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Benchmark dose analysis framework for developing wildlife toxicity reference values
Author(s) -
Mayfield David B.,
Skall Daniel G.
Publication year - 2018
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.4082
Subject(s) - benchmark (surveying) , risk assessment , wildlife , medicine , statistics , environmental health , computer science , biology , mathematics , geography , ecology , cartography , computer security
The effects characterization phase of ecological risk assessments (ERAs) often includes the selection or development of toxicity reference values (TRVs) for chemicals under investigation. In wildlife risk assessments, TRVs are thresholds represented by a dose or concentration associated with a specified adverse response. Traditionally, a TRV may be derived from an estimate of the no‐observed‐adverse effect level or lowest‐observed‐adverse‐effect level, identified from a controlled toxicity study. Because of the limitations of this approach, risk assessors are increasingly developing TRVs using alternative methods. Benchmark dose (BMD) analysis is widely recognized as one approach for developing TRVs. A BMD is derived using the full dose–response relationship from all experimental doses and may represent a user‐specified response level (e.g., 5, 10, 20, or 50%). Although many regulatory programs consider the use of BMD‐derived wildlife TRVs, there is limited guidance available for implementing the BMD approach, particularly for ERA. The present study provides a framework for ecological risk assessors to identify appropriate data, examine dose–response relationships, estimate BMDs, and document the results for use in risk analysis. This framework demonstrates the process of developing a TRV using BMD analysis and identifies applications for which this approach may enhance ERAs (e.g., site assessment, chemical or pesticide registration programs). Environ Toxicol Chem 2018;37:1496–1508. © 2018 SETAC

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