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Read-across to rank skin sensitization potential: subcategories for the Michael acceptor domain
Background: Eliminating animal testing for skin sensitization is a significant challenge in consumer safety risk assessment. To be able to perform resilient risk assessments in the future, one will need alternative approaches to fill the data gaps. Objectives: To this end, we propose a subcategory...
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Published in: | Contact dermatitis 2009-01, Vol.60 (1), p.21-31 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Background: Eliminating animal testing for skin sensitization is a significant challenge in consumer safety risk assessment. To be able to perform resilient risk assessments in the future, one will need alternative approaches to fill the data gaps.
Objectives: To this end, we propose a subcategory‐based read‐across approach to estimate and rank skin sensitization potential of chemicals. The example described here is for the mechanism of Michael‐type nucleophilic addition with subcategories being limited to carbonyl‐containing compounds.
Patients/Methods: In this approach, in silico tools based on structural alerts were used to determine both the mechanism of protein binding and the relative subcategories within that mechanism.
Results: Fifty compounds previously evaluated in the in vivo mouse local lymph node assay (LLNA) were placed in 10 subcategories defined by their polarized α,β‐unsaturated substructure. To offset the limitations and skewness of the published in vivo data, in chemico glutathione (GSH) depletion data also were included.
Conclusions: It was shown that the read‐across approach can be successfully used to rank qualitatively skin sensitization potential of an untested carbonyl‐containing Michael acceptor chemical by using subcategories. Moreover, the use of the more resilient in chemico GSH depletion data added further support to the read‐across result. |
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ISSN: | 0105-1873 1600-0536 |
DOI: | 10.1111/j.1600-0536.2008.01473.x |