Predicting concentrations of organic chemicals in fish by using toxicokinetic models

Environ Sci Technol. 2012 Mar 20;46(6):3273-80. doi: 10.1021/es2043728. Epub 2012 Feb 28.

Abstract

Quantification of chemical toxicity continues to be generally based on measured external concentrations. Yet, internal chemical concentrations have been suggested to be a more suitable parameter. To better understand the relationship between the external and internal concentrations of chemicals in fish, and to quantify internal concentrations, we compared three toxicokinetic (TK) models with each other and with literature data of measured concentrations of 39 chemicals. Two one-compartment models, together with the physiologically based toxicokinetic (PBTK) model, in which we improved the treatment of lipids, were used to predict concentrations of organic chemicals in two fish species: rainbow trout (Oncorhynchus mykiss) and fathead minnow (Pimephales promelas). All models predicted the measured internal concentrations in fish within 1 order of magnitude for at least 68% of the chemicals. Furthermore, the PBTK model outperformed the one-compartment models with respect to simulating chemical concentrations in the whole body (at least 88% of internal concentrations were predicted within 1 order of magnitude using the PBTK model). All the models can be used to predict concentrations in different fish species without additional experiments. However, further development of TK models is required for polar, ionizable, and easily biotransformed compounds.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adipose Tissue / metabolism
  • Animals
  • Cyprinidae / metabolism*
  • Kidney / metabolism
  • Liver / metabolism
  • Models, Biological*
  • Muscles / metabolism
  • Oncorhynchus mykiss / metabolism*
  • Organic Chemicals / analysis*
  • Organic Chemicals / metabolism
  • Water Pollutants, Chemical / analysis*
  • Water Pollutants, Chemical / metabolism

Substances

  • Organic Chemicals
  • Water Pollutants, Chemical