| Autor: |
Rüdesheim S; Clinical Pharmacy, Saarland University, 66123 Saarbrücken, Germany.; Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, 70376 Stuttgart, Germany., Wojtyniak JG; Clinical Pharmacy, Saarland University, 66123 Saarbrücken, Germany.; Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, 70376 Stuttgart, Germany., Selzer D; Clinical Pharmacy, Saarland University, 66123 Saarbrücken, Germany., Hanke N; Clinical Pharmacy, Saarland University, 66123 Saarbrücken, Germany., Mahfoud F; Department of Internal Medicine III, Cardiology, Angiology, Intensive Care Medicine, Saarland University Medical Center and Saarland University Faculty of Medicine, 66421 Homburg, Germany.; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA., Schwab M; Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, 70376 Stuttgart, Germany.; Departments of Clinical Pharmacology, Pharmacy and Biochemistry University of Tübingen, 72076 Tübingen, Germany.; Cluster of Excellence iFIT (EXC2180) 'Image-Guided and Functionally Instructed Tumor Therapies', University of Tübingen, 72076 Tübingen, Germany., Lehr T; Clinical Pharmacy, Saarland University, 66123 Saarbrücken, Germany. |
| Abstrakt: |
The beta-blocker metoprolol (the sixth most commonly prescribed drug in the USA in 2017) is subject to considerable drug-gene interaction (DGI) effects caused by genetic variations of the CYP2D6 gene. CYP2D6 poor metabolizers (5.7% of US population) show approximately five-fold higher metoprolol exposure compared to CYP2D6 normal metabolizers. This study aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model to predict CYP2D6 DGIs with metoprolol. The metoprolol ( R )- and ( S )-enantiomers as well as the active metabolite α-hydroxymetoprolol were implemented as model compounds, employing data of 48 different clinical studies (dosing range 5-200 mg). To mechanistically describe the effect of CYP2D6 polymorphisms, two separate metabolic CYP2D6 pathways (α-hydroxylation and O -demethylation) were incorporated for both metoprolol enantiomers. The good model performance is demonstrated in predicted plasma concentration-time profiles compared to observed data, goodness-of-fit plots, and low geometric mean fold errors of the predicted AUC last (1.27) and C max values (1.23) over all studies. For DGI predictions, 18 out of 18 DGI AUC last ratios and 18 out of 18 DGI C max ratios were within two-fold of the observed ratios. The newly developed and carefully validated model was applied to calculate dose recommendations for CYP2D6 polymorphic patients and will be freely available in the Open Systems Pharmacology repository. |
