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evaluate, eventually validate new approaches METHODS: previously conducted studies were compiled published literature unpublished sources.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