Literature DB >> 24407057

Categorization of chemicals according to their relative human skin sensitizing potency.

David A Basketter1, Nathalie Alépée, Takao Ashikaga, João Barroso, Nicola Gilmour, Carsten Goebel, Jalila Hibatallah, Sebastian Hoffmann, Petra Kern, Silvia Martinozzi-Teissier, Gavin Maxwell, Kerstin Reisinger, Hitoshi Sakaguchi, Andreas Schepky, Magalie Tailhardat, Marie Templier.   

Abstract

Although adoption of skin sensitization in vivo assays for hazard identification is likely to be successful in the next few years, this does not replace their use in potency prediction. Notably, measurement of potency of skin sensitizers in the local lymph node assay has been important. However, this local lymph node assay potency measure has not been formally assessed against a range of substances of known human sensitizing potential, because the latter is lacking. Accordingly, criteria for human data have been established that characterize 6 categories of human sensitizing potency, with 1 the most potent and 5 the least potent; category 6 represents true nonsensitizers. The literature has been searched, and 131 chemicals assigned into these categories according to their intrinsic potency judged only by the available human information. The criteria and data set generated provide a basis for examination of the capacity of nonanimal approaches for the determination of human sensitization potency.

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Year:  2014        PMID: 24407057     DOI: 10.1097/DER.0000000000000003

Source DB:  PubMed          Journal:  Dermatitis        ISSN: 1710-3568            Impact factor:   4.845


  20 in total

1.  Prediction of skin sensitization potency using machine learning approaches.

Authors:  Qingda Zang; Michael Paris; David M Lehmann; Shannon Bell; Nicole Kleinstreuer; David Allen; Joanna Matheson; Abigail Jacobs; Warren Casey; Judy Strickland
Journal:  J Appl Toxicol       Date:  2017-01-10       Impact factor: 3.446

2.  Use of Lhasa Limited Products for the In Silico Prediction of Drug Toxicity.

Authors:  David J Ponting; Michael J Burns; Robert S Foster; Rachel Hemingway; Grace Kocks; Donna S MacMillan; Andrew L Shannon-Little; Rachael E Tennant; Jessica R Tidmarsh; David J Yeo
Journal:  Methods Mol Biol       Date:  2022

3.  Evaluating Confidence in Toxicity Assessments Based on Experimental Data and In Silico Predictions.

Authors:  Candice Johnson; Lennart T Anger; Romualdo Benigni; David Bower; Frank Bringezu; Kevin M Crofton; Mark T D Cronin; Kevin P Cross; Magdalena Dettwiler; Markus Frericks; Fjodor Melnikov; Scott Miller; David W Roberts; Diana Suarez-Rodriguez; Alessandra Roncaglioni; Elena Lo Piparo; Raymond R Tice; Craig Zwickl; Glenn J Myatt
Journal:  Comput Toxicol       Date:  2021-11-08

4.  Progress on Reconstructed Human Skin Models for Allergy Research and Identifying Contact Sensitizers.

Authors:  Charlotte Rodrigues Neves; Susan Gibbs
Journal:  Curr Top Microbiol Immunol       Date:  2021       Impact factor: 4.291

Review 5.  Non-animal methods to predict skin sensitization (II): an assessment of defined approaches *.

Authors:  Nicole C Kleinstreuer; Sebastian Hoffmann; Nathalie Alépée; David Allen; Takao Ashikaga; Warren Casey; Elodie Clouet; Magalie Cluzel; Bertrand Desprez; Nichola Gellatly; Carsten Göbel; Petra S Kern; Martina Klaric; Jochen Kühnl; Silvia Martinozzi-Teissier; Karsten Mewes; Masaaki Miyazawa; Judy Strickland; Erwin van Vliet; Qingda Zang; Dirk Petersohn
Journal:  Crit Rev Toxicol       Date:  2018-02-23       Impact factor: 5.635

6.  Multivariate models for prediction of human skin sensitization hazard.

Authors:  Judy Strickland; Qingda Zang; Michael Paris; David M Lehmann; David Allen; Neepa Choksi; Joanna Matheson; Abigail Jacobs; Warren Casey; Nicole Kleinstreuer
Journal:  J Appl Toxicol       Date:  2016-08-02       Impact factor: 3.446

7.  Mapping Chemical Respiratory Sensitization: How Useful Are Our Current Computational Tools?

Authors:  Emily Golden; Mikhail Maertens; Thomas Hartung; Alexandra Maertens
Journal:  Chem Res Toxicol       Date:  2020-12-15       Impact factor: 3.739

8.  Evaluation of a High-Throughput Peptide Reactivity Format Assay for Assessment of the Skin Sensitization Potential of Chemicals.

Authors:  Chin Lin Wong; Ai-Leen Lam; Maree T Smith; Sussan Ghassabian
Journal:  Front Pharmacol       Date:  2016-03-14       Impact factor: 5.810

9.  Fragrances Categorized According to Relative Human Skin Sensitization Potency.

Authors:  Anne Marie Api; Rahul Parakhia; Devin OʼBrien; David A Basketter
Journal:  Dermatitis       Date:  2017 Sep/Oct       Impact factor: 4.845

10.  QSAR models of human data can enrich or replace LLNA testing for human skin sensitization.

Authors:  Vinicius M Alves; Stephen J Capuzzi; Eugene Muratov; Rodolpho C Braga; Thomas Thornton; Denis Fourches; Judy Strickland; Nicole Kleinstreuer; Carolina H Andrade; Alexander Tropsha
Journal:  Green Chem       Date:  2016-10-06       Impact factor: 10.182

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