Document Detail


A mechanistic approach to modelling respiratory sensitization.
MedLine Citation:
PMID:  24422459     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Chemical respiratory sensitization is an important occupational health problem which may lead to severely incapacitated human health yet there are currently no validated or widely accepted models for identifying and characterizing the potential of a chemical to induce respiratory sensitization. This is in part due to on-going uncertainty about the immunological mechanisms through which respiratory sensitization may be acquired. Despite the lack of test method, regulations such as REACH still require an assessment of respiratory sensitization for risk assessment and/or for the purposes of classification and labelling. The REACH guidance describes an integrated evaluation strategy to characterize what information sources could be available to facilitate such an assessment. The components of this include a consideration of well-established structural alerts and existing data (whether it be derived from read-across, (Quantitative) Structure Activity Relationships ((Q)SAR), in vivo studies etc.). There has been some progress in developing SARs as well as a handful of empirical QSARs. More recently efforts have been focused on exploring whether the reaction chemistry mechanistic domains first characterized for skin sensitization are relevant for respiratory sensitization and to what extent modifications or refinements are needed to rationalize the differences between the two endpoints as far as their chemistry is concerned. This study has built upon the Adverse Outcome Pathway (AOP) for skin sensitization that was developed and published by the OECD in 2012. We have structured a workflow to characterize the initiating events that are relevant in driving respiratory sensitization. OASIS pipeline technology was used to encode these events as components in a software platform to enable a prediction of respiratory sensitization potential to be made for new untested chemicals. This prediction platform could be useful in the assessment of respiratory sensitization potential or for grouping chemicals for subsequent read-across.
Authors:
Ovanes Garo Mekenyan; Grace Y Patlewicz; Chanita Kuseva; Ioanna Popova; Aycel Mehmed; Stefan Kotov; Teodor Zhechev; Todor Pavlov; Stanislav Temelkov; David W Roberts
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-1-14
Journal Detail:
Title:  Chemical research in toxicology     Volume:  -     ISSN:  1520-5010     ISO Abbreviation:  Chem. Res. Toxicol.     Publication Date:  2014 Jan 
Date Detail:
Created Date:  2014-1-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8807448     Medline TA:  Chem Res Toxicol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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