| Autor: |
Marok FZ; Clinical Pharmacy, Saarland University, 66123 Saarbruecken, Germany., Wojtyniak JG; Clinical Pharmacy, Saarland University, 66123 Saarbruecken, Germany.; Dr. Margarete Fischer-Bosch-Institut of Clinical Pharmacology, 70376 Stuttgart, Germany., Fuhr LM; Clinical Pharmacy, Saarland University, 66123 Saarbruecken, Germany., Selzer D; Clinical Pharmacy, Saarland University, 66123 Saarbruecken, Germany., Schwab M; Dr. Margarete Fischer-Bosch-Institut of Clinical Pharmacology, 70376 Stuttgart, Germany.; Departments of Clinical Pharmacology, and of Biochemistry and Pharmacy, University Hospital Tuebingen, 72076 Tuebingen, Germany.; Cluster of Excellence iFIT (EXC2180) 'Image-Guided and Functionally Instructed Tumor Therapies', University Tuebingen, 72076 Tuebingen, Germany., Weiss J; Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, 72076 Tuebingen, Germany.; German Center for Infection Research (DZIF), Heidelberg Partner Site, 69120 Heidelberg, Germany., Haefeli WE; Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, 72076 Tuebingen, Germany.; German Center for Infection Research (DZIF), Heidelberg Partner Site, 69120 Heidelberg, Germany., Lehr T; Clinical Pharmacy, Saarland University, 66123 Saarbruecken, Germany. |
| Abstrakt: |
The antifungal ketoconazole, which is mainly used for dermal infections and treatment of Cushing's syndrome, is prone to drug-food interactions (DFIs) and is well known for its strong drug-drug interaction (DDI) potential. Some of ketoconazole's potent inhibitory activity can be attributed to its metabolites that predominantly accumulate in the liver. This work aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model of ketoconazole and its metabolites for fasted and fed states and to investigate the impact of ketoconazole's metabolites on its DDI potential. The parent-metabolites model was developed with PK-Sim ® and MoBi ® using 53 plasma concentration-time profiles. With 7 out of 7 (7/7) DFI AUC last and DFI C max ratios within two-fold of observed ratios, the developed model demonstrated good predictive performance under fasted and fed conditions. DDI scenarios that included either the parent alone or with its metabolites were simulated and evaluated for the victim drugs alfentanil, alprazolam, midazolam, triazolam, and digoxin. DDI scenarios that included all metabolites as reversible inhibitors of CYP3A4 and P-gp performed best: 26/27 of DDI AUC last and 21/21 DDI C max ratios were within two-fold of observed ratios, while DDI models that simulated only ketoconazole as the perpetrator underperformed: 12/27 DDI AUC last and 18/21 DDI C max ratios were within the success limits. |
