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Bayesian analysis of minimal model under the insulin-modified IVGTT
University of Nebraska-Lincoln
University of Nebraska-Lincoln
University of Michigan
- 1 University of Nebraska-Lincoln
- 2 University of Nebraska-Lincoln
- 3 University of Michigan
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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.
KeywordsMinimal ModelBayesian AnalysisIVGTTNonlinear Mixed-Effects ModelingODE
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