Parameterisation affects identifiability of population models

  • Vittal Shivva
  • Julia Korell
  • Ian G. Tucker
  • Stephen B. Duffull
Short Report


Identifiability is an important aspect of model development. In this work, using a simple one compartment population pharmacokinetic model, we show that identifiability of the variances of the random effects parameters are affected by the parameterisation of the fixed effects parameters.


Identifiability Bateman model Parameterisation Population models 



Vittal Shivva was supported by University of Otago Postgraduate Scholarship.

Conflict of interest

The authors declared no conflict of interest.


  1. 1.
    Shivva V, Korell J, Tucker IG, Duffull S (2013) An approach for identifiability of population pharmacokinetic–pharmacodynamic models. CPT Pharmacometrics Syst Pharmacol 2(e49):1–9. doi: 10.1038/psp.2013.25 Google Scholar
  2. 2.
    Bateman H (1910) Solution of a system of differential equations occurring in the theory of radioactive transformations. Proc Camb Philos Soc 15:423–427Google Scholar
  3. 3.
    Garrett ER (1994) The Bateman function revisited: a critical reevaluation of the quantitative expressions to characterize concentrations in the one compartment body model as a function of time with first-order invasion and first-order elimination. J Pharmacokinet Biopharm 22(2):103–128. doi: 10.1007/bf02353538 PubMedCrossRefGoogle Scholar
  4. 4.
    Dost FH (1968) Grundlagen der Pharmakokinetik, vol 2. G. Thieme, Stuttgart, pp 38–47Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Vittal Shivva
    • 1
  • Julia Korell
    • 2
  • Ian G. Tucker
    • 1
  • Stephen B. Duffull
    • 1
  1. 1.School of PharmacyUniversity of OtagoDunedinNew Zealand
  2. 2.Department of Pharmaceutical BiosciencesUppsala UniversityUppsalaSweden

Personalised recommendations