2017 - Budapest - Hungary

PAGE 2017: Drug/Disease modelling - Oncology
Silvia Maria Lavezzi

Modelling of rituximab clearance reduction due to ibrutinib co-administration

Silvia Maria Lavezzi (1), Jan de Jong (2), Martine Neyens (3), Paula Cramer (4), Fatih Demirkan (5), Graeme Fraser (6), Alexander Pristupa (7), Nancy Bartlett (8), Marie-Sarah Dilhuydy (9), Javier Loscertales (10), Abraham Avigdor (11), Simon Rule (12), Olga Samoilova (13), Andre Goy (14), Siddhartha Ganguly (15), Mariya Salman (2), Angela Howes (16), Michelle Mahler (2), Giuseppe De Nicolao (1), Italo Poggesi (17)

(1) Università degli Studi di Pavia, Italy (2) Janssen R&D, USA, (3) Janssen R&D, Belgium, (4) University Hospital of Cologne, German CLL Study Group, Cologne, Germany, (5) Dokuz Eylul University, Izmir, Turkey, (6) McMaster University, Juravinski Cancer Centre, Hamilton, ON, Canada, (7) Regional Clinical Hospital, Ryazan, Russia, (8) Washington University School of Medicine, Siteman Cancer Center, St Louis, MO, USA, (9) Hôpital Haut-Lévêque, Bordeaux, Pessac, France, (10) Hospital Universitario de La Princesa, IIS-IP, Madrid, Spain, (11) Chaim Sheba Medical Center, Tel-Hashomer and Sackler School of Medicine, University of Tel-Aviv, Tel Aviv, Israel, (12) Derriford Hospital, Plymouth, UK, (13) Nizhny Novgorod Regional Clinical Hospital, Nizhny Novgorod, Russia, (14) John Theurer Cancer Center at Hackensack University Medical Center, Hackensack, NJ, USA, (15) University of Kansas Medical Center, Kansas City, KS, USA, (16) Janssen R&D, UK, (17) Janssen R&D, Italy

Objectives: Ibrutinib is an oral covalent inhibitor of Bruton’s tyrosine kinase indicated for the treatment of patients with B cell malignancies such as chronic lymphocytic leukaemia (CLL)/small lymphocytic lymphoma (SLL) [1]. In a recent phase III study (HELIOS), the combination of ibrutinib with bendamustine + rituximab (BR-I) in patients with previously treated CLL or SLL resulted in significant improvements in disease outcomes compared to BR + placebo (BR) [2]. The systemic exposure of rituximab, assessed only at selected sites, was higher in the BR-I arm than in the BR arm [3]. The aim of this work was to explore this difference in rituximab exposure using a modelling approach.

Methods: Rituximab serum concentrations (1174 observations, obtained at day 1 and 15 of cycle 1, predose on day 1 of cycles 2-6 and day 1 of cycles 7-9, in the washout phase) and tumour burden (857 observations, measured as sum of the products of the largest diameters, SPD) were evaluated in 147 patients, given either ibrutinib (n=77, 612 rituximab plasma observations) or placebo (n=70, 562 observations), together with BR. Rituximab pharmacokinetics were assessed using a nonlinear mixed-effects compartmental approach. A model previously reported in the literature [4], which includes a clearance term decreasing exponentially with time, was refined through the evaluation of treatment and SPD as meaningful covariates. Model estimation and simulation were performed with NONMEM version 7.1.0, while model diagnostics and plots were obtained via R version 3.2.4.

Results: The inclusion of both the treatment arm as a categorical covariate on the decay of the time-dependent clearance term, and SPD as a continuous time-varying covariate on overall rituximab clearance (expressed as a power model normalized for baseline) significantly improved the fitting of the data.

Conclusions: A model for describing the interaction between ibrutinib and rituximab in patients enrolled in the HELIOS study was developed, including both treatment arm as a discriminating factor and a clearance term which is dependent on tumour burden. These data suggest that rituximab disposition is, at least in part, target mediated. This finding is in agreement with what was reported in a recent paper [5], in which rituximab clearance was related to CD20 antigen count at baseline. Further modelling work may be needed to have a fully mechanistic representation that further elucidates rituximab disposition.



References:
[1] Ibrutinib prescribing information. https://www.janssenmd.com/pdf/imbruvica/PI-Imbruvica.pdf
[2] Khan AA, Cramer P, Demirkan F, et al. Ibrutinib combined with bendamustine and rituximab compared with placebo, bendamustine, and rituximab for previously treated chronic lymphocytic leukaemia or small lymphocytic lymphoma (HELIOS). The Lancet Oncology. 2016 Feb 1;17(2):200-11.
[3] Systemic Exposure of Rituximab Increased by Ibrutinib: Pharmacokinetic Results from the Helios Trial, 58th ASH annual meeting & exposition 2016, Abstr 4403. https://ash.confex.com/ash/2016/webprogram/Paper89616.html
[4] Li J, Zhi J, Wenger M, et al. Population pharmacokinetics of rituximab in patients with chronic lymphocytic leukemia. The Journal of Clinical Pharmacology. 2012 Dec 1;52(12):1918-26.
[5] Tout M, Gagez AL, Leprêtre S, et al. Influence of FCGR3A-158V/F Genotype and Baseline CD20 Antigen Count on Target-Mediated Elimination of Rituximab in Patients with Chronic Lymphocytic Leukemia: A Study of FILO Group. Clinical Pharmacokinetics. 2016 Oct 25:1-3. doi:10.1007/s40262-016-0470-8.


Reference: PAGE 26 (2017) Abstr 7139 [www.page-meeting.org/?abstract=7139]
Poster: Drug/Disease modelling - Oncology
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