Hybrid bayesian network model, Acute fish toxicity, Fish embryo toxicity, Weight of evidence, Animal alternatives, Risk assessment
A hybrid Bayesian network (BN) was developed for predicting the acute toxicity of chemicals to fish, using data from fish embryo toxicity (FET) testing in combination with other information. This model can support the use of FET data in a Weight-of-Evidence (WOE) approach for replacing the use of juvenile fish. The BN predicted correct toxicity intervals for 69%–80% of the tested substances. The model was most sensitive to components quantified by toxicity data, and least sensitive to components quantified by expert knowledge. The model is publicly available through a web interface. Further development of this model should include additional lines of evidence, refinement of the discretisation, and training with a larger dataset for weighting of the lines of evidence. A refined version of this model can be a useful tool for predicting acute fish toxicity, and a contribution to more quantitative WOE approaches for ecotoxicology and environmental assessment more generally.
Moe, S. Jannicke; Madsen, Anders L.; Connors, Kristin A.; Rawlings, Jane M.; Belanger, Scott E.; Landis, Wayne G.; Wolf, Raoul; and Lillicrap, Adam D., "Development of a hybrid Bayesian network model for predicting acute fish toxicity using multiple lines of evidence" (2020). IETC Publications. 4.
Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author’s written permission.