Biodegradation data evaluation for structure/biodegradability relations

Abstract

Previous attempts at structure/biodegradability relations (SBRs) and available biodegradation data are reviewed and it is concluded that (1) not enough rate data on large numbers of chemicals are available to develop quantitative SBRs and (2) attempted qualitative SBRs have suffered from either poor documentation of the biodegradation evaluation or they have used limited biodegradation test data. Because of the poor reproducibility of biodegradation tests, a weight‐of‐evidence evaluation procedure is proposed. A system for collecting and evaluating biodegradation data from screening tests, biological treatment simulations, grab sample tests and field studies is described and study‐specific and summary biodegradability codes in combination with reliability codes are developed that can be used for structure/biodegradability relations.

Structure-activity relationships for biodegradation: A critical review

“…Often important details affecting reproducibility are not reported. Howard et al [35] developed an evaluation method for collecting and evaluating individual studies and test data that facilitates the development of conclusions on biodegradability for use in structurehiodegradation relations [35]. This was done under the assumption that as the number of consistent test results or test results for which apparent inconsistencies are resolvable increases, the greater is the likelihood that the indication of biodegradability is a property of the chemical rather than of the test system.…”

“…In order to minimize the number of false negatives and false positives Kuenemann et al propose to test other molecular descriptors and new statistical methods [22]. Howard et al [23] used a file of evaluated biodegradation data [35] to develop a model for predicting aerobic biodegradability from chemical substructures. To this end, chemicals were initially divided into three groups:…”

Review of Estimation Models for Biodegradation

“…A linear probability model, Biowinl, and a non-linear probability model, Biowin2, were developed by using data for 295 chemicals in the BIODEG database (186 chemicals were evaluated as biodegrades fast and 109 chemicals as does not biodegrade fast). Howard et al have described the methodology [34] and the critical evaluation of the biodegradation data [46]. The linear and non-linear probability models developed with the BIODEG dataset were subsequently reparameterised by using the MITI dataset, resulting in Biowin5 and Biowin6, respectively [47].…”

Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances.

“…The vast majority of published quantitative structure-biodegradation relationships (QSBRs) rely on octanol-water partition coefficients (K ow ), van der Waal's radii, alkaline (abiotic) hydrolysis rate constants, and various molecular connectivity indices. Classes of chemicals covered by such models include chlorophenols and chloroanisoles, n-alkyl phthalates, alcohols, (2,4-dichlorophenoxyacetic acid) esters, parasubstituted phenols, meta-substituted anilines, esters, carbamates, ethers, and ketones (Howard 2000;Howard and Banerjee 1984;Howard et al 1987). Generally, the correlation coefficients between physical/chemical properties or molecular descriptors and biodegradation rates have been good, but overall these models have not seen much use.…”

“…Biodegradation (i.e., complete mineralization, or conversion to carbon dioxide and water) is an important environmental degradation process for organic chemicals. Prediction of biodegradability is severely limited because of the lack of reproducibility of biodegradation data (Howard et al 1987) as well as the numerous protocols that have been (Howard and Banerjee 1984). As a result, quantitative prediction of biodegradation rates has only been attempted on very limited numbers of structurally related chemicals (Howard et al 1992).…”