Galecki, A.T., Wolfinger, R.D., Linares, O.A., Smith, M.J. and Halter, J.B. (2004) Ordinary differential equation PK/PD using the SAS macro NLINMIX. Journal of Biopharmaceutical Statistics, 14(2), 483-503.

has been cited by the following article:

• TITLE: Bayesian analysis of minimal model under the insulin-modified IVGTT

  AUTHORS: Yi Wang, Kent M. Eskridge, Andrzej T. Galecki

  KEYWORDS: Minimal Model; Bayesian Analysis; IVGTT; Nonlinear Mixed-Effects Modeling; ODE

  JOURNAL NAME: Health, Vol.2 No.3, March 23, 2010

  ABSTRACT: A Bayesian analysis of the minimal model was proposed where both glucose and insulin were analyzed simultaneously under the insulin-modified intravenous glucose tolerance test (IVGTT). The resulting model was implemented with a nonlinear mixed-effects modeling setup using ordinary differential equations (ODEs), which leads to precise estimation of population parameters by separating the inter- and intra-individual variability. The results indicated that the Bayesian method applied to the glucose-insulin minimal model provided a satisfactory solution with accurate parameter estimates which were numerically stable since the Bayesian method did not require approximation by linearization.