An evaluated database of whole body in vivo biotransformation rate estimates in fish was used to develop a model for predicting the primary biotransformation half-lives of organic chemicals. The estimated biotransformation rates were converted to half-lives and divided into a model development set (n=421) and an external validation set (n=211) to test the model. The model uses molecular substructures similar to those of other biodegradation models. The biotransformation half-life predictions were calculated based on multiple linear regressions of development set data against counts of 57 molecular substructures, the octanol-water partition coefficient, and molar mass. The coefficient of determination (r2) for the development set was 0.82, the cross-validation (leave-one-out coefficient of determination, q2) was 0.75, and the mean absolute error (MAE) was 0.38 log units (factor of 2.4). Results for the external validation of the model using an independent test set were r2 = 0.73 and MAE = 0.45 log units (factor of 2.8). For the development set, 68 and 95% of the predicted values were within a factor of 3 and a factor of 10 of the expected values, respectively. For the test (or validation) set, 63 and 90% of the predicted values were within a factor of 3 and a factor of 10 of the expected values, respectively. Reasons for discrepancies between model predictions and expected values are discussed and recommendations are made for improving the model. This model can predict biotransformation rate constants from chemical structure for screening level bioaccumulation hazard assessments, exposure and risk assessments, comparisons with other in vivo and in vitro estimates, and as a contribution to testing strategies that reduce animal usage.

A method is proposed for estimating metabolic biotransformation rate constants for nonionic organic chemicals from measured laboratory bioconcentration and dietary bioaccumulation data in fish. Data have been selected based on a quality review to reduce uncertainty in the measured values. A kinetic mass balance model is used to estimate rates of chemical uptake and elimination. Biotransformation rate constants are essentially calculated as the difference between two quantities, a measured bioconcentration factor or elimination rate constant, and a model-derived bioconcentration factor or elimination rate constant estimated assuming no biotransformation. Model parameterization exploits key empirical data when they are available and assumes default values when study specific data are unavailable. Uncertainty analyses provide screening level assessments for confidence in the biotransformation rate constant estimates. The uncertainty analyses include the range for 95% of the predicted values and 95% confidence intervals for the calculated biotransformation values. Case studies are provided to illustrate the calculation and uncertainty methods. Biotransformation rate constants calculated by the proposed method are compared with other published estimates for 31 chemicals that range in octanol-water partition coefficients from approximately 10(1) to 10(8) and represent over four orders of magnitude in biotransformation potential. The comparison of previously published values with those calculated by the proposed method shows general agreement with 82% of the estimated values falling within a factor of three.

Biotransformation is a key process that can mitigate the bioaccumulation potential of organic substances and is an important parameter for exposure assessments. A recently published method for estimating whole-body in vivo metabolic biotransformation rate constants (kM) is applied to a database of measured laboratory bioconcentration factors and total elimination rate constants for fish. The method uses a kinetic mass balance model to estimate rates of chemical uptake and elimination when measured values are not reported. More than 5400 measurements for more than 1000 organic chemicals were critically reviewed to compile a database of 1535 kM estimates for 702 organic chemicals. Biotransformation rates range over six orders of magnitude across a diverse domain of chemical classes and structures. Screening-level uncertainty analyses provide guidance for the selection and interpretation of kM values. In general, variation in kM estimates from different routes of exposure (water vs diet) and between fish species is approximately equal to the calculation uncertainty in kM values. Examples are presented of structure-biotransformation relationships. Biotransformation rate estimates in the database are compared with estimates of biodegradation rates from existing quantitative structure-activity relationship models. Modest correlations are found, suggesting some consistency in biotransformation capabilities between fish and microorganisms. Additional analyses to further explore possible quantitative structure-biotransformation relationships for estimating kM from chemical structure are encouraged, and recommendations for improving the database are provided.

Overall persistence (P ov ) and long-range transport potential (LRTP) of organic chemicals are environmental hazard metrics calculated with multimedia fate and transport models. Since there are several models of this type, it is important to know whether and how different model designs (model geometry, selection of compartments and processes, process descriptions) affect the results for P ov and LRTP. Using a set of 3175 hypothetical chemicals covering a broad range of partition coefficients and degradation halflives, we systematically analyze the P ov and LRTP results obtained with nine multimedia models. We have developed several methods that make it possible to visualize the model results efficiently and to relate differences in model results to mechanistic differences between models. Rankings of the hypothetical chemicals according to P ov and LRTP are highly correlated among models and are largely determined by the chemical properties. Domains of chemical properties in which model differences lead to different results are identified, and guidance on model selection is provided for model users.