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An overview of the use of quantitative structure‐activity relationships for ranking and prioritizing large chemical inventories for environmental risk assessments
Author(s) -
Russom Christine L.,
Breton Roger L.,
Walker John D.,
Bradbury Steven P.
Publication year - 2003
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 - 10.1897/01-194
Subject(s) - ranking (information retrieval) , risk assessment , hazard , stressor , environmental science , adverse outcome pathway , risk analysis (engineering) , environmental resource management , environmental health , computer science , ecology , business , biology , medicine , machine learning , computational biology , computer security , neuroscience
Ecological risk assessments for chemical stressors are used to establish linkages between likely exposure concentrations and adverse effects to ecological receptors. At times, it is useful to conduct screening risk assessments to assist in prioritizing or ranking chemicals on the basis of potential hazard and exposure assessment parameters. Ranking of large chemical inventories can provide evidence for focusing research and/or cleanup efforts on specific chemicals of concern. Because of financial and time constraints, data gaps exist, and the risk assessor is left with decisions on which models to use to estimate the parameter of concern. In this review, several methods are presented for using quantitative structure‐activity relationships (QSARs) in conducting hazard screening or screening‐level risk assessments. The ranking methods described include those related to current regulatory issues associated with chemical inventories from Canada, Europe, and the United States and an example of a screening‐level risk assessment conducted on chemicals associated with a watershed in the midwest region of the United States.