Alternatives to Animal Testing and Experimentation
Online ISSN : 2185-4726
Print ISSN : 1344-0411
ISSN-L : 1344-0411
Volume 15 , Issue 3
Showing 1-3 articles out of 3 articles from the selected issue
TOPICS
  • William S. Stokes
    Type: TOPICS
    2010 Volume 15 Issue 3 Pages 119-123
    Published: December 31, 2010
    Released: February 21, 2011
    JOURNALS FREE ACCESS
    The U.S. National Toxicology Program's Interagency Center for the Evaluation of Alternative Methods and its Interagency Coordinating Committee on the Validation of Alternative Methods recently completed and planned several activities to promote the development, validation and regulatory acceptance of alternative methods for regulatory safety testing. Recommendations for new allergic contact dermatitis test methods were accepted in the U.S. and internationally by the OECD. An international workshop developed recommendations to advance alternative methods for human and veterinary vaccine potency and safety testing. Wokshops on best practices for assessing the eye injury and allergic contact dermatitis potential of chemicals and products were convened to foster the use of accepted new test methods. An upcoming international panel will evaluate the validity of an in vitro estrogen receptor transcriptional activation assay. These activities are expected to improve global animal welfare and reduce animal use while ensuring continued protection of people, animals, and the environment.
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ORIGINAL ARTICLE
  • Kazuhiro Sato, Tomohiro Umemura, Taro Tamura, Yukinori Kusaka, Toshiko ...
    Type: ORIGINAL ARTICLE
    2010 Volume 15 Issue 3 Pages 124-130
    Published: December 31, 2010
    Released: February 21, 2011
    JOURNALS FREE ACCESS
    New respiratory sensitization positive/negative prediction models with discriminant functions were generated and parameter analyses were discussed on the basis of QSAR technology. Samples used in this research were selected from the list of European Chemical Bureau (ECB): R42, R42/43 for positive samples (respiratory sensitizers) and from the classification results of the Japanese Inter-ministerial Committee for negative respiratory sensitizers (controls). A total of 214 compounds (61 positive sensitizers and 153 negative sensitizers) were used in this study. Parameters were generated from 2-D and 3-D structures of compound. All of the approximately 800 parameters generated were reduced to 12 parameter set by feature selection. Various linear and non-linear discriminant analysis methods were applied using the parameter set. All data analyses were performed using ADMEWORKS/ ModelBuilder software. Perfect classification ratios (100%) were achieved using Iterative Least Squares (ILS) and AdaBoost. The highest prediction ratio of 97.2% by leave-one-out cross-validation was achieved with Support Vector Machine (SVM). This model is applicable to initial prediction of respiratory sensitization.
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