Mechanistic Applicability Domain Classification of a Local Lymph Node Assay Dataset for Skin Sensitization

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• 作者：David W. Roberts ; Grace Patlewicz ; Petra S. Kern ; Frank Gerberick ; Ian Kimber ; Rebecca J. Dearman ; Cindy A. Ryan ; David A. Basketter ; Aynur O. Aptula
• 刊名：Chemical Research in Toxicology
• 出版年：2007
• 出版时间：July 2007
• 年：2007
• 卷：20
• 期：7
• 页码：1019 - 1030
• 全文大小：154K
• 年卷期：v.20,no.7(July 2007)
• ISSN：1520-5010

文摘

The goal of eliminating animal testing in the predictive identification of chemicals with the intrinsicability to cause skin sensitization is an important target, the attainment of which has recently been broughtinto 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 novelapproaches comprise not only confirmed skin sensitizers and non-sensitizers but also substances thatspan the full chemical mechanistic spectrum associated with skin sensitization. To this end, a recentlypublished database of more than 200 chemicals tested in the mouse local lymph node assay (LLNA) hasbeen examined in relation to various chemical reaction mechanistic domains known to be associatedwith sensitization. It is demonstrated here that the dataset does cover the main reaction mechanisticdomains. In addition, it is shown that assignment to a reaction mechanistic domain is a critical first stepin a strategic approach to understanding, ultimately on a quantitative basis, how chemical propertiesinfluence the potency of skin sensitizing chemicals. This understanding is necessary if reliable non-animal approaches, including (quantitative) structure-activity relationships (Q)SARs, read-across, andexperimental chemistry based models, are to be developed.