Title: Prediction of Acute Toxicity to Mice by the Arithmetic Mean Toxicity (AMT) Modelling Approach
Citation: SAR AND QSAR IN ENVIRONMENTAL RESEARCH vol. 21 no. 3-4 p. 265-275
Publication Year: 2010
JRC N°: JRC55764
ISSN: 1062-936X
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC55764
DOI: 10.1080/10629361003771025
Type: Articles in periodicals and books
Abstract: A novel modelling approach based on the structural and physicochemical similarity of chemicals to their nearest neighbours is proposed for toxicity estimation. This approach, called Arithmetic Mean Toxicity (AMT) modelling, is illustrated by means of an AMT model for predicting acute rodent toxicity. The AMT approach uses one or a few pairs of nearest structural neighbours. Each pair contains a chemical with a higher descriptor value and with a smaller descriptor value compared with the chemical of interest. Arithmetic mean toxicity values of those pairs are considered as toxicity of chemical of interest. The toxicity of the chemical of interest was not included in the development of the AMT model. The approach was applied to calculate the toxicity of chemicals to mice following intravenous injection. A toxicity data set containing 10241 organic neutral compounds was formed from the SYMYX database. The toxicity of only 14 chemicals was not calculated by the AMT model. The toxicity [log(1/LD50), mM/kg] of all other 10227 chemicals was calculated with a standard deviation ±0.52. Cascade AMT model was applied to estimate error values in calculations of toxicity of chemicals having different number structure neighbours and level of similarity. It was found that 7085 chemicals (about 69% of all chemicals in the data set) were calculated with standard deviation in interval (±0.33)-(±0.48), which is comparable to the experimental error of determination. For the remaining 3142 chemicals (about 31% of the data set), the standard deviation was ±0.64. The toxicity predictions for such chemicals should be regarded as preliminary estimate which could be improved by including additional structural neighbours with closed physicochemical properties. In the regulatory assessment of chemicals, the AMT approach could be used to support the read-across of properties between analogues.
JRC Institute:Institute for Health and Consumer Protection

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