Literature DB >> 17555332

Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization.

David W Roberts1, Grace Patlewicz, Petra S Kern, Frank Gerberick, Ian Kimber, Rebecca J Dearman, Cindy A Ryan, David A Basketter, Aynur O Aptula.   

Abstract

The goal of eliminating animal testing in the predictive identification of chemicals with the intrinsic ability to cause skin sensitization is an important target, the attainment of which has recently been brought into even sharper relief by the EU Cosmetics Directive and the requirements of the REACH legislation. Development of alternative methods requires that the chemicals used to evaluate and validate novel approaches comprise not only confirmed skin sensitizers and non-sensitizers but also substances that span the full chemical mechanistic spectrum associated with skin sensitization. To this end, a recently published database of more than 200 chemicals tested in the mouse local lymph node assay (LLNA) has been examined in relation to various chemical reaction mechanistic domains known to be associated with sensitization. It is demonstrated here that the dataset does cover the main reaction mechanistic domains. In addition, it is shown that assignment to a reaction mechanistic domain is a critical first step in a strategic approach to understanding, ultimately on a quantitative basis, how chemical properties influence the potency of skin sensitizing chemicals. This understanding is necessary if reliable non-animal approaches, including (quantitative) structure-activity relationships (Q)SARs, read-across, and experimental chemistry based models, are to be developed.

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Year:  2007        PMID: 17555332     DOI: 10.1021/tx700024w

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


  17 in total

1.  Fragment-based prediction of skin sensitization using recursive partitioning.

Authors:  Jing Lu; Mingyue Zheng; Yong Wang; Qiancheng Shen; Xiaomin Luo; Hualiang Jiang; Kaixian Chen
Journal:  J Comput Aided Mol Des       Date:  2011-09-20       Impact factor: 3.686

2.  Application of IATA - A case study in evaluating the global and local performance of a Bayesian network model for skin sensitization.

Authors:  J M Fitzpatrick; G Patlewicz
Journal:  SAR QSAR Environ Res       Date:  2017-04-20       Impact factor: 3.000

3.  Substituent effects on the reactivity of benzoquinone derivatives with thiols.

Authors:  Wilbes Mbiya; Itai Chipinda; Paul D Siegel; Morgen Mhike; Reuben H Simoyi
Journal:  Chem Res Toxicol       Date:  2012-12-27       Impact factor: 3.739

4.  Pyridoxylamine reactivity kinetics as an amine based nucleophile for screening electrophilic dermal sensitizers.

Authors:  Itai Chipinda; Wilbes Mbiya; Risikat Ajibola Adigun; Moshood K Morakinyo; Brandon F Law; Reuben H Simoyi; Paul D Siegel
Journal:  Toxicology       Date:  2013-12-12       Impact factor: 4.221

Review 5.  Methyl methacrylate and respiratory sensitization: a critical review.

Authors:  Jonathan Borak; Cheryl Fields; Larry S Andrews; Mark A Pemberton
Journal:  Crit Rev Toxicol       Date:  2011-03       Impact factor: 5.635

Review 6.  On exploring structure-activity relationships.

Authors:  Rajarshi Guha
Journal:  Methods Mol Biol       Date:  2013

7.  Haptenation: chemical reactivity and protein binding.

Authors:  Itai Chipinda; Justin M Hettick; Paul D Siegel
Journal:  J Allergy (Cairo)       Date:  2011-06-30

8.  A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests.

Authors:  Henrik Johansson; Malin Lindstedt; Ann-Sofie Albrekt; Carl A K Borrebaeck
Journal:  BMC Genomics       Date:  2011-08-08       Impact factor: 3.969

9.  Prediction of skin sensitization with a particle swarm optimized support vector machine.

Authors:  Hua Yuan; Jianping Huang; Chenzhong Cao
Journal:  Int J Mol Sci       Date:  2009-07-17       Impact factor: 6.208

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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