A multi drug disposition model accounting for rituximab antigen binding portion (Fab) and crystallizable (Fc) mediated drug disposition mechanisms
D Ternant, O Le Tilly, V. Gouilleux-Gruart, C Desvignes, O Casasnovas, T Lamy, S Leprêtre, D Mulleman, G Cartron, G Paintaud
University of Tours, France
Objectives: Rituximab, an anti-CD20 monoclonal antibody, has been approved in several diseases involving CD19+ B cells, including non-Hodgking lymphoma (NHL), chronic lymphocytic leukemia (CLL) and rheumatoid arthritis (RA). Rituximab pharmacokinetics was reported in more than 20 publications and displays considerable differences among treated diseases.[1-2] These differences were partly explained by the binding of rituximab by its Fab portion to target antigen (target-mediated drug disposition, TMDD)[3] but have still not been fully understood. This study aimed at investigating mechanisms of distribution and elimination mediated by Fab and Fc portions of rituximab using an integrated multi-TMDD model.[4]
Methods: Concentration-time data from NHL (n=108) [5], CLL (n=118) [6] and RA (n=90) [7] patients were gathered to refine a previous two-compartment pharmacokinetic model with target-mediated irreversible binding (IB) elimination.[3] Several strategies and scenarios were tested, compared and selected using difference in Bayesian Information Criterion (ΔBIC). In this new analysis, rituximab was assumed to be protected from elimination by neonatal receptor (FcRn). This protection was described using a FcRn-mediated disposition model similar to previous published models [8,9], but which assumed rituximab elimination, as well as protection from elimination, occuring between central and peripheral compartments. Rituximab was moreover assumed to be distributed to target cells from both central and peripheral compartments. This distribution was described using the TMDD Wagner’s approximation. A supplemental elimination of unbound rituximab from central compartment was described by first-order elimination rate constant. The association of covariates, i.e. underlying disease (NHL, CLL or RA), CD19 (target cells) count, metabolic tumor volume (MTV, in NHL patients), was tested on parameter distributions using likelihood ratio test (LRT). Nonlinear mixed-effects modeling approach was applied using MONOLIX software (Lixoft®, Antony, France).
Results: A total of 3171 rituximab concentrations were available in the 316 patients. The two-compartment pharmacokinetic model with FcRn-mediated protection from intercompartment degradation of rituximab led to a better concentration-time data description than the conventional two-compartment model (ΔBIC=-390). Data description was improved using target cell exchange compartements with both central (ΔBIC=-274) and peripheral (ΔBIC=-6.90) pharmacokinetic compartments. Dissociation constants (KD) of rituximab from FcRn, or from target cells in central and peripheral exchange compartments were 269, 307 and 806 nM, respectively. The amount of FcRn molecules bound to rituximab in the pharmacokinetic compartment space (QFcRn=5030 nM) increased with CD19 count (p=1.35.10-10). Second-order rituximab-target elimination rate constant (kdeg=1.16.10-4 nM-1day-1) increased with CD19 count (p<10-10). Baseline amounts of target cells in central (TC0=275 nM) and peripheral (TP0=323 nM) compartments both increased with MTV (both p<10-10). Surprisingly, baseline target amount (R0=1740 nM) was independent of target amount (CD19 counts or MTV). Underlying disease added no more significant information on parameter distributions.
Conclusions: The KD values of FcRn binding and of target cells in exchange compartments are of the same order than interactions of monoclonal antibodies with FcRn [10] and/or low affinity Fc gamma receptors (FcgRIIA, FcgRIIIA).[11] Rituximab protection from elimination is increased for high CD19 counts, which may explain its long elimination half-life reported in CLL. [2,6] In addition to refine rituximab target-mediated elimination via its Fab portion, this study suggests that rituximab disposition is influenced by complex mechanisms involving its Fc portion with FcRn and FcgR expressing cells, notably non-tumor and tumor B cells, and tumor-infiltrating immune cells (macrophages, NK cells). Therefore, TMDD of mAbs might be made of both Fab (« FabMDD ») and Fc (« FcMDD ») mechanisms.
References:
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