Silvia Maria Lavezzi1,2, Jan de Jong3, Martine Neyens4, Paula Cramer5, Fatih Demirkan6, Graeme Fraser7, Nancy Bartlett8, Marie-Sarah Dilhuydy9, Javier Loscertales10, Abraham Avigdor11, Simon Rule12, Olga Samoilova13, Andre Goy14, Siddhartha Ganguly15, Mariya Salman16, Angela Howes17, Michelle Mahler16, Giuseppe De Nicolao1, Italo Poggesi18. 1. Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Pavia, Italy. 2. Quantitative Clinical Development, PAREXEL International, Dublin 8, Ireland. 3. Janssen R&D, San Diego, California, USA. 4. Janssen R&D, Beerse, Belgium. 5. German CLL Study Group, University Hospital of Cologne, Cologne, Germany. 6. Dokuz Eylul University, Izmir, Turkey. 7. Juravinski Cancer Centre, McMaster University, Hamilton, Ontario, Canada. 8. Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri, 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, New Jersey, USA. 15. University of Kansas Medical Center, Kansas City, Kansas, USA. 16. , Raritan, New Jersey, USA. 17. Janssen R&D, High Wycombe, UK. 18. Global Clinical Pharmacology, Quantitative Sciences, Janssen-Cilag SpA, Via Michelangelo Buonarroti 23, 20093, Cologno Monzese, MI, Italy. ipoggesi@its.jnj.com.
Abstract
INTRODUCTION: In the HELIOS trial, bendamustine/rituximab (BR) plus ibrutinib (BR-I) improved disease outcomes versus BR plus placebo in previously treated chronic lymphocytic leukemia/small lymphocytic lymphoma. Here, we describe the pharmacokinetic (PK) observations, along with modeling to further explore the interaction between ibrutinib and rituximab. METHODS:578 subjects were randomized to ibrutinib or placebo with BR (6 cycles). Ibrutinib PK samples and tumor measurements were obtained from all subjects; a subset was evaluated for bendamustine and rituximab PK. Population rituximab PK was assessed using nonlinear mixed-effects modeling. RESULTS: Dose-normalized plasma concentration-time bendamustine data were comparable between the arms. Systemic rituximab exposure was higher with BR-I versus BR; mean trough serum concentrations were 2- to 3-fold higher in the first three cycles and 1.2- to 1.7-fold higher subsequently. No relevant safety differences were observed. In the modeling, including treatment arm as a categorical covariate and tumor burden as a continuous time-varying covariate on overall rituximab clearance significantly improved fitting of the data. CONCLUSIONS: BR-I led to higher dose-normalized systemic rituximab exposure versus BR and more rapid steady-state achievement. The modeling data suggest that rituximab disposition is, at least in part, target mediated. Determining the clinical significance of these findings requires further assessments. TRIAL REGISTRATION: This study is registered at https://clinicaltrials.gov/ct2/show/NCT01611090 .
RCT Entities:
INTRODUCTION: In the HELIOS trial, bendamustine/rituximab (BR) plus ibrutinib (BR-I) improved disease outcomes versus BR plus placebo in previously treated chronic lymphocytic leukemia/small lymphocytic lymphoma. Here, we describe the pharmacokinetic (PK) observations, along with modeling to further explore the interaction between ibrutinib and rituximab. METHODS: 578 subjects were randomized to ibrutinib or placebo with BR (6 cycles). Ibrutinib PK samples and tumor measurements were obtained from all subjects; a subset was evaluated for bendamustine and rituximab PK. Population rituximab PK was assessed using nonlinear mixed-effects modeling. RESULTS: Dose-normalized plasma concentration-time bendamustine data were comparable between the arms. Systemic rituximab exposure was higher with BR-I versus BR; mean trough serum concentrations were 2- to 3-fold higher in the first three cycles and 1.2- to 1.7-fold higher subsequently. No relevant safety differences were observed. In the modeling, including treatment arm as a categorical covariate and tumor burden as a continuous time-varying covariate on overall rituximab clearance significantly improved fitting of the data. CONCLUSIONS: BR-I led to higher dose-normalized systemic rituximab exposure versus BR and more rapid steady-state achievement. The modeling data suggest that rituximab disposition is, at least in part, target mediated. Determining the clinical significance of these findings requires further assessments. TRIAL REGISTRATION: This study is registered at https://clinicaltrials.gov/ct2/show/NCT01611090 .
Authors: Sarah E M Herman; Amber L Gordon; Erin Hertlein; Asha Ramanunni; Xiaoli Zhang; Samantha Jaglowski; Joseph Flynn; Jeffrey Jones; Kristie A Blum; Joseph J Buggy; Ahmed Hamdy; Amy J Johnson; John C Byrd Journal: Blood Date: 2011-03-21 Impact factor: 22.113
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Authors: Michael Hallek; Bruce D Cheson; Daniel Catovsky; Federico Caligaris-Cappio; Guillaume Dighiero; Hartmut Döhner; Peter Hillmen; Michael J Keating; Emili Montserrat; Kanti R Rai; Thomas J Kipps Journal: Blood Date: 2008-01-23 Impact factor: 22.113