Literature DB >> 23149339

Data integration of non-animal tests for the development of a test battery to predict the skin sensitizing potential and potency of chemicals.

Yuko Nukada1, Masaaki Miyazawa, Saitou Kazutoshi, Hitoshi Sakaguchi, Naohiro Nishiyama.   

Abstract

Recent changes in regulatory restrictions and social views against animal testing have accelerated development of reliable alternative tests for predicting skin sensitizing potential and potency of many chemicals. Lately, a test battery integrated with different in vitro tests has been suggested as a better approach than just one in vitro test for replacing animal tests. In this study, we created a dataset of 101 test chemicals with LLNA, human cell line activation test (h-CLAT), direct peptide reactivity assay (DPRA) and in silico prediction system. The results of these tests were converted into scores of 0-2 and the sum of individual scores provided the accuracy of 85% and 71% for the potential and potency prediction, compared with LLNA. Likewise, the straightforward tiered system of h-CLAT and DPRA provided the accuracy of 86% and 73%. Additionally, the tiered system showed a higher sensitivity (96%) compared with h-CLAT alone, indicating that sensitizers would be detected with higher reliability in the tiered system. Our data not only demonstrates that h-CLAT can be part of a test battery with other methods but also supports the practical utility of a tiered system when h-CLAT and DPRA are the first screening methods for skin sensitization.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23149339     DOI: 10.1016/j.tiv.2012.11.006

Source DB:  PubMed          Journal:  Toxicol In Vitro        ISSN: 0887-2333            Impact factor:   3.500


  10 in total

1.  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

2.  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

Review 3.  Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing.

Authors:  Uwe Marx; Tommy B Andersson; Anthony Bahinski; Mario Beilmann; Sonja Beken; Flemming R Cassee; Murat Cirit; Mardas Daneshian; Susan Fitzpatrick; Olivier Frey; Claudia Gaertner; Christoph Giese; Linda Griffith; Thomas Hartung; Minne B Heringa; Julia Hoeng; Wim H de Jong; Hajime Kojima; Jochen Kuehnl; Marcel Leist; Andreas Luch; Ilka Maschmeyer; Dmitry Sakharov; Adrienne J A M Sips; Thomas Steger-Hartmann; Danilo A Tagle; Alexander Tonevitsky; Tewes Tralau; Sergej Tsyb; Anja van de Stolpe; Rob Vandebriel; Paul Vulto; Jufeng Wang; Joachim Wiest; Marleen Rodenburg; Adrian Roth
Journal:  ALTEX       Date:  2016-05-15       Impact factor: 6.043

4.  Integrated decision strategies for skin sensitization hazard.

Authors:  Judy Strickland; Qingda Zang; Nicole Kleinstreuer; Michael Paris; David M Lehmann; Neepa Choksi; Joanna Matheson; Abigail Jacobs; Anna Lowit; David Allen; Warren Casey
Journal:  J Appl Toxicol       Date:  2016-02-06       Impact factor: 3.446

5.  Application of Defined Approaches for Skin Sensitization to Agrochemical Products.

Authors:  Judy Strickland; James Truax; Marco Corvaro; Raja Settivari; Joseph Henriquez; Jeremy McFadden; Travis Gulledge; Victor Johnson; Sean Gehen; Dori Germolec; David G Allen; Nicole Kleinstreuer
Journal:  Front Toxicol       Date:  2022-05-02

6.  Development of a 96-Well Electrophilic Allergen Screening Assay for Skin Sensitization Using a Measurement Science Approach.

Authors:  Elijah J Petersen; Richard Uhl; Blaza Toman; John T Elliott; Judy Strickland; James Truax; John Gordon
Journal:  Toxics       Date:  2022-05-17

Review 7.  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

8.  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

9.  Sensitization potential of dental resins: 2-hydroxyethyl methacrylate and its water-soluble oligomers have immunostimulatory effects.

Authors:  Izumi Fukumoto; Atsushi Tamura; Mitsuaki Matsumura; Hiroyuki Miura; Nobuhiko Yui
Journal:  PLoS One       Date:  2013-11-29       Impact factor: 3.240

10.  Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

Authors:  Konda Leela Sarath Kumar; Sujit R Tangadpalliwar; Aarti Desai; Vivek K Singh; Abhay Jere
Journal:  PLoS One       Date:  2016-06-07       Impact factor: 3.240

  10 in total

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