Literature DB >> 16536334

Compilation of historical local lymph node data for evaluation of skin sensitization alternative methods.

G Frank Gerberick1, Cindy A Ryan, Petra S Kern, Harald Schlatter, Rebecca J Dearman, Ian Kimber, Grace Y Patlewicz, David A Basketter.   

Abstract

BACKGROUND: Within the toxicology community, considerable effort is directed toward the development of alternative methods for skin sensitization testing. The availability of high-quality, relevant, and reliable in vivo data regarding skin sensitization is essential for the effective evaluation of alternative methodologies. Ideally, data derived from humans would be the most appropriate source because the test methods are attempting to predict a toxicologic effect in humans. Unfortunately, insufficient human data of the necessary quality are available, so it is necessary to rely on the best available animal data. In recent years, the local lymph node assay (LLNA) has emerged as a practical option for assessing the skin sensitization potential of chemicals. In addition to accurately identifying skin sensitizers, the LLNA can also provide a reliable measure of relative sensitization potency, information that is pivotal to the successful management of human health risks.
OBJECTIVE: To provide a database of robust in vivo data to calibrate, evaluate, and eventually validate new approaches for skin sensitization testing.
METHODS: LLNA data derived from previously conducted studies were compiled from the published literature and unpublished sources.
RESULTS: We provide a database that comprises LLNA data on 211 individual chemicals. This extensive chemical data set encompasses both the chemical and biologic diversity of known chemical allergens. To cover the range of relative allergenic potencies, the data set includes data on 13 extreme, 21 strong, 69 moderate, and 66 weak contact allergens, classified according to each allergen's mathematically estimated concentration of chemical required to induce a threefold stimulation index. In addition, there are also 42 chemicals that are considered to be nonsensitizers. In terms of chemical diversity, the database contains data pertaining to the chemical classes represented by aldehydes, ketones, aromatic amines, quinones, and acrylates, as well as compounds that have different reactivity mechanisms. In addition to two-dimensional chemical structures, the physicochemical parameters included are log Kp, log K(o/w), and molecular weight.
CONCLUSIONS: The list of chemicals contained in the data set represents both the chemical and biologic diversity that is known to exist for chemical allergens and non-allergens. It is anticipated that this database will help accelerate the development, evaluation, and eventual validation of new approaches to skin sensitization assessment.

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Year:  2005        PMID: 16536334

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


  34 in total

Review 1.  T-cell recognition of chemicals, protein allergens and drugs: towards the development of in vitro assays.

Authors:  Stefan F Martin; Philipp R Esser; Sonja Schmucker; Lisa Dietz; Dean J Naisbitt; B Kevin Park; Marc Vocanson; Jean-Francois Nicolas; Monika Keller; Werner J Pichler; Matthias Peiser; Andreas Luch; Reinhard Wanner; Enrico Maggi; Andrea Cavani; Thomas Rustemeyer; Anne Richter; Hermann-Josef Thierse; Federica Sallusto
Journal:  Cell Mol Life Sci       Date:  2010-08-18       Impact factor: 9.261

2.  4D-fingerprint categorical QSAR models for skin sensitization based on the classification of local lymph node assay measures.

Authors:  Yi Li; Yufeng J Tseng; Dahua Pan; Jianzhong Liu; Petra S Kern; G Frank Gerberick; Anton J Hopfinger
Journal:  Chem Res Toxicol       Date:  2007-01       Impact factor: 3.739

3.  Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors.

Authors:  Jianzhong Liu; Petra S Kern; G Frank Gerberick; Osvaldo A Santos-Filho; Emilio X Esposito; Anton J Hopfinger; Yufeng J Tseng
Journal:  J Comput Aided Mol Des       Date:  2008-03-13       Impact factor: 3.686

4.  Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

Authors:  Thomas Luechtefeld; Alexandra Maertens; James M McKim; Thomas Hartung; Andre Kleensang; Vanessa Sá-Rocha
Journal:  J Appl Toxicol       Date:  2015-06-05       Impact factor: 3.446

5.  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

6.  Navigating through the minefield of read-across tools: A review of in silico tools for grouping.

Authors:  Patlewicz Grace; Helman George; Pradeep Prachi; Shah Imran
Journal:  Comput Toxicol       Date:  2017-08

Review 7.  Application of proteomics in the elucidation of chemical-mediated allergic contact dermatitis.

Authors:  Tessa Höper; Franz Mussotter; Andrea Haase; Andreas Luch; Tewes Tralau
Journal:  Toxicol Res (Camb)       Date:  2017-06-13       Impact factor: 3.524

8.  Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds.

Authors:  Vinicius M Alves; Eugene Muratov; Denis Fourches; Judy Strickland; Nicole Kleinstreuer; Carolina H Andrade; Alexander Tropsha
Journal:  Toxicol Appl Pharmacol       Date:  2015-01-03       Impact factor: 4.219

9.  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

10.  Global QSAR models of skin sensitisers for regulatory purposes.

Authors:  Qasim Chaudhry; Nadège Piclin; Jane Cotterill; Marco Pintore; Nick R Price; Jacques R Chrétien; Alessandra Roncaglioni
Journal:  Chem Cent J       Date:  2010-07-29       Impact factor: 4.215

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