Stefaan Rossenu, Francesca Del Bene, An Vermeulen, Italo Poggesi
Janssen Research & Development, Beerse, Belgium
Objectives: To develop a PK model combining the use of a top-down (non-linear mixed effects model) with a bottom-up (physiology-based pharmacokinetic model) approach to predict potential drug-drug interactions (DDI), based on the outcome of a single drug-drug interaction trial.
Methods: A PK model for bedaquiline has been reported in the literature [1], based on the outcome of clinical studies in healthy subjects and in subjects with tuberculosis. In the available package of information on bedaquiline, the effect of inhibitors and inducers of CYP3A4 have been assessed following short term repeated doses of bedaquiline and DDI perpetrators [2]. These assessments may not provide the full extent of the DDI due to the inherent long terminal half-life of bedaquiline. To anticipate the level of DDI that can be observed following long term co-medication, simulations were performed based on the non-linear mixed effect PK model developed for bedaquiline. To establish the effect of mild, moderate and potent inhibitors, the physiology-based approach proposed by Ohno [3] was used and the inhibitor parameters reported. For providing different scenarios, different values for the fractional clearance due to CYP3A4 involvement in bedaquiline metabolism (fCYP3A4) were considered (0.75, 0.90, 0.95), compatible with CYP3A4 being responsible for the majority of the bedaquiline clearance. PK simulations at steady state were performed with bedaquiline clearance modulated by strong, moderate and mild CYP3A4 inhibitors.
Results: The simulations indicated that the exposure after long term administration of the combination with a strong CYP3A4 inhibitor provides an AUC increase of 1.80-2.21 fold, dependent on the assumed fCYP3A4 of bedaquiline. As expected, the DDI effect of moderate inhibitors was less extensive than for strong inhibitors, which – considering the observed interindividual variability – appears of minimal or no clinical relevance.
Conclusions: The proposed combination of top-down and bottom-up approaches provides useful information regarding the appropriate use of bedaquiline when clinical data cannot be generated due to logistical/ethical constraints.
References:
[1] McLeay SC, Vis P, van Heeswijk RP, Green, B. Population pharmacokinetics of bedaquiline (TMC207), a novel antituberculosis drug. Antimicrobial agents and chemotherapy, 2014, 58(9):5315-5324.
[2] Dooley KE, Park J-G, Swindells S, Allen R, Haas DW, Cramer Y, Aweeka F, Wiggins I, Gupta A, Lizak P, Qasba S, van Heeswijk R, Flexner C and the ACTG 5267 Study Team. Safety, Tolerability, and Pharmacokinetic Interactions of the Antituberculous Agent TMC207 (Bedaquiline) With Efavirenz in Healthy Volunteers: AIDS Clinical Trials Group Study A5267 J Acquir Immune Defic Syndr 2012, 59 (5): 455–462.
[3] Ohno Y, Hisaka A, Suzuki H. General Framework for the Quantitative Prediction of CYP3A4-Mediated Oral Drug Interactions Based on the AUC Increase by Coadministration of Standard Drugs. Clin Pharmacokinet 2007; 46 (8): 681-696.
Reference: PAGE 24 (2015) Abstr 3560 [www.page-meeting.org/?abstract=3560]
Poster: Methodology - Other topics