Skip to main content
Log in

Sensitivity Analysis of Pharmacokinetic and Pharmacodynamic Systems: I. A Structural Approach to Sensitivity Analysis of Physiologically Based Pharmacokinetic Models

  • Published:
Journal of Pharmacokinetics and Biopharmaceutics Aims and scope Submit manuscript

Abstract

Based on a frequency response approach to the sensitivity analysis of pharmacokinetic models, the concept of structural sensitivity is introduced. The core of this concept is the factorization of the system sensitivity into two multipliers. The first one, called structural sensitivity index, has an analytical form, which depends solely on the structure and connectivity of the system and does not depend on the drug administered or the factor perturbed. The second multiplier, the parameter sensitivity index, depends on the drug properties, the tissue of interest and the parameter perturbed, but is largely independent of the structure of the system. The structural and parametric sensitivity indices can be evaluated and analyzed separately. The most important feature of the proposed approach is that the conclusions drawn from the analysis of the structural sensitivity index are valid across all mammalian species, as the latter share a common anatomical and physiological structure. The concept of structural sensitivity is illustrated on the commonly used structure of the whole body physiologically based pharmacokinetic models by showing that the factorization of the sensitivity carried out arises naturally from the mechanism of the distribution of perturbations throughout the organism. The concept of structural sensitivity has interesting practical implications. It enables the formal proof of relationships and facts that have been observed previously. Moreover, the conclusions drawn introduce in fact a ranking of the tissues or subsystems with respect to their impact on the model outputs. From this ranking, direct recommendations regarding the design of experiments for whole-body physiologically based pharmacokinetic models are derived.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

REFERENCES

  1. J. P. C. Kleijnen. Sensitivity analysis and related analyses: A review of some statistical techniques. J. Statist. Comput. Simul. 57:111–142 (1997).

    Article  Google Scholar 

  2. R. C. H. Cheng and W. Holland. Sensitivity of computer simulation experiments to errors in input data. J. Statist. Comput. Simul. 57:219–241 (1997).

    Article  Google Scholar 

  3. G. E. B. Archer, A. Saltelli, and I. M. Sobol. Sensitivity measures, ANOVA-like techniques and the use of bootstrap. J. Statist. Comput. Simul. 58:99–120 (1997).

    Article  Google Scholar 

  4. I. Nestorov, L. Aarons, and M. Rowland. Physiologically based pharmacokinetic modelling of a homologous series of barbiturates in the rat. A sensitivity analysis. J. Pharmacokin. Biopharm. 25:413–447 (1997).

    Article  CAS  Google Scholar 

  5. R. A. Yetter, F. L. Dryer, and H. Rabitz. Some interpretative aspects of elementary sensitivity gradients in combustion kinetics modeling. Combustion Flame 59:107–133 (1985).

    Article  CAS  Google Scholar 

  6. M. V. Evans, W. D. Crank, H.-M. Yang, and J. E. Simmons. Applications of sensitivity analysis to a physiologically based pharmacokinetic model for carbon tetrachloride in rats. Toxicol. Appl. Pharmacol. 128:36–44 (1994).

    Article  CAS  PubMed  Google Scholar 

  7. D. M. Hetrick, A. M. Jarabek, and C. C. Travis. Sensitivity analysis for physiologically based pharmacokinetic models. J. Pharmacokin. Biopharm. 19:1–20 (1991).

    CAS  Google Scholar 

  8. P. Varkonyi, J. V. Bruckner, and J. M. Gallo. Effect of parameter variability on physiologically-based pharmacokinetic model predicted drug concentrations. J. Pharm. Sci. 84:381–384 (1995).

    Article  CAS  PubMed  Google Scholar 

  9. R. C. Spear, F. Y. Bois, T. Woodruff, D. Auslander, J. Parker, and S. Selvin. Modeling benzene pharmacokinetics across three sets of animal data: Parametric sensitivity and risk implications. Risk Anal. 11:641–654 (1991).

    Article  CAS  PubMed  Google Scholar 

  10. K. Thomaseth. PANSYM: A symbolic equation generator for mathematical modelling, analysis and control of metabolic and pharmacokinetic systems. Comput. Meth. Prog. Biomed. 42:99–112 (1994).

    Article  CAS  Google Scholar 

  11. P. M. Schlosser, T. Holcomb, and J. E. Bailey. Determining metabolic sensitivity coefficient directly from experimental data. Bioechn. Bioeng. 41:1027–1038 (1993).

    Article  CAS  Google Scholar 

  12. J. L. Gabrielsson and T. Groth. An extended physiological pharmacokinetic model of methadone disposition in the rat: Validation and sensitivity analysis. J. Pharmacokin. Biopharm. 16:183–201 (1988).

    Article  CAS  Google Scholar 

  13. K. Godfrey. Compartmental Models and Their Application, Academic Press, 1983.

  14. D. A. Anderson. Compartmental Modeling and Tracer Kinetics. Lecture Notes in Biomathematics, Vol. 50, Springer-Verlag, Heidelberg, 1983, p. 302.

    Google Scholar 

  15. M. Eslami. Theory of Sensitivity in Dynamic Systems. An Introduction, Springer-Verlag, Heidelberg, 1994, p. 600.

    Book  Google Scholar 

  16. Y. Z. Tsipkin. Basics of Automatic Systems Theory [In Russian]. Nauka, Moscow, 1977, pp. 88–101.

    Google Scholar 

  17. G. J. Murphy. Basic Automatic Control Theory, van Nostrand, Princeton, NJ, 1957, p. 832.

    Google Scholar 

  18. J. M. van Rossum, J. E. G. M. de Bie, G. van Lingen, and H. W. A. Teeuwen. Pharmacokinetics from a dynamical systems point of view. J. Pharmacokin. Biopharm. 17:365–397 (1989).

    Article  CAS  Google Scholar 

  19. L. Dedik and M. Durisova. Frequency response method in pharmacokinetics. J. Pharmacokin. Biopharm. 22:293–307 (1994).

    Article  CAS  Google Scholar 

  20. I. A. Nestorov, L. J. Aarons, P. A. Arundel, and M. Rowland. Lumping of whole-body physiologically based pharmacokinetic models. J. Pharmacokin. Biopharm. 26:21–46 (1998).

    Article  CAS  Google Scholar 

  21. L. E. Gerlovski and R. K. Jain. Physiologically based pharmacokinetic modeling: Principles and applications. J. Pharm. Sci. 72:1103–1129 (1983).

    Article  Google Scholar 

  22. M. C. Kohn. The importance of anatomical realism for validation of physiological models of disposition of inhaled toxicants. Toxicol. Appl. Pharmacol. 147:448–458 (1997).

    Article  CAS  PubMed  Google Scholar 

  23. A. Bernareggi and M. Rowland. Physiological modeling of cyclosporine kinetics in rat and man. J. Pharmacokin. Biopharm. 19:21–50 (1991).

    Article  CAS  Google Scholar 

  24. D. Krewski, Y. Wang, S. Bartlett, and K. Krishnan. Uncertainty, variability, and sensitivity analysis in physiological pharmacokinetic models. J. Biopharm. Statist. 5:245–271 (1995).

    CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nestorov, I.A. Sensitivity Analysis of Pharmacokinetic and Pharmacodynamic Systems: I. A Structural Approach to Sensitivity Analysis of Physiologically Based Pharmacokinetic Models. J Pharmacokinet Pharmacodyn 27, 577–596 (1999). https://doi.org/10.1023/A:1020926525495

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1020926525495

Navigation