Causal, predictive or observational? Different understandings of key event relationships for adverse outcome pathways and their implications on practice
Zhou, Zheng LU
; Pennings, Jeroen
and Sahlin, Ullrika
LU
(2025)
In Environmental Toxicology and Pharmacology
113.
- Abstract
- The Adverse Outcome Pathways (AOPs) framework is pivotal in toxicology, but the, terminology describing Key Event Relationships (KERs) varies within AOP guidelines.This study examined the usage of causal, observational and predictive terms in AOP, documentation and their adaptation in AOP development. A literature search and text, analysis of key AOP guidance documents revealed nuanced usage of these terms, with KERs often described as both causal and predictive. The adaptation of, terminology varies across AOP development stages. Evaluation of KER causality often, relies targeted blocking experiments and weight-of-evidence assessments in the, putative and qualitative stages. Our findings highlight a potential mismatch between,terminology... (More)
- The Adverse Outcome Pathways (AOPs) framework is pivotal in toxicology, but the, terminology describing Key Event Relationships (KERs) varies within AOP guidelines.This study examined the usage of causal, observational and predictive terms in AOP, documentation and their adaptation in AOP development. A literature search and text, analysis of key AOP guidance documents revealed nuanced usage of these terms, with KERs often described as both causal and predictive. The adaptation of, terminology varies across AOP development stages. Evaluation of KER causality often, relies targeted blocking experiments and weight-of-evidence assessments in the, putative and qualitative stages. Our findings highlight a potential mismatch between,terminology in guidelines and methodologies in practice, particularly in inferring,causality from predictive models. We argue for careful consideration of terms like, causal and essential to facilitate interdisciplinary communication. Furthermore, integrating known causality into quantitative AOP models remains a challenge. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/cb45a795-932c-43da-ba40-3cf70c1e5150
- author
- Zhou, Zheng
LU
; Pennings, Jeroen
and Sahlin, Ullrika
LU
- organization
- publishing date
- 2025-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Key event relationships, Adverse outcome pathways, Causal inference, Predictive, Modeling, Non-animal methods, Next generation risk assessment
- in
- Environmental Toxicology and Pharmacology
- volume
- 113
- article number
- 104597
- publisher
- Elsevier
- external identifiers
-
- pmid:39622398
- scopus:85210619760
- ISSN
- 1382-6689
- DOI
- 10.1016/j.etap.2024.104597
- language
- English
- LU publication?
- yes
- id
- cb45a795-932c-43da-ba40-3cf70c1e5150
- date added to LUP
- 2024-12-09 10:17:25
- date last changed
- 2025-04-04 14:54:38
@article{cb45a795-932c-43da-ba40-3cf70c1e5150,
abstract = {{The Adverse Outcome Pathways (AOPs) framework is pivotal in toxicology, but the, terminology describing Key Event Relationships (KERs) varies within AOP guidelines.This study examined the usage of causal, observational and predictive terms in AOP, documentation and their adaptation in AOP development. A literature search and text, analysis of key AOP guidance documents revealed nuanced usage of these terms, with KERs often described as both causal and predictive. The adaptation of, terminology varies across AOP development stages. Evaluation of KER causality often, relies targeted blocking experiments and weight-of-evidence assessments in the, putative and qualitative stages. Our findings highlight a potential mismatch between,terminology in guidelines and methodologies in practice, particularly in inferring,causality from predictive models. We argue for careful consideration of terms like, causal and essential to facilitate interdisciplinary communication. Furthermore, integrating known causality into quantitative AOP models remains a challenge.}},
author = {{Zhou, Zheng and Pennings, Jeroen and Sahlin, Ullrika}},
issn = {{1382-6689}},
keywords = {{Key event relationships; Adverse outcome pathways; Causal inference; Predictive; Modeling; Non-animal methods; Next generation risk assessment}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Environmental Toxicology and Pharmacology}},
title = {{Causal, predictive or observational? Different understandings of key event relationships for adverse outcome pathways and their implications on practice}},
url = {{http://dx.doi.org/10.1016/j.etap.2024.104597}},
doi = {{10.1016/j.etap.2024.104597}},
volume = {{113}},
year = {{2025}},
}