Population Pharmacokinetic Modeling of Zaltoprofen in Healthy Adults: Exploring the Dosage Regimen - Ji-Hun Jang; Seung-Hyun Jeong; Yong-Bok Lee (MDPI AG, 2023)
Zaltoprofen is a drug used for various pain and inflammatory diseases. Scientific and quantitative dosage regimen studies regarding its clinical application are scarce. This study aimed to discover effective covariates related to interindividual pharmacokinetic variability through population pharmacokinetic modeling for zaltoprofen and to explore dosage regimens. The bioequivalence results of healthy Korean males, biochemical analysis, and CYP2C9 genotyping information were utilized in modeling. The established model has been sufficiently verified through a bootstrap, goodness-of-fit, visual predictive check, and normalized prediction distribution error. External data sets derived from the literature were used for further model validation. The final model could be used to verify the dosage regimen through multiple exposure simulations according to the numerical change of the selected covariates. Zaltoprofen pharmacokinetics could be explained by a two-compartment with a first-order absorption model. Creatinine clearance (CrCL) and albumin were identified as effective covariates related to interindividual zaltoprofen pharmacokinetic variability, and they had positive and negative correlations with clearance (CL/F), respectively. The differences in pharmacokinetics between individuals according to CYP2C9 genetic polymorphisms (*1/*1 and *1/*3) were not significant or valid covariates. The model simulation confirmed that zaltoprofen pharmacokinetics could significantly differ as the CrCL and albumin levels changed within the normal range. Steady-state plasma exposure to zaltoprofen was significantly reduced in the group with CrCL and albumin levels of 130 mL/min and 3.5 g/dL, respectively, suggesting that dose adjustment may be necessary. This study is useful to guide precision medicine of zaltoprofen and provides scientific quantitative judgment data for its clinical applications.