Metoprolol Population Pharmacokinetics in Older Chinese Patients With CKM Syndrome: Joint Effects of rs1065852 and <scp> CKM ₂ S ₂ </scp> ‐ <scp>BAG</scp> Score on Clearance

ABSTRACT Older adults are vulnerable to adverse drug reactions due to multimorbidity, frailty and polypharmacy. In those with cardiovascular‐kidney‐metabolic (CKM) syndrome, CKM‐related multi‐organ burden may further alter drug disposition and elevate risk. Metoprolol exposure varies widely among individuals, and higher plasma concentrations have been associated with falls in prior studies. We aimed to develop a population pharmacokinetic (PopPK) model of metoprolol in older Chinese patients with CKM syndrome using real‐world data, identify key covariates affecting clearance, and perform model‐based dose simulations. The PopPK analysis included sparse real‐world data from 42 older adults (60–93 years) receiving immediate‐release metoprolol tartrate. Candidate covariates included demographics, genetic polymorphism, laboratory variables, comorbidities, frailty phenotype, SARC‐F score, age‐adjusted Charlson Comorbidity Index, CKM stage and CKM 2 S 2 ‐BAG score. Model‐based simulations were conducted across predefined genotype‐ and disease‐burden strata to evaluate dosing scenarios against literature‐based thresholds. Metoprolol pharmacokinetics were adequately described by a one‐compartment model with first‐order absorption and elimination. The rs1065852 T/T genotype and a high CKM 2 S 2 ‐BAG score (&gt; 11) were associated with lower apparent clearance ( CL/F ), resulting in approximately 32% and 30% reductions in CL/F , respectively, and reduced interindividual variability in CL/F from 46.9% to 39.9%. Simulations identified subgroup‐specific dosing regimens that maintained steady‐state trough concentrations within a literature‐derived range. In older Chinese patients with CKM syndrome, rs1065852 and CKM‐related burden influenced metoprolol clearance and accounted for a considerable part of the observed variability between individuals. This study provides a model‐informed framework for exposure‐threshold‐based dose stratification. Prospective validation with clinical outcomes and comprehensive CYP2D6 genotyping is warranted.