Evaluation of a Bayesian Network for Strengthening the Weight of Evidence to Predict Acute Fish Toxicity from Fish Embryo Toxicity Data

被引:9
作者
Lillicrap, Adam [1 ]
Moe, S. Jannicke [1 ]
Wolf, Raoul [1 ]
Connors, Kristin A. [2 ]
Rawlings, Jane M. [2 ]
Landis, Wayne G. [3 ]
Madsen, Anders [4 ,5 ]
Belanger, Scott E. [2 ]
机构
[1] Norwegian Inst Water Res NIVA, Oslo, Norway
[2] Procter & Gamble, Cincinnati, OH USA
[3] Western Washington Univ, Bellingham, WA 98225 USA
[4] Aalborg Univ, Dept Comp Sci, Aalborg, Denmark
[5] HUGIN EXPERT AS, Aalborg, Denmark
关键词
Fish embryo toxicity; Acute fish toxicity; Weight of evidence; Bayesian network; Hazard assessment; CHEMICALS; STRATEGY; BIOACCUMULATION; REDUCE; TESTS;
D O I
10.1002/ieam.4258
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The use of fish embryo toxicity (FET) data for hazard assessments of chemicals, in place of acute fish toxicity (AFT) data, has long been the goal for many environmental scientists. The FET test was first proposed as a replacement to the standardized AFT test nearly 15 y ago, but as of now, it has still not been accepted as a standalone replacement by regulatory authorities such as the European Chemicals Agency (ECHA). However, the ECHA has indicated that FET data can be used in a weight of evidence (WoE) approach, if enough information is available to support the conclusions related to the hazard assessment. To determine how such a WoE approach could be applied in practice has been challenging. To provide a conclusive WoE for FET data, we have developed a Bayesian network (BN) to incorporate multiple lines of evidence to predict AFT. There are 4 different lines of evidence in this BN model: 1) physicochemical properties, 2) AFT data from chemicals in a similar class or category, 3) ecotoxicity data from other trophic levels of organisms (e.g., daphnids and algae), and 4) measured FET data. The BN model was constructed from data obtained from a curated database and conditional probabilities assigned for the outcomes of each line of evidence. To evaluate the model, 20 data-rich chemicals, containing a minimum of 3 AFT and FET test data points, were selected to ensure a suitable comparison could be performed. The results of the AFT predictions indicated that the BN model could accurately predict the toxicity interval for 80% of the chemicals evaluated. For the remaining chemicals (20%), either daphnids or algae were the most sensitive test species, and for those chemicals, the daphnid or algal hazard data would have driven the environmental classification.Integr Environ Assess Manag2020;16:452-460. (c) 2020 The Authors.Integrated Environmental Assessment and Managementpublished by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)
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页码:452 / 460
页数:9
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