Nina Hanke (1), Pavel Balazki (2), Stephan Schaller (2), Jose David Gómez-Mantilla (1), Thomas Wendl (3), Thorsten Lehr (4), Ibrahim Ince (1)
Boehringer Ingelheim Pharma GmbH & Co. KG, Germany (1), EsqLABS GmbH, Germany (2), Bayer AG, Germany (3), Saarland University, Germany (4)
Introduction: The success of applications of Physiologically based pharmacokinetic (PBPK) modeling in drug development has led regulatory agencies to demand rigorous demonstration of the predictive capability of a PBPK platform for a specific intended application purpose, such as drug-drug interaction (DDI). Although the PBPK of CYP-mediated DDI is well established in the Open Systems Pharmacology (OSP) software [1], transporter-mediated DDI PBPK is less evaluated. Therefore, connected via the DDI Focus Group of the open source and open science GitHub landscape of Open Systems Pharmacology, PBPK experts from Bayer, Saarland University, Boehringer Ingelheim and EsqLABS are collaborating to establish state of the art qualification packages for transporter substrates.
Objectives: Our objective is to establish and qualify a network of transporter DDI substrate and perpetrator PBPK models for the OSP software (OSPS). An overview of currently available models for different transporter DDIs using an automated PBPK platform qualification of PK-Sim® PBPK M&S tool will be presented, and exemplary transporter DDI assessments using rosuvastatin [2] and verapamil [3] will be highlighted.
Methods: Both rosuvastatin and verapamil models were developed using the open-source PBPK software PK-Sim® as part of the OSPS. The rosuvastatin PBPK model has been developed and DDI studies with previously established models for rifampicin (inhibition of OATP2B1, Pgp, BCRP, OATP1B1/1B3 and CYP2C9), gemfibrozil (inhibition of OATP1B1/1B3, OAT3 and CYP2C9) and probenecid (inhibition of OATP1B1/1B3 and OAT3) as perpetrator drugs were included to qualify the model using in vitro inhibition constants without adjustments. The verapamil PBPK model was developed and validated as a perpetrator for Pgp using digoxin as victim drug.
Results: Currently, the qualification of several transporter substrate PBPK models is ongoing, to assess DDIs using PK-Sim®. The processes implemented to describe the rosuvastatin pharmacokinetics and DDIs were active uptake by OATP2B1, OATP1B1/OATP1B3 and OAT3, active efflux by BCRP and Pgp, metabolism by CYP2C9 and passive glomerular filtration. The good prediction of DDIs was demonstrated by simulated rosuvastatin plasma profiles, DDI AUClast ratios (AUClast during DDI/AUClast without co-administration) and DDI Cmax ratios (Cmax during DDI/Cmax without co-administration), with all simulated DDI ratios within 1.6-fold of the observed values [2]. For the verapamil PBPK model, mechanism-based inactivation of CYP3A4 and non-competitive inhibition of Pgp by the verapamil and norverapamil enantiomers were incorporated based on in vitro literature data, and DDI performance was demonstrated by prediction of DDIs with midazolam, digoxin, rifampicin, and cimetidine, with 21 out of 22 predicted DDI AUC ratios or Ctrough ratios within 1.5-fold of the observed values [3].
Conclusions: Exemplary DDI models for transporter substrates or transporter perpetrator drugs, such as rosuvastatin and verapamil, were built and qualified for the prediction of their pharmacokinetics and transporter-mediated DDIs and will be part of the automated qualification framework. The transporter DDI PBPK models demonstrate good model performance and are freely available in the Open Systems Pharmacology model repository [4], to support future investigations of DDI studies during model-informed drug discovery and development. More qualifications of transporter packages are under development and will be freely available, thanks to the support of different contributors from pharmaceutical companies and universities.
References:
[1] Open Systems Pharmacology. OSP DDI_Qualification_CYP3A4 v11.2 [Internet]. [cited 2024 Feb 26]. Available from: https://github.com/Open-Systems-Pharmacology/OSP-Qualification-Reports/tree/v11.2/DDI_Qualification_CYP3A4
[2] Hanke et al. Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions. Pharm Res. 2021; 38(10): 1645–1661; https://doi.org/10.1007/s11095-021-03109-6
[3] Hanke et al. A Mechanistic, Enantioselective, Physiologically Based Pharmacokinetic Model of Verapamil and Norverapamil, Built and Evaluated for Drug–Drug Interaction Studies. Pharmaceutics. 2020; 12(6): 556; https://doi.org/10.3390/pharmaceutics12060556
[4] Open Systems Pharmacology OSP PBPK substance model library – Release Version 11.2 [Internet]. [cited 2023 Sep 21]. Available from: https://github.com/Open-Systems-Pharmacology/OSP-PBPK-Model-Library/releases/tag/v11.2
Reference: PAGE 32 (2024) Abstr 10826 [www.page-meeting.org/?abstract=10826]
Poster: Methodology - Other topics