The Effects of a GLP-1 Analog on Glucose Homeostasis in Type 2 Diabetes Mellitus Quantified by an Integrated Glucose Insulin Model

Abstract

In recent years, several glucagon-like peptide-1 (GLP-1)-based therapies for the treatment of type 2 diabetes mellitus (T2DM) have been developed. The aim of this work was to extend the semimechanistic integrated glucose-insulin model to include the effects of a GLP-1 analog on glucose homeostasis in T2DM patients. Data from two trials comparing the effect of steady-state liraglutide vs. placebo on the responses of postprandial glucose and insulin in T2DM patients were used for model development. The effect of liraglutide was incorporated in the model by including a stimulatory effect on insulin secretion. Furthermore, for one of the trials an inhibitory effect on glucose absorption was included to account for a delay in gastric emptying. As other GLP-1 receptor agonists have similar modes of action, it is believed that the model can also be used to describe the effect of other receptor agonists on glucose homeostasis.

Figures

Figure 1

Schematic presentation of the integrated model including glucose, insulin, and liraglutide. Full arrows indicate flows and broken arrows indicate control mechanisms. GC and GP, central and peripheral compartments for glucose; GE2, glucose effect compartment for control of insulin secretion; GA and GT, absorption (GA) and transit (GT) compartment for glucose absorption; I, compartment for insulin distribution; IE, insulin effect compartment for control of glucose elimination; Q, CLG, and CLGI, clearance parameters for glucose; ka, rate constant for glucose absorption; D, glucose dose; CLI, endogenous insulin clearance; kGE2, and kIE, rate constants for the delay of effect compartment concentrations; LC, compartment for liraglutide distribution; LA, depot compartment for liraglutide absorption; kaL, rate constant for liraglutide absorption; CLL, liraglutide clearance.

Figure 2

(Left) Time course for liraglutide concentration. The dots show the geometric mean and the corresponding 95% confidence interval of the data. The solid lines show the geometric mean of the individual predictions (solid line) and the geometric mean of the population predictions (dashed line). (Right) Visual predictive check for the PK model for liraglutide. Solid lines represent median concentrations and dashed lines represent 5th and 95th percentiles. The red lines represent the data and the black lines represent simulations from the model. The shaded area represents the 95% confidence intervals for the model predicted median. Time zero is the time at which the last dose of liraglutide 1.8 mg was administered.

Figure 3

Time courses for plasma glucose and insulin concentrations for trial 1. The dots show the geometric mean and the corresponding 95% confidence interval of the data. The solid lines show the geometric mean of the individual predictions (solid lines) and the geometric mean of the population predictions (dashed lines). Time zero is defined as the time of the first measurement in the MTT, which is 10 minutes before meal ingestion.

Figure 4

Time courses for plasma glucose and insulin concentrations for trial 2. The dots show the geometric mean and the corresponding 95% confidence interval of the data. The solid lines show the geometric mean of the individual predictions (solid lines) and the geometric mean of the population predictions (dashed lines). Time zero is defined as the time of the first measurement in the MTT, which is 15 minutes before meal ingestion.

Figure 5

(Left) Model predicted insulin secretion for the different dose levels for trial 1. (Right) Mean baseline corrected postprandial plasma glucose profiles during the MTTs for trial 1. All placebo data was included in the calculation of the mean, i.e., each subject contributes with three placebo profiles.