A physiologically-based pharmacokinetic model of ruxolitinib and posaconazole to predict CYP3A4-mediated drug–drug interaction frequently observed in graft versus host disease patients

Please always quote using this URN: urn:nbn:de:bvb:20-opus-297261
  • Ruxolitinib (RUX) is approved for the treatment of steroid-refractory acute and chronic graft versus host disease (GvHD). It is predominantly metabolized via cytochrome P450 (CYP) 3A4. As patients with GvHD have an increased risk of invasive fungal infections, RUX is frequently combined with posaconazole (POS), a strong CYP3A4 inhibitor. Knowledge of RUX exposure under concomitant POS treatment is scarce and recommendations on dose modifications are inconsistent. A physiologically based pharmacokinetic (PBPK) model was developed to investigateRuxolitinib (RUX) is approved for the treatment of steroid-refractory acute and chronic graft versus host disease (GvHD). It is predominantly metabolized via cytochrome P450 (CYP) 3A4. As patients with GvHD have an increased risk of invasive fungal infections, RUX is frequently combined with posaconazole (POS), a strong CYP3A4 inhibitor. Knowledge of RUX exposure under concomitant POS treatment is scarce and recommendations on dose modifications are inconsistent. A physiologically based pharmacokinetic (PBPK) model was developed to investigate the drug–drug interaction (DDI) between POS and RUX. The predicted RUX exposure was compared to observed concentrations in patients with GvHD in the clinical routine. PBPK models for RUX and POS were independently set up using PK-Sim\(^®\) Version 11. Plasma concentration-time profiles were described successfully and all predicted area under the curve (AUC) values were within 2-fold of the observed values. The increase in RUX exposure was predicted with a DDI ratio of 1.21 (C\(_{max}\)) and 1.59 (AUC). Standard dosing in patients with GvHD led to higher RUX exposure than expected, suggesting further dose reduction if combined with POS. The developed model can serve as a starting point for further simulations of the implemented DDI and can be extended to further perpetrators of CYP-mediated PK-DDIs or disease-specific physiological changes.show moreshow less

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Metadaten
Author: Bettina Gerner, Fatemeh Aghai-Trommeschlaeger, Sabrina Kraus, Götz Ulrich Grigoleit, Sebastian Zimmermann, Max Kurlbaum, Hartwig Klinker, Nora Isberner, Oliver Scherf-Clavel
URN:urn:nbn:de:bvb:20-opus-297261
Document Type:Journal article
Faculties:Medizinische Fakultät / Medizinische Klinik und Poliklinik I
Medizinische Fakultät / Medizinische Klinik und Poliklinik II
Fakultät für Chemie und Pharmazie / Institut für Pharmazie und Lebensmittelchemie
Language:English
Parent Title (English):Pharmaceutics
ISSN:1999-4923
Year of Completion:2022
Volume:14
Issue:12
Article Number:2556
Source:Pharmaceutics (2022) 14:12, 2556. https://doi.org/10.3390/pharmaceutics14122556
DOI:https://doi.org/10.3390/pharmaceutics14122556
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:cytochrome P450 3A4 (CYP3A4); drug–drug interactions (DDIs); graft versus host disease; pharmacokinetics; physiologically based pharmacokinetic (PBPK) modeling; posaconazole; ruxolitinib
Release Date:2023/11/15
Date of first Publication:2022/11/22
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International