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ICCVAM Biennial Report 2018-2019

ICCVAM Biennial Report 2018-2019
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https://ntp.niehs.nih.gov/go/884608

Statistical Models for Classification of Eye Irritants

NICEATM developed statistical models that could potentially be used to classify chemicals as eye corrosives, irritants, or non-irritants according to EPA and GHS hazard classification endpoints. Models were developed using machine learning approaches combined with historical in vivo eye irritation data, chemical structural information, and physicochemical properties. These models were used to predict hazard classifications for a database of over 500 substances, including many mixtures. Results suggest that these models are useful for screening substances for eye irritation potential. Future efforts to increase the models’ utility will focus on expanding their applicability domains and using the models in conjunction with other input variables in a defined approach for eye irritation testing. A paper describing this work is in preparation.

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