Meloxicam, used for treating inflammatory diseases, shows large differences in metabolism according to CYP2C9 genetic polymorphisms; however, there are few studies on dose regimen setting based on quantitative predictions. The aim of this study was to determine the appropriate meloxicam dose regimen for each genotype through population pharmacokinetic-pharmacodynamic modeling of meloxicam by considering CYP2C9 genetic polymorphisms. For modeling, previously reported pharmacokinetic (plasma concentration)-pharmacodynamic (inhibition of thromboxane B2 generation) data of meloxicam were collected for CYP2C9 genetic polymorphisms (n=43). And these data were mainly used in the modeling process. Through simulations of the established models, steady-state pharmacokinetic-pharmacodynamic profiles were obtained according to meloxicam multiple exposures for each CYP2C9 genotype, and predictions were made based on dose regimen changes. Genetic polymorphisms of CYP2C9 were identified as key covariates that significantly affected pharmacokinetic variability of meloxicam between individuals. The developed meloxicam population pharmacokinetic-pharmacodynamic model predicted pharmacokinetic results of the 7.5mg meloxicam administration groups (n=26) for CYP2C9*1/*1 and *1/*3 as an external validation. The results of model simulation revealed that the differences were 2.39-5.42 times for steady-state mean plasma concentrations and 1.21-1.71 times for the degree of inhibition of thromboxane B2 generation following multiple exposures for CYP2C9*1/*1 versus *1/*13, *1/*3, and *3/*3. This suggested that thromboxane B2 inhibition following increased plasma exposure to meloxicam differed significantly according to CYP2C9 genetic polymorphisms. The dose of meloxicam in CYP2C9*1/*13, *1/*3, and *3/*3 was randomly adjusted to 1.6-15 mg to approximate the mean thromboxane B2 inhibition for CYP2C9*1/*1 at steady state, the dose intervals varied from 24 h to 48 h. The results suggested that clinical dose adjustment of meloxicam would be necessary to account for CYP2C9 genetic polymorphisms and reduce side effects. This study suggests a clearer direction for setting up clinical therapy based on personalized medicine and quantitative predictions for meloxicam.
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