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QSAR‐Based Estimation of Species Sensitivity Distribution Parameters: An Exploratory Investigation
Author(s) -
Hoondert Renske P.J.,
Oldenkamp Rik,
Zwart Dick,
Meent Dik,
Posthuma Leo
Publication year - 2019
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.4601
Subject(s) - quantitative structure–activity relationship , ecotoxicity , sensitivity (control systems) , chemistry , environmental chemistry , biochemical engineering , computer science , machine learning , toxicity , electronic engineering , engineering , organic chemistry
Ecological risk assessments are hampered by limited availability of ecotoxicity data. The present study aimed to explore the possibility of deriving species sensitivity distribution (SSD) parameters for nontested compounds, based on simple physicochemical characteristics, known SSDs for data‐rich compounds, and a quantitative structure–activity relationship (QSAR)‐type approach. The median toxicity of a data‐poor chemical for species assemblages significantly varies with values of the physicochemical descriptors, especially when based on high‐quality SSD data (from either acute median effect concentrations or chronic no‐observed‐effect concentrations). Beyond exploratory uses, we discuss how the precision of QSAR‐based SSDs can be improved to construct models that accurately predict the SSD parameters of data‐poor chemicals. The current models show that the concept of QSAR‐based SSDs supports screening‐level evaluations of the potential ecotoxicity of compounds for which data are lacking. Environ Toxicol Chem 2019;38:2764–2770. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC