A mechanism-based binding model for the population pharmacokinetics and pharmacodynamics of omalizumab

Abstract

Aim: Omalizumab, a humanized IgG monoclonal antibody that binds to human immunoglobulin E (IgE), interrupts the allergic cascade in asthmatic patients. The aim was to compare simultaneously drug exposure and IgE biomarker responses in Japanese and White patient populations.

Methods: An instantaneous equilibrium drug-ligand binding and turnover population model was built from 202 Japanese patients. A posterior predictive evaluation for the steady-state distributions of omalizumab and IgE was then carried out against 531 White patients.

Results: The mean parameters estimated from the Japanese patients were as follows: omalizumab clearance 7.32 +/- 0.153 ml h(-1), IgE clearance 71.0 +/- 4.68 ml h(-1) and the difference between that for omalizumab and the complex 5.86 +/- 0.920 ml h(-1), the volume of distribution for omalizumab and IgE 5900 +/- 107 ml, and that for the complex 3630 +/- 223 ml, the rate of IgE production 30.3 +/- 2.04 microg h(-1). Half-lives of IgG (23 days) and IgE (2.4 days) were close to previous reports. The dissociation constant for binding, 1.07 nM, was similar to in vitro values. Clearance and volume of distribution for omalizumab varied with bodyweight, whereas the clearance and rate of production of IgE were predicted accurately by baseline IgE. Overall, these covariates explained much of the interindividual variability.

Conclusions: The predictiveness of the Japanese model was confirmed by Monte-Carlo simulations for a White population, also providing evidence that the pharmacokinetics of omalizumab and IgE were similar in these two populations. Furthermore, the model enabled the estimation of not only omalizumab disposition parameters, but also the binding with and the rate of production, distribution and elimination of its target, IgE.

Figure 1

The PK/PD model structure

Figure 2

Diagnostic plots for the model. The upper panels show the goodness-of-fit through the relationship between the estimated values (IPRED) and the corresponding observed values with respect to the line of identity. The lower panels show the distributions of individual weight residuals (IWRES) for free and total IgE and omalizumab. The broken lines indicate the S-Plus LOESS local regression lines. The upper limit of quantification for free IgE was 150 ng ml⁻¹. Observations above this value were not quantifiable and could not be plotted

Figure 3

Individual observed serum concentrations of omalizumab, total and free IgE in study 1101 and the 80% prediction intervals of the model predictions. The circles are individual observed values and lines are 10%, 50% and 90% percentiles at each time point calculated from 1000 simulated subjects for each cohort. The dashed line indicates the time of omalizumab administration. The upper limit of quantification for free IgE was 150 ng ml⁻¹. Observations above this value were not quantified and could not be plotted

Figure 4

Median observed serum concentrations of omalizumab, total and free IgE in studies 1305 and 007, and the 95% prediction intervals of the median predicted time course of the respective compound for the given dosing regimen. The circles are observed medians at each time point for each dose and regimen combination, and the lines are the 95% prediction intervals for medians calculated from 1000 simulated subjects at each time point. The data for two dose groups in study 1305 were omitted because the number of subjects was <10

Figure 5

Frequency distribution of trough concentrations at steady state. Comparison of observed values and model predictions after the administration of omalizumab every 2 or 4 weeks in studies 008 and 009. The histograms are the observed distributions of trough concentrations, and the curve shows the distribution of trough concentrations for a simulation of 1000 subjects based on the parameters estimated from studies 1101 and 1305. The vertical line indicates the median of observed values and the hatched area indicates the 95% prediction intervals of the median calculated from the simulation