Literature DB >> 24422459

A mechanistic approach to modeling respiratory sensitization.

Ovanes Mekenyan1, Grace Patlewicz, Chanita Kuseva, Ioanna Popova, Aycel Mehmed, Stefan Kotov, Teodor Zhechev, Todor Pavlov, Stanislav Temelkov, David W Roberts.   

Abstract

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 the ongoing 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 labeling. 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 end points 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.

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Year:  2014        PMID: 24422459     DOI: 10.1021/tx400345b

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  10 in total

1.  Predicting the future: opportunities and challenges for the chemical industry to apply 21st-century toxicity testing.

Authors:  Raja S Settivari; Nicholas Ball; Lynea Murphy; Reza Rasoulpour; Darrell R Boverhof; Edward W Carney
Journal:  J Am Assoc Lab Anim Sci       Date:  2015-03       Impact factor: 1.232

Review 2.  Skin and respiratory chemical allergy: confluence and divergence in a hybrid adverse outcome pathway.

Authors:  Ian Kimber; Alan Poole; David A Basketter
Journal:  Toxicol Res (Camb)       Date:  2018-01-26       Impact factor: 3.524

3.  Modeling and insights into molecular basis of low molecular weight respiratory sensitizers.

Authors:  Xueyan Cui; Rui Yang; Siwen Li; Juan Liu; Qiuyun Wu; Xiao Li
Journal:  Mol Divers       Date:  2020-03-12       Impact factor: 2.943

4.  Gas-phase reaction products and yields of terpinolene with ozone and nitric oxide using a new derivatization agent.

Authors:  Jason E Ham; Stephen R Jackson; Joel C Harrison; J R Wells
Journal:  Atmos Environ (1994)       Date:  2015-12       Impact factor: 4.798

5.  In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities.

Authors:  Arianna Bassan; Vinicius M Alves; Alexander Amberg; Lennart T Anger; Lisa Beilke; Andreas Bender; Autumn Bernal; Mark T D Cronin; Jui-Hua Hsieh; Candice Johnson; Raymond Kemper; Moiz Mumtaz; Louise Neilson; Manuela Pavan; Amy Pointon; Julia Pletz; Patricia Ruiz; Daniel P Russo; Yogesh Sabnis; Reena Sandhu; Markus Schaefer; Lidiya Stavitskaya; David T Szabo; Jean-Pierre Valentin; David Woolley; Craig Zwickl; Glenn J Myatt
Journal:  Comput Toxicol       Date:  2021-09-13

6.  Application of the direct peptide reactivity assay (DPRA) to inorganic compounds: a case study of platinum species.

Authors:  Jocelyn D C Hemming; Mark Hosford; Martin M Shafer
Journal:  Toxicol Res (Camb)       Date:  2019-11-20       Impact factor: 3.524

7.  A new agent for derivatizing carbonyl species used to investigate limonene ozonolysis.

Authors:  J R Wells; Jason E Ham
Journal:  Atmos Environ (1994)       Date:  2014-12       Impact factor: 4.798

Review 8.  In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts.

Authors:  Hongbin Yang; Lixia Sun; Weihua Li; Guixia Liu; Yun Tang
Journal:  Front Chem       Date:  2018-02-20       Impact factor: 5.221

9.  Systems Toxicology: Real World Applications and Opportunities.

Authors:  Thomas Hartung; Rex E FitzGerald; Paul Jennings; Gary R Mirams; Manuel C Peitsch; Amin Rostami-Hodjegan; Imran Shah; Martin F Wilks; Shana J Sturla
Journal:  Chem Res Toxicol       Date:  2017-03-31       Impact factor: 3.739

10.  An Explainable Supervised Machine Learning Model for Predicting Respiratory Toxicity of Chemicals Using Optimal Molecular Descriptors.

Authors:  Keerthana Jaganathan; Hilal Tayara; Kil To Chong
Journal:  Pharmaceutics       Date:  2022-04-11       Impact factor: 6.525

  10 in total

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