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ICCVAM Biennial Report 2018-2019

ICCVAM Biennial Report 2018-2019
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https://ntp.niehs.nih.gov/go/884123

Variability Analysis of In Vivo Data to Set Performance Thresholds for Alternative Methods

To better characterize the reproducibility of the in vivo rabbit skin irritation assay, NICEATM assessed variability within a data set of over 3000 results for over 700 chemicals tested at least twice. The in vivo rabbit skin irritation assay has historically been the benchmark against which NAMs have been compared. However, a limiting factor in identifying a full replacement for the in vivo method could be the variability inherent to the subjective scoring of responses in the rabbit test. The NICEATM analysis found that chemicals classified as moderate irritants at least once were classified as mild irritants or non-irritants over 40% of the time when tested repeatedly. The level of variability was greatest between mild and moderate irritant classifications. This analysis indicates that the level of variability present in the rabbit skin irritation test should be taken into consideration when evaluating the performance of nonanimal alternative methods.

NICEATM also assessed the reproducibility of the rat acute oral lethality test using a comprehensively curated dataset of over 2000 chemicals. Quantitative and categorical analyses were conducted and a global confidence interval was established to characterize the inherent variability of the test method. These analyses revealed that independent studies can yield LD50 values orders of magnitude apart, which can have significant implications from a regulatory perspective due to the resulting impact on hazard classification and labeling. Similar to the analysis of the rabbit skin irritation test, no physicochemical properties or differences in test method protocol were identified that could readily explain differences between study results. The resulting publicly available dataset can be used for modeling, and the calculated confidence interval can be applied when assessing performance of NAMs. A publication describing this work is planned for submission in 2020.

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