Badee, Justine Marine (2024) Building Confidence in Physiologically Based Pharmacokinetic Modeling of CYP3A Induction Mediated by Rifampin: An Industry Perspective. CPT: pharmacometrics & systems pharmacology..

Abstract

Physiologically Based Pharmacokinetic (PBPK) modeling offers a viable approach to predict drug-drug interactions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made with sufficient confidence. In this study, the ability to predict the effect of rifampin, a well-characterized CYP3A4 inducer, on 20 CYP3A probes with publicly available PBPK models, was assessed. Substrates with a range of fm,CYP3A (0.086 to 1.0), Fg (0.11 to 1) and Fh (0.09 to 0.96) were included. Predictions were most likely to be accurate for compounds that are not P-gp substrates or that are P-gp substrates but that have high permeability. Case studies for 3 more challenging DDI predictions (ie, for eliglustat, tofacitinib, and ribociclib) are presented. Along with parameter sensitivity analysis to understand key parameters impacting DDI simulations, alternative model structures should be considered, eg, a mechanistic absorption model instead of a first-order absorption model might be more appropriate for a P-gp substrate with low permeability. Any mechanisms pertinent to the CYP3A substrate that rifampin might impact should be considered for inclusion in the model. While this analysis focused on rifampin, the learnings should apply to other inducers.

Item Type:	Article
Date Deposited:	17 Dec 2024 00:45
Last Modified:	17 Dec 2024 00:45
URI:	https://oak.novartis.com/id/eprint/53929