A Comparison of Minimal Pharmacokinetic Models for an Anti-diabetic Agent

  • May Anne E. Mata University of the Philippines Mindanao
Keywords: pharmacokinetic models, modelling diabetes, metformin, regression analysis, Akaike information criterion, parameter estimation, glucose-insulin system


In diabetes studies, pharmacologists rely on statistical techniques tied with experimental results to describe the plasma concentration of an anti-diabetic agent. However, these sets of statistical information only provide minimal inference to the drug’s kinetics. To understand the effect of an anti-diabetic agent to a glucose-insulin system, it is necessary to predict its movement in the system over a specific time interval. In this study, a set of simple pharmacokinetic models was formulated to describe the dynamics of the plasma concentration of an anti-diabetic agent known as metformin. The models were fitted to empirical data via nonlinear regression analysis and were compared using Akaike information criterion to determine the most reasonable model and parameter estimates. The results reveal that models considering varying absorption rate have a promising fit. These models can be extended to multiple drug dosage cases and can be used to estimate rate constants associated to other anti-diabetic agents.

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Author Biography

May Anne E. Mata, University of the Philippines Mindanao

Department of Math, Physics, and Computer Science, University of the Philippines Mindanao

Institute of Applied Mathematics, The University of British Columbia


Figure 1. The best fit curves (solid curves) of Models 1-3 and 11 data points (open squares) representing mean observed values of metformin plasma concentration after oral administration of 500 mg tablet within 12 hours.