Matthews Edwin J, Kruhlak Naomi L, Daniel Benz R, Contrera Joseph F
US Food and Drug Administration, Center for Drug Evaluation and Research, Office of Pharmaceutical Science, Informatics and Computational Safety Analysis Staff, Silver Spring, MD 20993-0002, USA.
Regul Toxicol Pharmacol. 2007 Mar;47(2):115-35. doi: 10.1016/j.yrtph.2006.11.002. Epub 2007 Jan 4.
A weight of evidence (WOE) reproductive and developmental toxicology (reprotox) database was constructed that is suitable for quantitative structure-activity relationship (QSAR) modeling and human hazard identification of untested chemicals. The database was derived from multiple publicly available reprotox databases and consists of more than 10,000 individual rat, mouse, or rabbit reprotox tests linked to 2134 different organic chemical structures. The reprotox data were classified into seven general classes (male reproductive toxicity, female reproductive toxicity, fetal dysmorphogenesis, functional toxicity, mortality, growth, and newborn behavioral toxicity), and 90 specific categories as defined in the source reprotox databases. Each specific category contained over 500 chemicals, but the percentage of active chemicals was low, generally only 0.1-10%. The mathematical WOE model placed greater significance on confirmatory observations from repeat experiments, chemicals with multiple findings within a category, and the categorical relatedness of the findings. Using the weighted activity scores, statistical analyses were performed for specific data sets to identify clusters of categories that were correlated, containing similar profiles of active and inactive chemicals. The analysis revealed clusters of specific categories that contained chemicals that were active in two or more mammalian species (trans-species). Such chemicals are considered to have the highest potential risk to humans. In contrast, some specific categories exhibited only single species-specific activities. Results also showed that the rat and mouse were more susceptible to dysmorphogenesis than rabbits (6.1- and 3.6-fold, respectively).
构建了一个证据权重（WOE）生殖和发育毒理学（生殖毒理学）数据库，该数据库适用于未测试化学品的定量构效关系（QSAR）建模和人类危害识别。该数据库源自多个公开可用的生殖毒理学数据库，由10000多个与2134种不同有机化学结构相关的大鼠、小鼠或兔子的个体生殖毒理学测试组成。生殖毒理学数据被分为七个一般类别（雄性生殖毒性、雌性生殖毒性、胎儿畸形、功能毒性、死亡率、生长和新生动物行为毒性），以及源生殖毒理学数据库中定义的90个特定类别。每个特定类别包含超过500种化学品，但活性化学品的比例较低，通常仅为0.1%-10%。数学WOE模型更重视重复实验的验证性观察结果、同一类别中有多个发现的化学品以及发现结果的类别相关性。使用加权活性分数，对特定数据集进行统计分析，以识别相关类别的聚类，这些聚类包含活性和非活性化学品的相似概况。分析揭示了特定类别的聚类，其中包含在两种或更多哺乳动物物种（跨物种）中具有活性的化学品。这类化学品被认为对人类具有最高的潜在风险。相比之下，一些特定类别仅表现出单一物种特异性活性。结果还表明，大鼠和小鼠比兔子更容易发生畸形（分别为6.1倍和3.6倍）。
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