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Fundamentals of Population Pharmacokinetic Modelling

Modelling and Software

Abstract

Population pharmacokinetic modelling is widely used within the field of clinical pharmacology as it helps to define the sources and correlates of pharmacokinetic variability in target patient populations and their impact upon drug disposition. This review focuses on the fundamentals of population pharmacokinetic modelling and provides an overview of the commonly available software programs that perform these functions.

This review attempts to define the common, fundamental aspects of population pharmacokinetic modelling through a discussion of the literature describing the techniques and placing them in the appropriate context. An overview of the most commonly available software programs is also provided.

Population pharmacokinetic modelling is a powerful approach where sources and correlates of pharmacokinetic variability can be identified in a target patient population receiving a pharmacological agent. There is a need to further standardize and establish the best approaches in modelling so that any model created can be systematically evaluated and the results relied upon. Various nonlinear mixed-effects modelling methods, packaged in a variety of software programs, are available today. When selecting population pharmacokinetic software programs, the consumer needs to consider several factors, including usability (e.g. user interface, native platform, price, input and output specificity, as well as intuitiveness), content (e.g. algorithms and data output) and support (e.g. technical and clinical).

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References

  1. 1.

    Jelliffe RW, Schumitzky A, Van Guilder M, et al. Individualizing drug dosage regimens: roles of population pharmacokinetic and dynamic models, Bayesian fitting, and adaptive control. Ther Drug Monit 1993; 15: 380–93

  2. 2.

    FDA. Guidance for industry: population pharmacokinetics. US Department of Health and Human Services; Food and Drug Administration; Centre for Drug Evaluation and Research & Centre for Biologics Evaluation and Research, 1999 Feb; CP 1 [online]. Available from URL: http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM072137.pdf?utm_campaign=Google2&utm_source=fdaSearch&utm_medium=website&utm_term=Guidanceforindustrypopulationpharmacokinetics&utm_content=1 [Accessed 2011 Sep 1]

  3. 3.

    Ette EI, Williams PJ. Population pharmacokinetics I: background, concepts, and models. Ann Pharmacother 2004; 38: 1702–6

  4. 4.

    Shen D, Lu Z. Population pharmacokinetics studies with nonlinear mixed effects modeling. SAS Global Forum 2007 [online]. Available from URL: http://www2.sas.com/proceedings/forum2007/148-2007.pdf [Accessed 2011 Aug2]

  5. 5.

    Jelliffe RW. Some comments and suggestions concerning population pharmacokinetic modeling, especially of digoxin, and its relation to clinical therapy [online]. Available from URL: http://www.lapk.org/pubsinfo/pdf/DOX_Tech_Rep_2012-1_4-2-12.pdf [Accessed 2011 Aug 2]

  6. 6.

    D’Argenio DZ. Optimal sampling times for pharmacokinetic experiments. J Pharmacokinet Biopharm 1981; 9: 739–56

  7. 7.

    Jelliffe RW, Gomis P, Schumitzky A. A population model of gentamicin made with a new nonparametric EM algorithm. Los Angeles (CA): Laboratory of Applied Pharmacokinetics, USC School of Medicine, 1990. Technical report no.: 90–4

  8. 8.

    Concordet D, Léger F, Ané C. Population PK/PD analysis. In: Chow S, editor. Encyclopedia of biopharmaceutical statistics. New York: Marcel Dekker, Inc., 2004

  9. 9.

    Bustad A, Terziivanov D, Leary R, et al. Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies. Clin Pharmacokinet 2006; 45: 365–83

  10. 10.

    Jelliffe R, Schumitzky A, Van Guilder M. Population pharmacokinetics/pharmacodynamics modeling: parametric and nonparametric methods. Ther Drug Monit 2000; 22: 354–65

  11. 11.

    Ogungbenro K, Aarons L. Design of population pharmacokinetic experiments using prior information. Xenobiotica 2007; 37: 1311–30

  12. 12.

    Tod M, Jullien V, Pons G. Facilitation of drug evaluation in children by population methods and modelling. Clin Pharmacokinet 2008; 47: 231–43

  13. 13.

    Dartois C, Brendel K, Comets E, et al. Overview of model-building strategies in population PK/PD analyses: 2002–2004 literature survey. Br J Clin Pharmacol 2007; 64: 603–12

  14. 14.

    Pillai GC, Mentre F, Steimer JL. Non-linear mixed effects modeling-from methodology and software development to driving implementation in drug development science. J Pharmacokinet Pharmacodyn 2005; 32: 161–83

  15. 15.

    Aarons L. Software for population pharmacokinetics and pharmacodynamics. Clin Pharmacokinet 1999; 36: 255–64

  16. 16.

    Bauer RJ, Guzy S, Ng C. A survey of population analysis methods and software for complex pharmacokinetic and pharmacodynamic models with examples. AAPS J 2007; 9: E60–83

  17. 17.

    Machado SG, Miller R, Hu C. A regulatory perspective on pharmacokinetic/pharmacodynamic modelling. Stat Methods Med Res 1999; 8: 217–45

  18. 18.

    Aarons L, Balant LP, Mentre F, et al. Population approaches in drug development: report on an expert meeting to discuss population pharmacokinetic/pharmacodynamic software. Eur J Clin Pharmacol 1994; 46: 389–91

  19. 19.

    Buffington DE, Lampasona V, Chandler MH. Computers in pharmacokinetics: choosing software for clinical decision making. Clin Pharmacokinet 1993; 25: 205–16

  20. 20.

    Charles BG, Duffull SB. Pharmacokinetic software for the health sciences: choosing the right package for teaching purposes. Clin Pharmacokinet 2001; 40: 395–403

  21. 21.

    Ette EI, Williams PJ. Population pharmacokinetics II: estimation methods. Ann Pharmacother 2004; 38: 1907–15

  22. 22.

    Dartois C, Lemenuel-Diot A, Laveille C, et al. Evaluation of uncertainty parameters estimated by different population PK software and methods. J Pharmacokinet Pharmacodyn 2007; 34: 289–311

  23. 23.

    Beal SL, Sheiner LB. The NONMEM system. Am Stat 1980; 34: 118–9

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Acknowledgements

No sources of funding were used to assist in the preparation of this review. The authors have no potential conflicts of interest that are directly relevant to the content of this review to declare.

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Correspondence to Dr Mary H. H. Ensom.

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Kiang, T.K.L., Sherwin, C.M.T., Spigarelli, M.G. et al. Fundamentals of Population Pharmacokinetic Modelling. Clin Pharmacokinet 51, 515–525 (2012). https://doi.org/10.1007/BF03261928

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Keywords

  • Pharmacokinetic Parameter
  • Population Pharmacokinetic Modelling
  • Pharmacokinetic Variability
  • Population Pharmacokinetic Study
  • Target Patient Population