| Literature DB >> 32599945 |
James D Ede1, Vladimir Lobaskin2, Ulla Vogel3, Iseult Lynch4, Sabina Halappanavar5, Shareen H Doak6, Megan G Roberts7, Jo Anne Shatkin1.
Abstract
Much of the current innovation in advanced materials is occurring at the nanoscale, specifically in manufactured nanomaterials (MNs). MNs display unique attributes and behaviors, and may be biologically and physically unique, making them valuable across a wide range of applications. However, as the number, diversity and complexity of MNs coming to market continue to grow, assessing their health and environmental risks with traditional animal testing approaches is too time- and cost-intensive to be practical, and is undesirable for ethical reasons. New approaches are needed that meet current requirements for regulatory risk assessment while reducing reliance on animal testing and enabling safer-by-design product development strategies to be implemented. The adverse outcome pathway (AOP) framework presents a sound model for the advancement of MN decision making. Yet, there are currently gaps in technical and policy aspects of AOPs that hinder the adoption and use for MN risk assessment and regulatory decision making. This review outlines the current status and next steps for the development and use of the AOP framework in decision making regarding the safety of MNs. Opportunities and challenges are identified concerning the advancement and adoption of AOPs as part of an integrated approach to testing and assessing (IATA) MNs, as are specific actions proposed to advance the development, use and acceptance of the AOP framework and associated testing strategies for MN risk assessment and decision making. The intention of this review is to reflect the views of a diversity of stakeholders including experts, researchers, policymakers, regulators, risk assessors and industry representatives on the current status, needs and requirements to facilitate the future use of AOPs in MN risk assessment. It incorporates the views and feedback of experts that participated in two workshops hosted as part of an Organization for Economic Cooperation and Development (OECD) Working Party on Manufactured Nanomaterials (WPMN) project titled, "Advancing AOP Development for Nanomaterial Risk Assessment and Categorization", as well as input from several EU-funded nanosafety research consortia.Entities:
Keywords: adverse outcome pathway; decision making; nanomaterials; risk assessment
Year: 2020 PMID: 32599945 PMCID: PMC7353114 DOI: 10.3390/nano10061229
Source DB: PubMed Journal: Nanomaterials (Basel) ISSN: 2079-4991 Impact factor: 5.076
Discussion themes posed to OECD workshop participants.
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Figure 1(A) Generalized AOP showing the relationship between MIE, KEs and AOs, and the KERs that connect them. Bioassays targeting the MIE and KEs in an AOP are characterized or developed as part of an IATA. (B) AOPs can form interlinked networks based on overlapping MIEs, KEs and AOs that better capture the complex biology of disease processes. (From [11]).
Figure 2Scientific papers on AOPs published annually, 2010–2019. PubMed was searched for published papers containing the text words “adverse outcome pathway” on 22 May, 2020. The result for 2020 is estimated given the number of publications that have been published per month.
Figure 3AOPs created in the AOP-KB from 2015–2019 (until May 22, 2020).
Potential applications and benefits of the AOP framework in chemical risk assessment.
| 1. Evaluation of existing information |
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improve chemical grouping and categorization to fill data gaps by read-across |
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utilize data developed from advances in alternative testing strategies, such as in chemico, in vitro, ex vivo and ‘omic’ data, for decision making |
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improve predictivity in safety assessment (e.g., quantitative structure–activity relationships) |
| 2. Identification of data gaps and generation of new data |
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improve high-throughput screening for chemical prioritization |
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identify data gaps to inform relevant research |
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identify novel biomarkers for hazard evaluation |
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develop novel, nonanimal approaches for hazard characterization |
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reduce reliance on animal testing |
| 3. Iterative decision making |
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increase confidence in nontraditional test methods |
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use nontraditional data and methods to improve weight-of-evidence in decision making |
Central Recommendations for Promoting the Development, Use and Acceptance of the AOP Framework for MN Decision Making.
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| 1. Establish the types of data required to develop AOPs for MNs and identify existing NM-relevant AOPs; | 1. Identify similarities and differences in MIEs, KEs and KERs between other emerging advanced materials and MNs [ | 1. Develop data sets for quantitative AOPs (qAOPs) that include consideration of the exposure conditions necessary for MN risk assessment. This includes adopting formal definitions and structures for qAOPs and developing case studies outlining the development and use of qAOPs for MNs; |
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| 1. Evaluate data quality from the peer review literature and current suite of in vitro assays based on identified KEs; | 1. Develop guidance on how the existing nanotoxicity literature, despite its documented limitations (e.g., minimal reporting of physical and chemical characteristics), can be used for AOP development and decision making; | Create processes to continually update publicly available databases as new data is developed. |
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| 1. Identify priority AOs observed with MNs and initiate research into AOP development for these AOs; | 1. Generate data to allow for grouping – data collection/mining to determine the mode of action using MNs that can represent groups of MNs/functionalizations; | 1. Advance modeling and QSAR databases and link to the physical and chemical attributes of MNs; |
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| 1. Review findings of existing data and research on the relationships between physical and chemical properties and MN KEs, including MIEs, AOs and KERs; | 1. Test predictive physical and chemical relationships of MNs to biological outcomes, using carefully controlled changes within and across materials (furthering the work of the projects which inaugurated this effort, such as SmartNanoTox and NanoMILE); | 1. Develop quantitative structure–activity relationships (QSAR) as predictive tools for KEs. |
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| 1. Identify screening-level MN safety decisions that are fit-for-purpose/can rely on AOPs; | 1. Adopt a testing scheme/decision tree for MN grouping and read-across; | 1. Develop guidance and case studies for the use of AOPs in product development decision making, and the implementation of a safe-by-design approach. |
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| 1. Evaluate, advance or develop physical and chemical characterization protocols for MNs and determine how they can be used to identify MIE, KE and AO portions of the AOP framework; | 1. Create voluntary standard methods for IATA; | 1. Develop OECD test guidelines for MNs that relate to MIEs, KEs and AOs; |
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| 1. Assess the strength of evidence for considering dose-response relationships in AOPs as predictive tools for MN risk assessment. | 1. Compare the predictive capability of in vitro assays for MIEs and KEs with in vivo observations or epidemiological data; | 1. Develop and test predictive alternative testing models; |
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| 1. Identify MN-relevant and MN-specific AOPs, KEs and KERs, including assessments of the AOPs which have been officially OECD-endorsed, approved or are under review and under active development for MN-relevance (e.g., | 1. Develop and validate an IATA based on KEs, KERs and AOPs that can be used in risk assessments of new nanoscale materials. This includes identifying and prioritizing which KEs are critical for testing as part of an IATA, building on the work currently ongoing in NanoSolveIT; | 1. Incorporate technical developments into specific regulatory guidance/policy documents. |
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| 1. Develop communication and educational materials on the use of the AOP framework for MN decision making for nontechnical stakeholders; | ||