4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on the Classification of Local Lymph Node Assay Measures
نویسندگان
چکیده
منابع مشابه
4D-fingerprint categorical QSAR models for skin sensitization based on the classification of local lymph node assay measures.
Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the local lymph node assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, for eaxample, quantitative structure-activity relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data hav...
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Three and four state categorical quantitative structure-activity relationship (QSAR) models for skin sensitization have been constructed using data from the murine Local Lymph Node Assay studies. These are the same data we previously used to build two-state (sensitizer, nonsensitizer) QSAR models (Li et al., 2007, Chem. Res. Toxicol. 20, 114-128). 4D-fingerprint descriptors derived from the 4D-...
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Allergic Contact Dermatitis (ACD) is a common work-related skin disease that often develops as a result of repetitive skin exposures to a sensitizing chemical agent. A variety of experimental tests have been suggested to assess the skin sensitization potential. We applied a method of Quantitative Structure-Activity Relationship (QSAR) to relate measured and calculated physical-chemical properti...
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The local lymph node assay (LLNA) is a new test method which allows for the quantitative assessment of sensitizing potency in the mouse. Here, we investigate the quantitative correlation between results from the LLNA and two human sensitization tests--specifically, human repeat insult patch tests (HRIPTs) and human maximization tests (HMTs). Data for 57 substances were evaluated, of which 46 sh...
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ژورنال
عنوان ژورنال: Chemical Research in Toxicology
سال: 2007
ISSN: 0893-228X,1520-5010
DOI: 10.1021/tx6002535