When there is enough quantitative understanding of the relationships between key events in an AOP, a mathematical model may be developed to connect key events in a quantitative AOP (qAOP). Ideally, a qAOP will reduce the time and resources spent for chemical toxicity testing and risk assessment and enable the extrapolation of data collected at the molecular-level by in vitro assays, for example, to predict whether an adverse outcome may occur. Here, we review AOPs in the AOPWiki, an AOP repository, to determine best practices that would facilitate conversion from AOP to qAOP. Then, focusing on a particular case study, acetylcholinesterase inhibition leading to neurodegeneration, we describe specific methods and challenges. Examples of challenges include the availability and collection of quantitative data amenable to model development, the lack of studies that measure multiple key events, and model accessibility or transferability across platforms. We conclude with recommendations for improving key event and key event relationship descriptions in the AOPWiki that facilitate the transition of qualitative AOPs to qAOPs.

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The Development of Quantitative AOPs

Cited by 3 publications

References 37 publications

Quantification of an Adverse Outcome Pathway Network by Bayesian Regression and Bayesian Network Modeling

Quantification of an Adverse Outcome Pathway Network by Bayesian Regression and Bayesian Network Modeling

New approach methodologies (NAMs) for human-relevant biokinetics predictions

From Qualitative to Quantitative AOP: A Case Study of Neurodegeneration

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