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Lewis Sheiner


2018
Montreux, Switzerland



2017
Budapest, Hungary

2016
Lisboa, Portugal

2015
Hersonissos, Crete, Greece

2014
Alicante, Spain

2013
Glasgow, Scotland

2012
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2011
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2010
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2009
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2008
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2007
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2006
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2005
Pamplona, Spain

2004
Uppsala, Sweden

2003
Verona, Italy

2002
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2001
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2000
Salamanca, Spain

1999
Saintes, France

1998
Wuppertal, Germany

1997
Glasgow, Scotland

1996
Sandwich, UK

1995
Frankfurt, Germany

1994
Greenford, UK

1993
Paris, France

1992
Basel, Switzerland



Printable version

PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe.
ISSN 1871-6032

Reference:
PAGE 27 (2018) Abstr 8499 [www.page-meeting.org/?abstract=8499]


Poster: Drug/Disease modelling - Oncology


I-59 Justin Wilkins Population pharmacokinetic analysis of M7824 (MSB0011359C) in different cancer types

Justin J Wilkins (1), Yulia Vugmeyster (2), Isabelle Dussault (2), Nadia Terranova (3), Akash Khandelwal (4)

(1) Occams, Amstelveen, The Netherlands; (2) EMD Serono Research & Development Institute, Inc., Billerica, MA, USA; (3) Merck Institute for Pharmacometrics, Merck Serono S.A., Lausanne, Switzerland; (4) Merck KGaA, Darmstadt, Germany

Objectives: M7824 is an innovative first-in-class bifunctional fusion protein composed of a human IgG1 monoclonal antibody against programmed death-ligand 1 (PD-L1) fused with 2 extracellular domains of transforming growth factor-beta (TGF-β) receptor II to function as a TGF-β “trap” and has shown promising antitumor activity and manageable safety in phase 1 trials [1]. A population pharmacokinetic (popPK) analysis of M7824 was conducted to assess covariate relationships and time-varying clearance (CL) and to support dosing strategy.

Methods: Pharmacokinetic and covariate data from 644 patients with various solid tumor types enrolled in 2 phase 1 clinical studies of M7824 (NCT02517398 and NCT02699515) were used to develop the popPK model using NONMEM software. Patients received intravenous bi-weekly doses of 0.3, 1, 3, 10, or 20 mg/kg, 500 mg, and 1200 mg for 1 to 58 weeks (as of the analysis cutoff date). Two-compartment models with support for time-constant and alternative time-varying clearance (CL) [2], target-mediated drug disposition (TMDD) and time-varying covariate models [3] were investigated during the analysis. A full covariate modeling approach was followed, in which all covariates of interest were tested on CL and central volume of distribution (V1) simultaneously.

Results: A 2-compartmental linear model was found to provide the best description of M7824 concentration. In the typical patient, CL was estimated to be 0.0158 L/h (relative standard error [RSE], 4.1%; interindividual variability [IIV], 8.1%), V1 to be 3.21 L (RSE, 3.2%; IIV, 8.6%), peripheral volume of distribution (V2) to be 0.483 L (RSE, 9.8%; IIV, 17.5%) and intercompartmental clearance (Q) to be 0.00512 L/h (RSE, 12.3%; IIV, not estimable using these data). Covariates estimated to produce a median change in CL of >10% at baseline, with an asymptotic confidence interval excluding the no-effect value, included body weight (BW), sex, albumin, C-reactive protein, platelet count, tumor size, and tumor type (glioblastoma). Covariates affecting V1 to a similar degree included BW, sex, albumin, and tumor type (pancreatic cancer). BW was the most influential covariate, producing median increases > 20% in both CL and V1 at the high extremes of weight in the population. Both CL and V1 were increased in patients enrolled in the ascending-dose phases of the trials. Incorporation of time-varying clearance models did not result in any significant model improvement, despite widespread prior observation of this behavior in other drugs acting on PD-1 and PD-L1 [2], although treatment duration was relatively short in most subjects included in the current analysis population. Models incorporating TMDD and time-varying covariate effects [3] failed to provide improvement to the model. The results of simulations from the model suggested that the variability in exposure was slightly higher with BW-based dosing than with flat dosing.

Conclusions: The linear popPK model for M7824 described the observed data well and was applied to inform dosing strategy. Simulations demonstrated that variability in exposure was slightly higher in regimens applying body weight-based dosing than in regimens applying flat dosing.



References:
[1] Strauss J, et al. Clin Cancer Res doi:10.1158/1078-0432.CCR-17-2653.
[2] Liu C, et al. Clin Pharmacol Ther 2017;101:657-66.
[3] Wählby U, et al (2004). Br J Clin 2004;58:367-77.