A Bayesian PK/PD model for synergy; a case study
La Gamba, F., Jacobs, T., Geys, H., Faes, C.
Janssen Pharmaceutica NV, Turnhoutseweg 30, B-2340 Beerse, Belgium; Center for Statistics, Interuniversity Institute for Biostatistics and statistical Bioinformatics, Campus Diepenbeek, Agoralaan building D, B-3590 Diepenbeek, Belgium
Introduction: The co-administration of two or more treatments can alter underlying body exposure (pharmacokinetic, or PK, interaction) and/or effects (pharmacodynamics, or PD, interaction) of the individual compounds. Studies on drug-drug interactions are usually performed in an in-vitro setting [1].
Objectives: In this work, the co-administration of a novel molecule with a marketed treatment is studied through an in-vivo study, where a continuous safety biomarker under study is assessed at 4 different time points after oral administration of the two drugs.
Methods: The change over time of the biomarker is expressed through an indirect response model [2], where a virtual PK profile of the marketed treatment is assumed to drive the effect [3]. Since previous studies showed no drug-drug interaction at the PK, a pharmacodynamic interaction was assumed by expressing EC50 as a function of both treatments’ doses.
Several studies at different dose level combinations were performed sequentially. A traditional analysis consists of a pooled modeling of all the data simultaneously in a frequentist fashion. Besides the frequentist model, a Bayesian framework is used in order to sequentially pool data collected in different studies. As such, modeling results from one study serves as prior distribution for the analysis of the next study.
Results and Conclusion: Both frequentist and Bayesian models showed a significant pharmacodynamic interaction. Future work will focus on improving the efficiency of the Bayesian nonlinear mixed models performance.
References:
[1] Harbron C. A flexible unifi ed approach to the analysis of pre-clinical combination studies. Stat Med 2010;29(16):1746-56.
[2] Sharma A, Jusko WJ. Characterization of four basic models of indirect pharmacodynamic responses. J Pharmacokinet Biopharm 1996;24:611-635.
[3] Jacqmin P, Snoeck E, van Schaick EA, et al. Modelling Response Time Profi les in the Absence of Drug Concentrations: Defi nition and Performance Evaluation of the KPD Model.
J Pharmacokinet Pharmacodyn 2007;34(1):57-85.
