Abstract

The mean serum half life of rituximab reported in the current approved package insert (February 2007) is 76.3 and 205.8 hours following the first and fourth infusions, respectively. This results is based on data from 14 Non-Hodgkin’s Lymphoma (NHL) patients treated with a dose of 375 mg/m2 weekly × 4 analyzed using non-compartmental analysis (NCA). The aims of the current analysis were:

  1. to develop a population pharmacokinetic (POP PK) model using a large NHL patient population

  2. to investigate possible mechanisms that may explain the observed increase in half-life with time such as a B-cell/tumor burden mediated clearance

  3. to identify covariates as potential predictors of PK variability.

The population PK analysis was performed using NONMEM V based on 3739 rituximab serum concentration samples from 298 patients who received rituximab as a single agent or in combination with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) therapy from six clinical studies. Tested covariates evaluated included body surface area (BSA), gender, age, race, WHO status, baseline CD19+ counts, sum of the tumor perpendicular diameters (SPD) of tumor and CHOP therapy. A non-parametric bootstrap procedure was used to estimate the precision of model parameters, and the model performance was assessed using visual predictive check. Rituximab concentration data were best described by a two-compartment model with time-varying clearance. Total clearance comprised of two terms, a non-specific clearance pathway (CL1), which remains unchanged throughout treatment, and a specific clearance pathway (CL2, B cells/tumor burden mediated), which decreased at a first-order decay rate from its initial value following the first infusion. The typical population estimates of rituximab nonspecific clearance (CL1), specific clearance (CL2), and central compartment volume of distribution (V1) were 0.14 L/day, 0.59 L/day, and 2.7 L, respectively. Age, gender, race, and WHO performance status had no effect on the PK of rituximab. Covariate analysis revealed that patients with higher CD19 counts or SPD of tumor burden at baseline had a higher rituximab CL2, while V1 varied by body surface area (BSA) and CHOP chemotherapy. However, unexplained inter-individual variability remained high for CL2 following correction for CD19/SPD. Changes from typical V1 values contributed by extreme BSA (1.53 to 2.32 m2) and concurrent CHOP therapy, were relatively minor (27.1% and 19.0%) and explained 27.3% and 5.75% of the inter-individual variability in V1, respectively. Dose adjustment for the tested covariates is not expected to result in a meaningful reduction in rituximab PK variability. Retrospective analysis of rituximab PK using non linear mixed effect modeling confirmed that rituximab elimination decreased following multiple infusions. The median of individual estimates of rituximab terminal half-life was 22 days (range, 6.1 to 52 days), which is typical for immunoglobulin isotype IgG in human and is longer than that reported for humanized anti-CD20 clinical candidates, IMMU106 and of atumumab of 12.0 and 14.3 days, respectively.

Author notes

Disclosure: No relevant conflicts of interest to declare.