Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23778
Title: Evidenced-Based Approaches to Support the Development of Endocrine-Mediated Adverse Outcome Pathways: Challenges and Opportunities
Authors: Audouze, K
Zgheib, E
Abass, K
Baig, A
Forner-Piquer, I
Holbech, H
Knapen, D
Leonards, PE
Lupu, DI
Palaniswamy, S
Rautio, A
Sapounidou, M
Martin, OV
Keywords: adverse outcome pathways;endocrine disruption;systematic (literature) review;machine learning;evidence-based methods
Issue Date: 21-Dec-2021
Publisher: Frontiers Media
Citation: Audouze, K. et al. (2021) 'Evidenced-based approaches to support the development of endocrine-mediated Adverse Outcome Pathways: Challenges and Opportunities', Frontiers in Toxicology, 3, 787017, pp. 1 - 10. doi: 10.3389/ftox.2021.787017.
Abstract: Adverse outcome pathways (AOP) have captured the attention of regulators and researchers alike as a systematic approach for organizing toxicological knowledge. AOPs can help identify Key Events (KE) that could be targeted for the development of New Approach Methods (NAM) and fit in Integrated Approaches to Testing and Assessment, as such they are an integral part of activities within the EURION cluster of projects developing new methods to identify endocrine disrupters. Although AOP development does not currently explicitly require the use of evidence-based methods (EBM), efforts are ongoing to recommend developers document the most important aspects of their process. This perspective article draws on lessons learnt from activities within the EURION cluster to review the circumstances in which EBMs approaches may be most usefully applied to endocrine-mediated (EM) AOP development and opportunities for further research and development of tools tailored to mechanistic evidence gathering and evaluation. We argue that; (1) systematic evidence mapping may support problem formulation in complementing canonical knowledge and identifying key event relationships (KER) for which systematic review (SR) is appropriate, (2) some selected machine learning tools (MLT) are identified as suitable to support the earlier stages of SR adapted to endocrine-mediated AOP development such as problem formulation or the design of search strategies, (3) their implementation for information retrieval ought to be validated and compared with manual methods, (4) whilst the feasibility and desirability of their application to the appraisal of evidence or the evaluation strength of the overall body of evidence is not yet demonstrated.
URI: https://bura.brunel.ac.uk/handle/2438/23778
DOI: https://doi.org/10.3389/ftox.2021.787017
ISSN: 2673-3080
Other Identifiers: 787017
ORCID iD: Asma Baig https://orcid.org/0000-0002-3764-1456
ORCID iD: Isabel Forner-Piquer https://orcid.org/0000-0002-5315-3858
ORCID iD: Olwenn V. Martin https://orcid.org/0000-0003-2724-7882
Appears in Collections:Dept of Social and Political Sciences Research Papers
Dept of Life Sciences Research Papers

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