Description: The talk aims to introduce physiologically based pharmacokinetic (PBPK) model-based approach as a useful tool of model-informed drug development (MIDD) for bridging the “Past” and the “New Horizons” of drug-drug interaction (DDI) studies in special populations. DDIs in patients with chronic kidney disease (CKD) are commonly studied in healthy volunteers to alleviate ethical concerns in the “Past as Prologue”. CKD may affect drug disposition by multiple pathophysiological changes including the changes in abundancy and activity of hepatic drug enzymes and transporters. Also, the disease factors may interplay with DDI in patients with CKD causing a different DDI scenario from the one in healthy volunteers. The translation of DDI magnitude between healthy volunteers and patients with CKD may not be straightforward due to the complex drug-drug-disease interaction (DDDI) scenarios, whereas PBPK model-based approach may serve as a valuable quantitative tool as “Bridges to New Horizons” to predict the complex DDDI. Herein, we present an overview of the impact of severe renal disease on hepatic enzymes (CYP and non-CYP enzymes) and transporters (OATP1B1/3 and BCRP). Then, we illustrate the best practice of using PBPK modelling for DDDI prediction. The usefulness of PBPK modelling will be demonstrated with the case study of statin-roxadustat DDI mediated by hepatic enzymes and transporters in patients with severe CKD. The case study has been published in the paper entitled “Understanding Statin-Roxadustat Drug–Drug-Disease Interaction Using Physiologically-Based Pharmacokinetic Modeling” in Clinical Pharmacology & Therapeutics in 2023.
Learning Objectives:
The audience will learn the overview of the impact of severe renal disease factors on the PK and DDI. Additionally, they will hear about PBPK as a state-of-the-art tool to assess the complex interaction between drug-drug-disease interaction in lieu of a clinical trial. The audience will see the best practice to develop and validate a robust PBPK model through four-way cross-validation for decoding such complex DDI scenarios. The use of PBPK modelling to inform product information will be demonstrated to the audience with the case study of statin-roxadustat DDI in patients with severe CKD.
