Applying the skin sensitisation adverse outcome pathway (AOP) to quantitative risk assessment

Maxwell, Gavin; MacKay, Cameron; Cubberley, Richard; Davies, Michael J.; Gellatly, Nichola; Glavin, Stephen; Gouin, Todd; Jacquoilleot, Sandrine; Moore, Craig S.; Pendlington, Ruth; Saib, Ouarda; Sheffield, David; Stark, Richard; Summerfield, Vicki

doi:10.1016/j.tiv.2013.10.013

Cited by 64 publications

(43 citation statements)

References 26 publications

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“…Most of the time, only results from animal studies are reaction is required or to distinguish between skin and respiratory sensitizers (Rovida et al, 2013). Mathematical models have been proposed to quantitatively establish a relationship between the dose of sensitizer applied to the skin and the possible human adverse effect (Maxwell et al, 2014).…”

Section: The Example Of Skin Sensitizationmentioning

confidence: 99%

Integrated testing strategies (ITS) for safety assessment

Rovida

2015

ALTEX

147

128

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SummaryIntegrated testing strategies (ITS), as opposed to a single definitive test or fixed batteries of tests, are expected to efficiently combine different information sources in a quantifiable fashion to satisfy an information need, in this case for regulatory safety assessments. With increasing awareness of the limitations of each individual tool and the development of highly targeted tests and predictions, the need for combining pieces of evidence increases. The discussions that took place during this workshop, which brought together a group of experts coming from different related areas, illustrate the current state of the art of ITS, as well as promising developments and identifiable challenges. The case of skin sensitization was taken as an example to understand how possible ITS can be constructed, optimized and validated. This will require embracing and developing new concepts such as adverse outcome pathways (AOP), advanced statistical learning algorithms and machine learning, mechanistic validation and "Good ITS Practices".Keywords: in vitro methods, testing strategy, Tox21c, skin sensitization, computational toxicology this is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is appropriately cited. *A report of t 4 -the transatlantic think tank for toxicology, a collaboration of the toxicologically oriented chairs in Baltimore, Konstanz and Utrecht sponsored by the Doerenkamp-Zbinden Foundation; participants do not represent their institutions and do not necessarily endorse all recommendations made.

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Section: The Example Of Skin Sensitizationmentioning

confidence: 99%

Integrated testing strategies (ITS) for safety assessment

Rovida

2015

ALTEX

147

128

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“…Intermediate KEs in the AOP capture processes related to the induction of inflammatory cytokines by dendritic cells and keratinocytes, and activation and proliferation of T-cells that ultimately cause sensitization (Kimber et al , 2012). The scientific support for this AOP is considered to be strong (Patlewicz et al , 2015; Perkins et al , 2015) so it also offers an excellent basis for development of quantitative models relating the MIE to the AO (Maxwell et al , 2014). In particular, there is a strong regulatory and scientific interest in applying mechanistic understanding captured in the AOP to help reduce and replace the need for animal testing associated with the hazard characterization and risk assessment of skin sensitizing chemicals for use in cosmetic and other consumer care products (eg, soaps, lotions).…”

Section: Case Examples Of Aop-informed Computational Prediction Modelsmentioning

confidence: 99%

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology

Wittwehr¹,

Aladjov²,

Ankley³

et al. 2016

Toxicol. Sci.

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135

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Efforts are underway to transform regulatory toxicology and chemical safety assessment from a largely empirical science based on direct observation of apical toxicity outcomes in whole organism toxicity tests to a predictive one in which outcomes and risk are inferred from accumulated mechanistic understanding. The adverse outcome pathway (AOP) framework provides a systematic approach for organizing knowledge that may support such inference. Likewise, computational models of biological systems at various scales provide another means and platform to integrate current biological understanding to facilitate inference and extrapolation. We argue that the systematic organization of knowledge into AOP frameworks can inform and help direct the design and development of computational prediction models that can further enhance the utility of mechanistic and in silico data for chemical safety assessment. This concept was explored as part of a workshop on AOP-Informed Predictive Modeling Approaches for Regulatory Toxicology held September 24–25, 2015. Examples of AOP-informed model development and its application to the assessment of chemicals for skin sensitization and multiple modes of endocrine disruption are provided. The role of problem formulation, not only as a critical phase of risk assessment, but also as guide for both AOP and complementary model development is described. Finally, a proposal for actively engaging the modeling community in AOP-informed computational model development is made. The contents serve as a vision for how AOPs can be leveraged to facilitate development of computational prediction models needed to support the next generation of chemical safety assessment.

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“…A quantitative model describing the responseresponse relationships among the KEs in the AOP allows AO predictions based on the MIE measurements with caveats regarding the potential for modulating factors that modify the response-response relationships in certain sensitive groups. The skin sensitization AOP has been incorporated into a combined model including toxicokinetics and dose-response informed by high-throughput screening assays as a proof of concept for this application (Maxwell et al, 2014).…”

Section: Applications For the Aop/moa Frameworkmentioning

confidence: 99%

Adverse Outcome Pathways--Organizing Toxicological Information to Improve Decision Making

Edwards

Tan

Villeneuve

et al. 2015

Journal of Pharmacology and Experimental Therapeutics

172

126

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The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High-throughput screening commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a framework for connecting high-throughput toxicity testing (HTT) and other results to potential impacts on human and wildlife populations. As a result of international efforts, the AOP development process is now well-defined and efforts are underway to broaden the participation through outreach and training. One key principle is that AOPs represent the chemical-agnostic portions of pathways to increase the generalizability of their application from early key events to overt toxicity. The closely related mode of action framework extends the AOP as needed when evaluating the potential risk of a specific chemical. This in turn enables integrated approaches to testing and assessment (IATA), which incorporate results of assays at various levels of biologic organization such as in silico; HTT; chemical-specific aspects including absorption, distribution, metabolism, and excretion (ADME); and an AOP describing the biologic basis of toxicity. Thus, it is envisaged that provision of limited information regarding both the AOP for critical effects and the ADME for any chemical associated with any adverse outcome would allow for the development of IATA and permit more detailed AOP and ADME research, where higher precision is needed based on the decision context.

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Applying the skin sensitisation adverse outcome pathway (AOP) to quantitative risk assessment

Cited by 64 publications

References 26 publications

Integrated testing strategies (ITS) for safety assessment

Integrated testing strategies (ITS) for safety assessment

How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology

Adverse Outcome Pathways--Organizing Toxicological Information to Improve Decision Making

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