MODERN BIOSTATISTICAL METHODS FOR ASSESSING IN-VITRO IN-VIVO CORRELATION OF SEVERELY EYE IRRITATING CHEMICALS IN A VALIDATION-STUDY OF IN-VITRO ALTERNATIVES TO THE DRAIZE EYE TEST

The HET-CAM test and 3T3 cell neutral red uptake (NRU) cytotoxicity as say 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 test ing of 200 chemicals in the two in vitro assays did not sufficiently a llow severely eye irritating chemicals to be identified and since the scoring system of the HET-CAM assay has been derived empirically, it w as investigated whether modern biostatistical methods, for example dis criminant analysis, would improve the selection of predictive endpoint s of the HET-CAM assay. Comparison of HET-CAM data with adverse reacti ons observed in different tissues of the rabbit's eye proved that comp lex regression models are better describing in vitro/in vivo correlati ons than simple linear models. Discriminant analysis revealed that amo ng the nine endpoints routinely determined in the HET-CAM test, coagul ation was the only acceptable endpoint to classify severely irritating chemicals 'R-41' according to EU regulations. To identify R-41 chemic als the reaction time of appearance of coagulation of a 10% solution w as the best discriminating factor and coagulation of the undiluted che mical for the less water-soluble ones. The results suggest that only R -41 chemicals are inducing coagulation of the CAM within 50 sec, and c an therefore be classified without further testing in vivo. Stepwise d iscriminant analysis allowed an in vitro testing strategy to be develo ped to identify R-41 chemicals by combining coagulation data of the HE T-CAM assay with cytotoxicity data. Validity of the model for future d ata sets was assessed by cross-validation. The results obtained with 2 00 chemicals under blind conditions suggest that this approach will pr ovide an acceptable sensitivity, predictivity and percentage of false positive data for severely eye irritating chemicals.