Robert S Boethling | PubMed Health

PubMed2003

Recent developments in broadly applicable structure-biodegradability relationships.

Biodegradation is one of the most important processes influencing concentration of a chemical substance after its release to the environment. It is the main process for removal of many chemicals from the environment and therefore is an important factor in risk assessments. This article reviews available methods and models for predicting biodegradability of organic chemicals from structure. The first section of the article briefly discusses current needs for biodegradability estimation methods related to new and existing chemicals and in the context of multimedia exposure models. Following sections include biodegradation test methods and endpoints used in modeling, with special attention given to the Japanese Ministry of International Trade and Industry test; a primer on modeling, describing the various approaches that have been used in the structure/biodegradability relationship work, and contrasting statistical and mechanistic approaches; and recent developments in structure/biodegradability relationships, divided into group contribution, chemometric, and artificial intelligence approaches.

Artificial Intelligence↗

PubMed2003

Predicting ready biodegradability of premanufacture notice chemicals.

Chemical substances other than pesticides, drugs, and food additives are regulated by the U.S. Environmental Protection Agency (U.S. EPA) under the Toxic Substances Control Act (TSCA), but the United States does not require that new substances be tested automatically for such critical properties as biodegradability. The resulting lack of submitted data has fostered the development of estimation methods, and the BioWIN models for predicting biodegradability from chemical structure have played a prominent role in premanufacture notice (PMN) review. Until now, validation efforts have used only the Japanese Ministry of International Trade and Industry (MITI) test data and have not included all models. To assess BioWIN performance with PMN substances, we assembled a database of PMNs for which ready biodegradation data had been submitted over the period 1995 through 2001. The 305 PMN structures are highly varied and pose major challenges to chemical property estimation. Despite the variability of ready biodegradation tests, the use of at least six different test methods, and widely varying quality of submitted data, accuracy of four of six BioWIN models (MITI linear, MITI nonlinear, survey ultimate, survey primary) was in the 80+% range for predicting ready biodegradability. Greater accuracy (>90%) can be achieved by using model estimates only when the four models agree (true for 3/4 of the PMNs). The BioWIN linear and nonlinear probability models did not perform as well even when classification criteria were optimized. The results suggest that the MITI and survey BioWIN models are suitable for use in screening-level applications.

Biodegradation, Environmental↗