Predictive QSAR models for estimating biodegradation of aromatic compounds

The development of valid structure biodegradation relationships (SBRs) is restricted by the lack of reproducible published data and by the considered endpoint of degradation data. A classification scheme is required for comparative evaluation of degradation data obtained by different test methods. SBRs based on substructure indicators are available for application to most compounds, but the reliability is still uncertain. SBRs based on physico-chemical parameters are only available for a few classes of compounds based on specific test methods. A combination of several SBRs covering the various transformation pathways provides a promising tool for predicting biodegradability. Two models describing biodegradation are introduced.