Spielmann H, Liebsch M, Moldenhauer F, Holzhutter H G, de Silva O
ZEBET, Federal Institute for Consumer Protection and Veterinary Medicine (BgW), Diederdorfer Weg 1, D-12277 Berlin, Germany.
Toxicol In Vitro. 1995 Aug;9(4):549-56. doi: 10.1016/0887-2333(95)00043-8.
The HET-CAM test and 3T3 cell neutral red uptake (NRU) cytotoxicity assay were evaluated in a national German validation project to replace the Draize eye test for classifying severely eye irritating chemicals, which have to be labelled 'R-41' according to EU regulations. As testing of 200 chemicals in the two in vitro assays did not sufficiently allow severely eye irritating chemicals to be identified and since the scoring system of the HET-CAM assay has been derived empirically, it was investigated whether modern biostatistical methods, for example discriminant analysis, would improve the selection of predictive endpoints of the HET-CAM assay. Comparison of HET-CAM data with adverse reactions observed in different tissues of the rabbit's eye proved that complex regression models are better describing in vitro /in vivo correlations than simple linear models. Discriminant analysis revealed that among the nine endpoints routinely determined in the HET-CAM test, coagulation was the only acceptable endpoint to classify severely irritating chemicals 'R-41' according to EU regulations. To identify R-41 chemicals the reaction time of appearance of coagulation of a 10% solution was the best discriminating factor and coagulation of the undiluted chemical for the less water-soluble ones. The results suggest that only R-41 chemicals are inducing coagulation of the CAM within 50 sec, and can therefore be classified without further testing in vivo. Stepwise discriminant analysis allowed an in vitro testing strategy to be developed to identify R-41 chemicals by combining coagulation data of the HET-CAM assay with cytotoxicity data. Validity of the model for future data sets was assessed by cross-validation. The results obtained with 200 chemicals under blind conditions suggest that this approach will provide an acceptable sensitivity, predictivity and percentage of false positive data for severely eye irritating chemicals.
在德国的一个全国性验证项目中，对HET-CAM试验和3T3细胞中性红摄取（NRU）细胞毒性试验进行了评估，以取代Draize眼试验来对严重眼刺激性化学品进行分类，根据欧盟法规，这些化学品必须标注“R-41”。由于在这两种体外试验中对200种化学品进行测试不足以充分识别严重眼刺激性化学品，且HET-CAM试验的评分系统是基于经验得出的，因此研究了现代生物统计学方法（如判别分析）是否会改善HET-CAM试验预测终点的选择。将HET-CAM数据与兔眼不同组织中观察到的不良反应进行比较，结果证明复杂回归模型比简单线性模型能更好地描述体外/体内相关性。判别分析表明，在HET-CAM试验中常规测定的九个终点中，凝血是根据欧盟法规对严重刺激性化学品“R-41”进行分类的唯一可接受终点。为了识别R-41化学品，10%溶液出现凝血的反应时间是最佳判别因素，对于水溶性较差的化学品，则是未稀释化学品的凝血情况。结果表明，只有R-41化学品会在50秒内诱导鸡胚绒毛尿囊膜（CAM）凝血，因此无需进一步进行体内试验即可分类。逐步判别分析允许开发一种体外测试策略，通过将HET-CAM试验的凝血数据与细胞毒性数据相结合来识别R-41化学品。通过交叉验证评估了该模型对未来数据集的有效性。在盲法条件下对200种化学品获得的结果表明，这种方法将为严重眼刺激性化学品提供可接受的敏感性、预测性和假阳性数据百分比。
