A strategy for ranking environmentally occurring chemicals. Part III: Multivariate quantitative structure‐activity relationships for halogenated aliphatics
- 1 November 1990
- journal article
- research article
- Published by Oxford University Press (OUP) in Environmental Toxicology and Chemistry
- Vol. 9 (11) , 1339-1351
- https://doi.org/10.1002/etc.5620091103
Abstract
A strategy for systematic analysis and priority ranking of chemical compounds was applied to a class of 58 saturated halogenated aliphatics. By means of a fractional factorial design, a training set consisting of 10 compounds was selected. The training set compounds were subjected to biological testing and their acute oral toxicity to rat and highest nonlethal dose to mouse were determined. Based on the selected training set, two multivariate quantitative structure‐activity relationships (QSARs) were developed. It was concluded that both end points needed a multivariate structural description to be modelled. The derived QSARs were used to predict the potential hazards of the remaining compounds in the class.Keywords
This publication has 8 references indexed in Scilit:
- QSARs based on statistical design and their use for identifying chemicals for further biological testingEnvironmental Toxicology and Chemistry, 1990
- A strategy for ranking environmentally occurring chemicalsChemometrics and Intelligent Laboratory Systems, 1989
- A strategy for ranking environmentally occurring chemicalsChemometrics and Intelligent Laboratory Systems, 1989
- Principal component analysisChemometrics and Intelligent Laboratory Systems, 1987
- Principal Component AnalysisPublished by Springer Nature ,1986
- Multivariate structure‐activity relationships between data from a battery of biological tests and an ensemble of structure descriptors: The PLS methodQuantitative Structure-Activity Relationships, 1984
- Cross-Validatory Estimation of the Number of Components in Factor and Principal Components ModelsTechnometrics, 1978
- Cross-Validatory Estimation of the Number of Components in Factor and Principal Components ModelsTechnometrics, 1978