A database of fish biotransformation rates for organic chemicals

Authors

  • Jon A. Arnot,

    Corresponding author
    1. The Canadian Environmental Modelling Centre, Trent University, 1600 West Bank Drive Peterborough, Ontario K9H 7B8, Canada
    • The Canadian Environmental Modelling Centre, Trent University, 1600 West Bank Drive Peterborough, Ontario K9H 7B8, Canada; 1Published on the Web 6/3/2008
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  • Don Mackay,

    1. The Canadian Environmental Modelling Centre, Trent University, 1600 West Bank Drive Peterborough, Ontario K9H 7B8, Canada
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  • Thomas F. Parkerton,

    1. ExxonMobil Biomedical Sciences, 1545 Route 22 East, Annandale, New Jersey 08801, USA
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  • Mark Bonnell

    1. Science and Technology Branch, Environment Canada, 351 St-Joseph Boulevard Gatineau, Quebec K1A 0H3, Canada
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Abstract

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 5,400 measurements for more than 1,000 organic chemicals were critically reviewed to compile a database of 1,535 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.

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