Abstract
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 AUClast (1.27) and Cmax values (1.23) over all studies. For DGI predictions, 18 out of 18 DGI AUClast ratios and 18 out of 18 DGI Cmax 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.
Highlights
Metoprolol is one of the most frequently administered beta-blockers in the U.S with well over 50 million total prescriptions per year [1]
Metoprolol is listed by the U.S Food and Drug Administration (FDA) as a moderately sensitive substrate for clinical drug-drug interaction (DDI) studies as it is predominantly metabolized by cytochrome P450 2D6 (CYP2D6) [3]
Metoprolol enantiomers were modeled as stand-alone compounds, to allow for the implementation of enantioselective CYP2D6 metabolism
Summary
Metoprolol is one of the most frequently administered beta-blockers in the U.S with well over 50 million total prescriptions per year [1]. The gene encoding CYP2D6 is subject to different genetic variations, ranging from null alleles to several-fold amplification [5], resulting in considerable phenotypical interindividual differences in CYP2D6-dependent drug metabolism [6]. CYP2D6 alleles are assigned a value indicating no (0), decreased (0.25 or 0.5), normal function (1), or a copy number variation of a normal function allele (2). As this assignment is based on semiquantitative observations, an activity score of 0.5 does not necessarily imply a reduction of enzymatic activity by 50% [6,8]. Considerable interindividual variability in metoprolol plasma concentrations, caused by genetic components independent of the CYP2D6 genotype, such as the rs5758550 SNP, has been observed [9,10]
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