Key result
A physiologically based pharmacokinetic model successfully predicted metoprolol disposition in healthy, CKD, and AMI populations, with all PK parameters falling within a 2-fold error range.
Why the study?
This study sought to assess the pharmacokinetics of metoprolol in healthy populations, chronic kidney disease, and acute myocardial infarction by developing and evaluating physiologically based pharmacokinetic models.
Can physiologically based pharmacokinetic (PBPK) models accurately predict metoprolol disposition in healthy individuals and those with CKD or AMI?
Can physiologically based pharmacokinetic (PBPK) models accurately predict metoprolol disposition in healthy individuals and those with CKD or AMI?
PBPK modeling can accurately predict metoprolol pharmacokinetics in patients with CKD and AMI, potentially aiding in dose optimization for these populations.
PBPK models may inform metoprolol dosing in AMI and CKD; leaves open prospective validation before practice change.
High Resolution Image Download MS PowerPoint Slide The evolution in the development of drugs has increased the popularity of physiologically based pharmacokinetic (PBPK) models. This study seeks to assess the PK of metoprolol in populations with healthy, chronic kidney disease (CKD), and acute myocardial infarction (AMI) conditions by developing and evaluating PBPK models. An extensive literature review for identifying and selecting plasma concentration vs time profile data and other drug-related parameters was undergone for their integration into the PK-Sim program followed by the development of intravenous, oral, and diseased models. The developed PBPK model of metoprolol was then evaluated using the visual predictive checks, mean observed/predicted ratios ( R obs/pre ), and average fold error for all PK parameters, i.e., the area under the curve (AUC), maximal plasma concentration, and clearance. The model evaluation depicted that none of the PK parameters were out of the allowed range (2-fold error) in the case of the mean R obs/pre ratios. The model anticipations were executed to determine the influence of diseases on unbound and total AUC after the application of metoprolol in healthy, moderate, and severe CKD. The dosage reductions were also suggested based on differences in unbound and total AUC in different stages of CKD. The developed PBPK models have successfully elaborated the PK changes of metoprolol occurring in healthy individuals and those with renal and heart diseases (CKD & AMI), which may be fruitful for dose optimization among diseased patients.
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Zamir et al. (2023) studied Healthy, chronic kidney disease (CKD), and acute myocardial infarction (AMI). Metoprolol was evaluated on Pharmacokinetic parameters (AUC, maximal plasma concentration, and clearance). A physiologically based pharmacokinetic model successfully predicted metoprolol disposition in healthy, CKD, and AMI populations, with all PK parameters falling within a 2-fold error range.
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