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Reducing whole body physiologically based pharmacokinetic models using global sensitivity analysis: diazepam case

Ivelina Gueorguieva1, Ivan A Nestorov, Malcolm Rowland

  • 1Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Oxford Road, Manchester, M13 9PL, UK. ivelina.gueorguieva@manchester.ac.uk

Journal of Pharmacokinetics and Pharmacodynamics
|December 22, 2005
PubMed
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This study introduces a method to simplify complex pharmacokinetic models using global sensitivity analysis. The approach preserves key concentration data, making models more manageable while maintaining accuracy for drug development.

Area of Science:

  • Pharmacokinetics
  • Computational Biology
  • Drug Development

Background:

  • Physiologically based pharmacokinetic (PBPK) models are crucial in drug development but can be highly complex.
  • Reducing model dimensionality is necessary for efficient analysis and prediction.
  • Existing reduction methods may not adequately preserve essential pharmacokinetic parameters.

Purpose of the Study:

  • To present a formal method for reducing the dimensionality of whole-body PBPK models.
  • To utilize global sensitivity analysis to guide model reduction.
  • To ensure that mean and variance of tissue and/or blood concentrations are preserved in reduced models.

Main Methods:

  • Employed the Extended Fourier Amplitude Sensitivity Test (FAST) for global sensitivity analysis.

Related Experiment Videos

  • Applied established literature rules for formal model reduction to identify potential simplified models.
  • Treated model structural uncertainty as a key factor in the discrimination process.

    • Main Results:

    • Successfully reduced a 14-compartment whole-body PBPK model for diazepam disposition in rats to three alternative reduced models.
    • The reduced models accurately preserved the arterial mean and variance concentration profiles of the original model.
    • Demonstrated the efficacy of extended FAST in selecting appropriate reduced mechanistic models.

    Conclusions:

    • Formal model reduction based on global sensitivity analysis is a viable technique for simplifying complex PBPK models.
    • This method effectively maintains critical pharmacokinetic information (mean and variance) in reduced models.
    • The approach offers a robust strategy for managing complexity in PBPK modeling for drug development and research.