Development of a Physiologically Based Pharmacokinetic Model for Metoprolol in Different CYP2D6 Genotypes

Metoprolol, used in the treatment of hypertension, angina, and heart failure, is primarily metabolized by the CYP2D6 enzyme, which catalyzes alpha‐hydroxylation and O‐demethylation. The genetic polymorphism of CYP2D6 leads to differences in the pharmacokinetics of CYP2D6 substrates. Physiologically based pharmacokinetic (PBPK) modeling is a useful tool for predicting the PK profile of drugs that assess the impact of covariates such as demographics, race, and genetic polymorphism. We tested whether the pharmacokinetics of metoprolol was altered by the different CYP2D6 genotypes in Korean subjects. Then, through in vitro study of metoprolol, the metabolic capacity of metoprolol was measured according to the CYP2D6 genotypes. Finally, we developed the PBPK model of metoprolol related to CYP2D6 genetic polymorphism. Forty‐five volunteers were recruited and grouped as CYP2D6 *wt⁄*wt ( *wt =1 or 2, n=15), CYP2D6 *wt⁄*5 (n=4), CYP2D6 *wt/*10 (n=9), CYP2D6 *10⁄*10 (n=10), CYP2D6 *5/*10 (n=5) and CYP2D6 *5/*5 (n=2) according to their genotypes. Metoprolol tartrate 100 mg (Betaloc®) was administered orally once to each subject in these six groups. The CYP2D6*1 and CYP2D6*10 were incubated with 10–2000 μM metoprolol for 20 min at 37 □. Then the metabolites were extracted, and the concentration was analyzed by liquid chromatography‐mass spectrometry. The PBPK modeling of metoprolol was developed and optimized using PK‐sim® software. And, PBPK model validation was conducted by comparing the predicted values with observed values from comparison the pharmacokinetic studies. The AUC inf mean of clinical PK data were 492.96, 673.57, 790.15, 2054.61, 3157.16 and 5152.65 ng·h/ml in CYP2D6 *wt⁄*wt , *wt/*10 , *wt⁄*5 , *10⁄*10 , *5⁄*10 and *5⁄*5 , respectively. In vitro study, compared with wild‐type CYP2D6 *1 (100%), the intrinsic clearance (V max /K m ) values of CYP2D6 *10 (0.33 % for α‐hydroxymetoprolol and 0.41 % for O‐desmethylmetoprolol) were significantly altered. Depending on the physico‐chemical parameters, absorption, distribution, metabolism, excretion (ADME) of each genotype, PBPK model of metoprolol was developed using PK‐sim® software. The AUC inf mean of simulated PK data were 468.01, 646.33, 804.03, 2100.12, 3003.65 and 5677.73 ng·h/ml in CYP2D6 *wt⁄*wt , *wt/*10 , *wt⁄*5 , *10⁄*10 , *5⁄*10 and *5⁄*5 , respectively. The developed PBPK model of metoprolol successfully described the pharmacokinetics of each CYP2D6 genotype group and its simulated values were within acceptance criterion (99.998% confidence interval). We developed a PBPK model of metoprolol in relation to genetic polymorphism, which predicts the pharmacokinetics of metoprolol, considering demographic data of subjects, physico‐chemical parameters, ADME properties and CYP2D6 genotypes. These results demonstrate the possibility of metoprolol prescription considering the individual genetic differences through this mechanical approach. Furthermore, the PBPK modeling of metoprolol in CYP2D6 genotypes will be applicable to the treatment of various races, ages, and patients. Support or Funding Information This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future Planning. The observed and predicted metoprolol pharmacokinetic profiles in CYP2D6*wt/*wt, CYP2D6*wt/*10, CYP2D6*wt/*5, CYP2D6*10/*10, CYP2D6*5/*10 and CYP2D6*5/*5 groups. Figure 1