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Structure and Parameterization of Pharmacokinetic Models: Their Impact on Model Predictions

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  • Tracey J. Woodruff
  • Frédéric Y. Bois
  • David Auslander
  • Robert C. Spear

Abstract

There has been an increasing interest in physiologically based pharmacokinetic (PBPK)models in the area of risk assessment. The use of these models raises two important issues: (1)How good are PBPK models for predicting experimental kinetic data? (2)How is the variability in the model output affected by the number of parameters and the structure of the model? To examine these issues, we compared a five‐compartment PBPK model, a three‐compartment PBPK model, and nonphysiological compartmental models of benzene pharmacokinetics. Monte Carlo simulations were used to take into account the variability of the parameters. The models were fitted to three sets of experimental data and a hypothetical experiment was simulated with each model to provide a uniform basis for comparison. Two main results are presented: (1)the difference is larger between the predictions of the same model fitted to different data se1ts than between the predictions of different models fitted to the dame data; and (2)the type of data used to fit the model has a larger effect on the variability of the predictions than the type of model and the number of parameters.

Suggested Citation

  • Tracey J. Woodruff & Frédéric Y. Bois & David Auslander & Robert C. Spear, 1992. "Structure and Parameterization of Pharmacokinetic Models: Their Impact on Model Predictions," Risk Analysis, John Wiley & Sons, vol. 12(2), pages 189-201, June.
    • Handle: RePEc:wly:riskan:v:12:y:1992:i:2:p:189-201
    DOI: 10.1111/j.1539-6924.1992.tb00667.x
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    References listed on IDEAS

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    1. Dale Hattis & Paul White & Laura Marmorstein & Paul Koch, 1990. "Uncertainties in Pharmacokinetic Modeling for Perchloroethylene. I. Comparison of Model Structure, Parameters, and Predictions for Low‐Dose Metabolism Rates for Models Derived by Different Authors," Risk Analysis, John Wiley & Sons, vol. 10(3), pages 449-458, September.
    2. Robert C. Spear & Frédéric Y. Bois & Tracey Woodruff & David Auslander & Jennifer Parker & Steve Selvin, 1991. "Modeling Benzene Pharmacokinetics Across Three Sets of Animal Data: Parametric Sensitivity and Risk Implications," Risk Analysis, John Wiley & Sons, vol. 11(4), pages 641-654, December.
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    1. Leona H. Clark & R. Woodrow Setzer & Hugh A. Barton, 2004. "Framework for Evaluation of Physiologically‐Based Pharmacokinetic Models for Use in Safety or Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1697-1717, December.
    2. Karen H. Watanabe & Frédéric Y. Bois, 1996. "Interspecies Extrapolation of Physiological Pharmacokinetic Parameter Distributions," Risk Analysis, John Wiley & Sons, vol. 16(6), pages 741-754, December.
    3. William J. Cronin & Eric J. Oswald & Michael L. Shelley & Jeffrey W. Fisher & Carlyle D. Flemming, 1995. "A Trichloroethylene Risk Assessment Using a Monte Carlo Analysis of Parameter Uncertainty in Conjunction with Physiologically‐Based Pharmacokinetic Modeling," Risk Analysis, John Wiley & Sons, vol. 15(5), pages 555-565, October.
    4. Maxine E. Dakins & John E. Toll & Mitchell J. Small & Kevin P. Brand, 1996. "Risk‐Based Environmental Remediation: Bayesian Monte Carlo Analysis and the Expected Value of Sample Information," Risk Analysis, John Wiley & Sons, vol. 16(1), pages 67-79, February.
    5. Kevin P. Brand & Mitchell J. Small, 1995. "Updating Uncertainty in an Integrated Risk Assessment: Conceptual Framework and Methods," Risk Analysis, John Wiley & Sons, vol. 15(6), pages 719-729, December.

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