Biomedical subjects

Robert S Boethling

Publications and source records attributed to Robert S Boethling.

5 recordsLinked to original sources

PubMed2006

Biodegradation of US premanufacture notice chemicals in OECD tests.

Biodegradation testing of commercial chemicals other than pesticides is generally performed using test guidelines of the Organization for Economic Cooperation and Development (OECD). We used test data submitted with US Premanufacture Notifications (PMNs) received from 1995 through 2005 to study performance of OECD biodegradation tests, as well as the overall testing strategy and guidance. Among the findings are that (1) ready biodegradation (RB) tests gave fairly consistent results relative to the pass/fail outcome, but not necessarily percent degradation; (2) the Zahn-Wellens test worked well in providing a quick measure of sorption potential, but aside from this, provided little useful information for the investigated chemicals beyond what was already available from RB tests; (3) the SCAS test sometimes gives lower % removal than continuous-feed simulation tests like OECD 303A; and (4) OECD 306 (marine biodegradation test) appeared less conservative than ordinary RB tests. Overall, the PMN data lend support to new OECD guidance that endorses the primary role of RB tests, but emphasizes simulation rather than inherent biodegradation tests as the next step.

Biodegradation, Environmental↗

PubMed2004

Using Biowin, Bayes, and batteries to predict ready biodegradability.

Whether or not a given chemical substance is readily biodegradable is an important piece of information in risk screening for both new and existing chemicals. Despite the relatively low cost of Organization for Economic Cooperation and Development tests, data are often unavailable and biodegradability must be estimated. In this paper, we focus on the predictive value of selected Biowin models and model batteries using Bayesian analysis. Posterior probabilities, calculated based on performance with the model training sets using Bayes' theorem, were closely matched by actual performance with an expanded set of 374 premanufacture notice (PMN) substances. Further analysis suggested that a simple battery consisting of Biowin3 (survey ultimate biodegradation model) and Biowin5 (Ministry of International Trade and Industry [MITI] linear model) would have enhanced predictive power in comparison to individual models. Application of the battery to PMN substances showed that performance matched expectation. This approach significantly reduced both false positives for ready biodegradability and the overall misclassification rate. Similar results were obtained for a set of 63 pharmaceuticals using a battery consisting of Biowin3 and Biowin6 (MITI nonlinear model). Biodegradation data for PMNs tested in multiple ready tests or both inherent and ready biodegradation tests yielded additional insights that may be useful in risk screening.

Bayes Theorem↗

PubMed2004

Finding and estimating chemical property data for environmental assessment.

The ability to predict the behavior of a chemical substance in a biological or environmental system largely depends on knowledge of the physicochemical properties and reactivity of that substance. We focus here on properties, with the objective of providing practical guidance for finding measured values and using estimation methods when necessary. Because currently available computer software often makes it more convenient to estimate than to retrieve measured values, we try to discourage irrational exuberance for these tools by including comprehensive lists of Internet and hard-copy data resources. Guidance for assessors is presented in the form of a process to obtain data that includes establishment of chemical identity, identification of data sources, assessment of accuracy and reliability, substructure searching for analogs when experimental data are unavailable, and estimation from chemical structure. Regarding property estimation, we cover estimation from close structural analogs in addition to broadly applicable methods requiring only the chemical structure. For the latter, we list and briefly discuss the most widely used methods. Concluding thoughts are offered concerning appropriate directions for future work on estimation methods, again with an emphasis on practical applications.

Data Collection↗

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↗