Prediction of the Daphnia acute toxicity from heterogeneous data

Two descriptors (log( P ow), ‘hardness’) were selected to predict the Daphnia acute toxicity of a training set of heterogeneous chemical compounds. The data were extracted from 523 notification files about new chemicals stored at the French Department of Environment. The selection of the descriptors...

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Bibliographic Details
Published in:Chemosphere (Oxford) 2001-07, Vol.44 (3), p.407-422
Main Authors: Faucon, J.C., Bureau, R., Faisant, J., Briens, F., Rault, S.
Format: Article
Language:English
Subjects:
Animal, plant and microbial ecology
Animals
Applied ecology
Biological and medical sciences
Daphnia
Daphnia acute toxicity
DNA Damage
Dose-Response Relationship, Drug
Ecotoxicology, biological effects of pollution
Effects of pollution and side effects of pesticides on protozoa and invertebrates
Forecasting
France
Fundamental and applied biological sciences. Psychology
Genetic algorithm
Hardness
log( Pow)
Models, Genetic
Models, Theoretical
QSAR
Reference Values
Regression Analysis
Risk Assessment
Structure-Activity Relationship
Toxicity Tests - statistics & numerical data
Water - chemistry
Water Pollutants, Chemical - toxicity
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Summary:Two descriptors (log( P ow), ‘hardness’) were selected to predict the Daphnia acute toxicity of a training set of heterogeneous chemical compounds. The data were extracted from 523 notification files about new chemicals stored at the French Department of Environment. The selection of the descriptors was carried out using a statistical method coupling ordinary least square (OLS) regression and genetic algorithm (GA). The validity limits for the final equation are discussed by comparing the actual and predicted activities of several compounds. The study points out the interest of the ‘hardness’ parameter for quantitative structure–activity relationships (QSAR) with a heterogeneous data set.
ISSN:0045-6535
1879-1298
DOI:10.1016/S0045-6535(00)00301-5