ORIGINAL RESEARCH article

Front. Pharmacol.

Sec. Drug Metabolism and Transport

Volume 16 - 2025 | doi: 10.3389/fphar.2025.1578643

This article is part of the Research TopicAdvancements and Strategies in Predicting and Managing Clinical Drug-Drug InteractionsView all articles

Physiologically Based Pharmacokinetic Modeling Supports Investigation of Potential Drug-drug Interactions in the Pre-and Early Post-hematopoietic Stem Cell Transplantation Stages

Provisionally accepted
  • Department of Pharmacy, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

The final, formatted version of the article will be published soon.

Introduction: Drug-drug interactions (DDIs) are an important issue in medication safety and a potential cause of adverse drug events in the pre-and early post-hematopoietic stem cell transplantation (HSCT). This study introduced a physiologically based pharmacokinetic (PBPK) modeling platform to evaluate complex DDIs in these critical stages and to optimize dosing for personalized treatment.Methods: PBPK models were developed using a bottom-up with middle-out approach and executed with PK-Sim ® software. Model validation required that predicted PK values fall within a twofold range of observed data. Then, the validated model was used to simulate alternative dosing regimens to achieve target therapeutic levels.Results: PBPK models were developed and evaluated for 13 drugs commonly used in HSCT, including cyclosporine, tacrolimus, sirolimus, busulfan, phenytoin, voriconazole, posaconazole, itraconazole, fluconazole, letermovir, fosaprepitant, aprepitant, and omeprazole.Simulation results indicated marked DDIs in the pre-and early post-HSCT phases, particularly involving cyclosporine and phenytoin. Several drugs notably increased cyclosporine concentrations, while phenytoin substantially reduced the exposure to other medications.This PBPK modeling platform provides a robust tool for identifying and mitigating DDIs in the pre-and early post-HSCT phases. By enabling the optimization of treatment regimens, this model serves as a valuable tool for improving drug safety and therapeutic outcomes for patients with HSCT.

Keywords: HSCT, PBPK modeling, DDIs, pharmacokinetics, Personalized dosing

Received: 18 Feb 2025; Accepted: 23 Apr 2025.

Copyright: © 2025 Wang, Lu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Jing Yang, Department of Pharmacy, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

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