Abstract

AbstractTwo new predictive models for assessing a chemical's biodegradability in the Japanese Ministry of International Trade and Industry (MITI) ready biodegradation test have been developed. The new methods use an approach similar to that in the existing BIOWIN© program, in which the probability of rapid biodegradation is estimated by means of multiple linear or nonlinear regression against counts of 36 chemical substructures (molecular fragments) plus molecular weight (mol wt). The data set used to develop the new models consisted of results (pass/no pass) from the MITI test for 884 discrete organic chemicals. This data set was first divided into randomly selected training and validation sets, and new coefficients were derived for the training set using the BIOWIN fragment library and mol wt as independent variables. Based on these results, the fragment library was then modified by deleting some fragments and adding or refining others, and the new set of independent variables (42 substructures and mol wt) was fit to the MITI data. The resulting linear and nonlinear regression models accurately classified 81% of the chemicals in an independent validation set. Like the established BIOWIN models, the MITI models are intended for use in chemical screening and in setting priorities for further review.

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