Effects of paroxetine on the pharmacokinetics of atomoxetine and its metabolites in different CYP2D6 genotypes

PBPK modeling to predict the pharmacokinetics of venlafaxine and its active metabolite in different CYP2D6 genotypes and drug-drug interactions with clarithromycin and paroxetine

Venlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI), is indicated for the treatment of major depressive disorder, social anxiety disorder, generalized anxiety disorder, and panic disorder. Venlafaxine is metabolized to the active metabolite desvenlafaxine mainly by CYP2D6. Genetic polymorphism of CYP2D6 and coadministration with other medications can significantly affect the pharmacokinetics and/or pharmacodynamics of venlafaxine and its active metabolite. This study aimed to establish the PBPK models of venlafaxine and its active metabolite related to CYP2D6 genetic polymorphism and to predict drug-drug interactions (DDIs) with clarithromycin and paroxetine in different CYP2D6 genotypes. Clinical pharmacogenomic data for venlafaxine and desvenlafaxine were collected to build the PBPK model. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) characteristics of respective compounds were obtained from previously reported data, predicted by the PK-Sim® software, or optimized to capture the plasma concentration-time profiles. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and plasma concentration-time profiles to the observed data. Predicted plasma concentration-time profiles of venlafaxine and its active metabolite were visually similar to the observed profiles and all predicted AUC and Cmax values for respective compounds were included in the twofold error range of observed values in non-genotyped populations and different CYP2D6 genotypes. When clarithromycin or clarithromycin plus paroxetine was concomitantly administered, predicted plasma concentration-time profiles of venlafaxine properly captured the observed profiles in two different CYP2D6 genotypes and all predicted DDI ratios for AUC and Cmax were included within the acceptance range. Consequently, the present model successfully captured the pharmacokinetic alterations of venlafaxine and its active metabolite according to CYP2D6 genetic polymorphism as well as the DDIs between venlafaxine and two CYP inhibitors. The present model can be used to predict the pharmacokinetics of venlafaxine and its active metabolite considering different races, ages, coadministered drugs, and CYP2D6 activity of individuals and it can contribute to individualized pharmacotherapy of venlafaxine.

Individualized atomoxetine response and tolerability in children with ADHD receiving different dosage regimens: the need for CYP2D6 genotyping and therapeutic drug monitoring to dance together

Integrating CYP2D6 genotyping and therapeutic drug monitoring (TDM) is crucial for guiding individualized atomoxetine therapy in children with attention-deficit/hyperactivity disorder (ADHD). The aim of this retrospective study was (1) to investigate the link between the efficacy and tolerability of atomoxetine in children with ADHD and plasma atomoxetine concentrations based on their CYP2D6 genotypes; (2) to offer TDM reference range recommendations for atomoxetine based on the CYP2D6 genotypes of children receiving different dosage regimens. This retrospective study covered children and adolescents with ADHD between the ages of 6 and <18, who visited the psychological and behavioral clinic of Children's Hospital of Nanjing Medical University from June 1, 2021, to January 31, 2023. The demographic information and laboratory examination data, including CYP2D6 genotype tests and routine TDM of atomoxetine were obtained from the hospital information system. We used univariate analysis, Mann-Whitney U nonparametric test, Kruskal-Wallis test, and the receiver operating characteristic (ROC) curve to investigate outcomes of interest. 515 plasma atomoxetine concentrations of 385 children (325 boys and 60 girls) with ADHD between 6 and 16 years of age were included for statistical analysis in this study. Based on genotyping results, >60% of enrolled children belonged to the CYP2D6 extensive metabolizer (EM), while <40% fell into the intermediate metabolizer (IM). CYP2D6 IMs exhibited higher dose-corrected plasma atomoxetine concentrations by 1.4-2.2 folds than those CYP2D6 EMs. Moreover, CYP2D6 IMs exhibited a higher response rate compare to EMs (93.55% vs 85.71%, P = 0.0132), with higher peak plasma atomoxetine concentrations by 1.67 times than those of EMs. Further ROC analysis revealed that individuals under once daily in the morning (q.m.) dosing regimen exhibited a more effective response to atomoxetine when their levels were ≥ 268 ng/mL (AUC = 0.710, P < 0.001). In addition, CYP2D6 IMs receiving q.m. dosing of atomoxetine were more likely to experience adverse reactions in the central nervous system and gastrointestinal system when plasma atomoxetine concentrations reach 465 and 509 ng/mL, respectively. The findings in this study provided promising treatment strategy for Chinese children with ADHD based on their CYP2D6 genotypes and plasma atomoxetine concentration monitoring. A peak plasma atomoxetine concentration higher than 268 ng/mL might be requisite for q.m. dosing. Assuredly, to validate and reinforce these initial findings, it is necessary to collect further data in controlled studies with a larger sample size.

Physiologically based pharmacokinetic (PBPK) modeling to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes

Irbesartan, a potent and selective angiotensin II type-1 (AT1) receptor blocker (ARB), is one of the representative medications for the treatment of hypertension. Cytochrome P450 (CYP) 2C9 is primarily involved in the oxidation of irbesartan. CYP2C9 is highly polymorphic, and genetic polymorphism of this enzyme is the leading cause of significant alterations in the pharmacokinetics of irbesartan. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes. The irbesartan PBPK model was established using the PK-Sim® software. Our previously reported pharmacogenomic data for irbesartan was leveraged in the development of the PBPK model and collected clinical pharmacokinetic data for irbesartan was used for the validation of the model. Physicochemical and ADME properties of irbesartan were obtained from previously reported data, predicted by the modeling software, or optimized to fit the observed plasma concentration-time profiles. Model evaluation was performed by comparing the predicted plasma concentration-time profiles and pharmacokinetic parameters to the observed results. Predicted plasma concentration-time profiles were visually similar to observed profiles. Predicted AUCinf in CYP2C9*1/*3 and CYP2C9*1/*13 genotypes were increased by 1.54- and 1.62-fold compared to CYP2C9*1/*1 genotype, respectively. All fold error values for AUC and Cmax in non-genotyped and CYP2C9 genotyped models were within the two-fold error criterion. We properly established the PBPK model of irbesartan in different CYP2C9 genotypes. It can be used to predict the pharmacokinetics of irbesartan for personalized pharmacotherapy in individuals of various races, ages, and CYP2C9 genotypes.

Personalizing atomoxetine dosing in children with ADHD: what can we learn from current supporting evidence

PURPOSE

There is marked heterogeneity in treatment response of atomoxetine in patients with attention deficit/hyperactivity disorder (ADHD), especially for the pediatric population. This review aims to evaluate current evidence to characterize the dose-exposure relationship, establish clinically relevant metrics for systemic exposure to atomoxetine, define a therapeutic exposure range, and to provide a dose-adaptation strategy before implementing personalized dosing for atomoxetine in children with ADHD.

METHODS

A comprehensive search was performed across electronic databases (PubMed and Embase) covering the period of January 1, 1985 to July 10, 2022, to summarize recent advances in the pharmacokinetics, pharmacogenomics/pharmacogenetics (PGx), therapeutic drug monitoring (TDM), physiologically based pharmacokinetics (PBPK), and population pharmacokinetics (PPK) of atomoxetine in children with ADHD.

RESULTS

Some factors affecting the pharmacokinetics of atomoxetine were summarized, including food, CYP2D6 and CYP2C19 phenotypes, and drug‒drug interactions (DDIs). The association between treatment response and genetic polymorphisms of genes encoding pharmacological targets, such as norepinephrine transporter (NET/SLC6A2) and dopamine β hydroxylase (DBH), was also discussed. Based on well-developed and validated assays for monitoring plasma concentrations of atomoxetine, the therapeutic reference range in pediatric patients with ADHD proposed by several studies was summarized. However, supporting evidence on the relationship between systemic atomoxetine exposure levels and clinical response was far from sufficient.

CONCLUSION

Personalizing atomoxetine dosage may be even more complex than anticipated thus far, but elucidating the best way to tailor the non-stimulant to a patient's individual need will be achieved by combining two strategies: detailed research in linking the pharmacokinetics and pharmacodynamics in pediatric patients, and better understanding in nature and causes of ADHD, as well as environmental stressors.

Effects of CYP2C19 genetic polymorphism on the pharmacokinetics of tolperisone in healthy subjects

Tolperisone hydrochloride is a centrally-acting muscle relaxant used for relieving spasticities of neurological origin and muscle spasms associated with painful locomotor diseases. It is metabolized to the inactive metabolite mainly by CYP2D6 and, to a lesser extent, by CYP2C19 and CYP1A2. In our previous study, the pharmacokinetics of tolperisone was significantly affected by the genetic polymorphism of CYP2D6, but the wide interindividual variation of tolperisone pharmacokinetics was not explained by genetic polymorphism of CYP2D6 alone. Thus, we studied the effects of CYP2C19 genetic polymorphism on tolperisone pharmacokinetics. Eighty-one subjects with different CYP2C19 genotypes received a single oral dose of 150 mg tolperisone with 240 mL of water, and blood samples were collected up to 12 h after dosing. The plasma concentration of tolperisone was measured by a liquid chromatography-tandem mass spectrometry system. The CYP2C19PM group had significantly higher C_max and lower CL/F values than the CYP2C19EM and CYP2C19IM groups. The AUC_inf of the CYP2C19PM group was 2.86-fold and 3.00-fold higher than the CYP2C19EM and CYP2C19IM groups, respectively. In conclusion, the genetic polymorphism of CYP2C19 significantly affected tolperisone pharmacokinetics.

Effects of CYP2D6*10 allele on the pharmacokinetics of tolperisone

Tolperisone, a muscle relaxant used for post-stroke spasticity, has been reported to have a very wide interindividual pharmacokinetic variability. It is metabolized mainly by CYP2D6 and, to a lesser extent, by CYP2C19 and CYP1A2. CYP2D6 is a highly polymorphic enzyme, and CYP2D6*wt/*wt, CYP2D6*wt/*10 and CYP2D6*10/*10 genotypes constitute more than 90% of the CYP2D6 genotypes in the Korean population. Thus, effects of the CYP2D6*10 on tolperisone pharmacokinetics were investigated in this study to elucidate the reasons for the wide interindividual variability. Oral tolperisone 150 mg was given to sixty-four healthy Koreans, and plasma concentrations of tolperisone were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The CYP2D6*10/*10 and CYP2D6*wt/*10 groups had significantly higher C_max and lower CL/F values than the CYP2D6*wt/*wt group. The AUC_inf of CYP2D6*10/*10 and CYP2D6*wt/*10 groups were 5.18-fold and 2.25-fold higher than the CYP2D6*wt/*wt group, respectively. There were considerable variations in the C_max and AUC values within each genotype group, and the variations were greater as the activity of CYP2D6 decreased. These results suggest that the genetic polymorphism of CYP2D6 significantly affected tolperisone pharmacokinetics and factor(s) other than CYP2D6 may also have significant effects on the pharmacokinetics of tolperisone.

CYP2D6 pharmacogenetics and phenoconversion in personalized medicine

INTRODUCTION

CYP2D6 contributes to the metabolism of approximately 20-25% of drugs. However, CYP2D6 is highly polymorphic and different alleles can lead to impacts ranging from null to increase in activity. Moreover, there are commonly used drugs that potently inhibit the CYP2D6, thus causing 'phenoconversion' which can convert the genotypic normal metabolizer into phenotypic poor metabolizer. Despite growing literature on the clinical implications of non-normal CYP2D6 genotype and phenoconversion on patient-related outcomes, implementation of CYP2D6 pharmacogenetics and phenoconversion to guide prescribing is rare. This review focuses on providing the clinical importance of CYP2D6 pharmacogenetics and phenoconversion in precision medicine and summarizes the challenges and approaches to implement these into clinical practice.

AREAS COVERED

A literature search was performed using PubMed and clinical studies documenting the effects of CYP2D6 genotypes and/or CYP2D6 inhibitors on pharmacokinetics, pharmacodynamics or treatment outcomes of CYP2D6-metabolized drugs, and studies on implementation challenges and approaches.

EXPERT OPINION

Considering the extent and impact of genetic polymorphisms of CYP2D6, phenoconversion by the comedications, and contribution of CYP2D6 in drug metabolism, CYP2D6 pharmacogenetics is essential to ensure drug safety and efficacy. Utilization of proper guidelines incorporating both CYP2D6 pharmacogenetics and phenoconversion in clinical care assists in optimizing drug therapy.

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k_cat) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C9*1/*1 genotype. The ranges of fold errors for AUC_inf, C_max, and t_1/2 were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

Physiologically based pharmacokinetic modelling to predict the pharmacokinetics of metoprolol in different CYP2D6 genotypes

Metoprolol, a selective β₁-adrenoreceptor blocking agent used in the treatment of hypertension, angina, and heart failure, is primarily metabolized by the CYP2D6 enzyme, which catalyzes α-hydroxylation and O-desmethylation. As CYP2D6 is genetically highly polymorphic and the enzymatic activity differs greatly depending on the presence of the mutant allele(s), the pharmacokinetic profile of metoprolol is highly variable depending on the genotype of CYP2D6. The aim of study was to develop the physiologically based pharmacokinetic (PBPK) model of metoprolol related to CYP2D6 genetic polymorphism for personalized therapy with metoprolol. For PBPK modelling, our previous pharmacogenomic data were used. To obtain kinetic parameters (K_m, V_max, and CL_int) of each genotype, the recombinant CYP enzyme of each genotype was incubated with metoprolol and metabolic rates were assayed. Based on these data, the PBPK model of metoprolol was developed and validated in different CYP2D6 genotypes using PK-Sim^® software. As a result, the input values for various parameters for the PBPK model were presented and the PBPK model successfully described the pharmacokinetics of metoprolol in each genotype group. The simulated values were within the acceptance criterion (99.998% confidence intervals) compared with observed values. The PBPK model developed in this study can be used for personalized pharmacotherapy with metoprolol in individuals of various races, ages, and CYP2D6 genotypes.

Physiologically based pharmacokinetic (PBPK) modeling of piroxicam with regard to CYP2C9 genetic polymorphism

Piroxicam is a non-steroidal anti-inflammatory drug used to alleviate symptoms of osteoarthritis and rheumatoid arthritis. CYP2C9 genetic polymorphism significantly influences the pharmacokinetics of piroxicam. The objective of this study was to develop and validate the piroxicam physiologically based pharmacokinetic (PBPK) model related to CYP2C9 genetic polymorphism. PK-Sim^® version 10.0 was used for the PBPK modeling. The PBPK model was evaluated by predicted and observed plasma concentration-time profiles, fold errors of predicted to observed pharmacokinetic parameters, and a goodness-of-fit plot. The turnover number (k_cat) of CYP2C9 was adjusted to capture the pharmacokinetics of piroxicam in different CYP2C9 genotypes. The population PBPK model overall accurately described and predicted the plasma concentration-time profiles in different CYP2C9 genotypes. In our simulations, predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.83-, 2.07-, and 6.43-fold higher than CYP2C9*1/*1 genotype, respectively. All fold error values for AUC, C_max, and t_1/2 were included in the acceptance criterion with the ranges of 0.57-1.59, 0.63-1.39, and 0.65-1.51, respectively. The range of fold error values for predicted versus observed plasma concentrations was 0.11-3.13. 93.9% of fold error values were within the two-fold range. Average fold error, absolute average fold error, and root mean square error were 0.93, 1.27, and 0.72, respectively. Our model accurately captured the pharmacokinetic alterations of piroxicam according to CYP2C9 genetic polymorphism.

Effects of CYP2C9*3 and *13 alleles on the pharmacokinetics and pharmacodynamics of glipizide in healthy Korean subjects

Glipizide is a second-generation sulfonylurea antidiabetic drug. It is principally metabolized to inactive metabolites by genetically polymorphic CYP2C9 enzyme. In this study, we investigated the effects of CYP2C9*3 and *13 variant alleles on the pharmacokinetics and pharmacodynamics of glipizide. Twenty-four healthy Korean volunteers (11 subjects with CYP2C9*1/*1, 8 subjects with CYP2C9*1/*3, and 5 subjects with CYP2C9*1/*13) were recruited for this study. They were administered a single oral dose of glipizide 5 mg. The plasma concentration of glipizide was quantified for pharmacokinetic analysis and plasma glucose and insulin concentrations were measured as pharmacodynamic parameters. The results represented that CYP2C9*3 and *13 alleles significantly affected the pharmacokinetics of glipizide. In subjects with CYP2C9*1/*3 and CYP2C9*1/*13 genotypes, the mean AUC_0-∞ were increased by 44.8% and 58.2%, respectively (both P < 0.001), compared to those of subjects with CYP2C9*1/*1 genotype, while effects of glipizide on plasma glucose and insulin levels were not significantly different between CYP2C9 genotype groups. In conclusion, individuals carrying the defective CYP2C9*3 and CYP2C9*13 alleles have markedly elevated plasma concentrations of glipizide compared with CYP2C9*1/*1 wild-type.

Physiologically based pharmacokinetic modeling of candesartan related to CYP2C9 genetic polymorphism in adult and pediatric patients

Candesartan cilexetil is an angiotensin II receptor blocker and it is widely used to treat hypertension and heart failure. This drug is a prodrug that rapidly converts to candesartan after oral administration. Candesartan is metabolized by cytochrome P450 2C9 (CYP2C9) enzyme or uridine diphosphate glucurinosyltransferase 1A3, or excreted in an unchanged form through urine, biliary tract and feces. We investigated the effect of genetic polymorphism of CYP2C9 enzyme on drug pharmacokinetics using physiologically based pharmacokinetic (PBPK) modeling. In addition, by introducing the age and ethnicity into the model, we developed a model that can propose an appropriate dosage regimen taking into account the individual characteristics of each patient. To evaluate the suitability of the model, the results of a clinical trial on twenty-two healthy Korean subjects and their CYP2C9 genetic polymorphism data was applied. In this study, PK-Sim® was used to develop the PBPK model of candesartan.

Physiologically based pharmacokinetic (PBPK) modeling of meloxicam in different CYP2C9 genotypes

Meloxicam, a non-steroidal anti-inflammatory drug, is used for the treatment of rheumatoid arthritis and osteoarthritis. Cytochrome P450 (CYP) 2C9 and CYP3A4 are major and minor enzymes involved in the metabolism of meloxicam. Impaired enzyme activity of CYP2C9 variants increases the plasma exposures of meloxicam and the risk of adverse events. The objective of our study is to develop and validate the physiologically based pharmacokinetic (PBPK) model of meloxicam related to CYP2C9 genetic polymorphism using the PK-Sim^® software. In vitro k_cat of CYP2C9 was optimized in different CYP2C9 genotypes. The demographic and pharmacokinetic dataset for the development of the PBPK model was extracted from two previous clinical pharmacokinetic studies. Thirty-one clinical datasets, representing different dose regimens and demographic characteristics, were utilized to validate the PBPK model. The shapes of simulated plasma concentration-time profiles in each CYP2C9 genotype were visually similar to observed profiles. The predicted exposures (AUC_inf) of meloxicam in CYP2C9*1/*3, CYP2C9*1/*13, and CYP2C9*3/*3 genotypes were increased by 1.77-, 2.91-, and 8.35-fold compared to CYP2C9*1/*1 genotype, respectively. In all datasets for the development and validations, fold errors between predicted and observed pharmacokinetic parameters were within the two-fold error criteria. As a result, the PBPK model was appropriately established and properly described the pharmacokinetics of meloxicam in different CYP2C9 genotypes. This study is expected to contribute to reducing the risk of adverse events of meloxicam through optimization of meloxicam dosing in different CYP2C9 genotypes.

Physiologically based pharmacokinetic (PBPK) modelling of tamsulosin related to CYP2D6*10 allele

Tamsulosin, a selective [Formula: see text]-adrenoceptor blocker, is commonly used for alleviation of lower urinary tract symptoms related to benign prostatic hyperplasia. Tamsulosin is predominantly metabolized by CYP3A4 and CYP2D6 enzymes, and several studies reported the effects of CYP2D6 genetic polymorphism on the pharmacokinetics of tamsulosin. This study aims to develop and validate the physiologically based pharmacokinetic (PBPK) model of tamsulosin in CYP2D6*wt/*wt, CYP2D6*wt/*10, and CYP2D6*10/*10 genotypes, using Simcyp® simulator. Physicochemical, and formulation properties and data for absorption, distribution, metabolism and excretion were collected from previous publications, predicted in the simulator, or optimized in different CYP2D6 genotypes. The tamsulosin PBPK model in CYP2D6*wt/*wt and CYP2D6*wt/*10 genotypes were developed based on the clinical pharmacokinetic study where a single oral dose of 0.2 mg tamsulosin was administered to 25 healthy Korean male volunteers with CYP2D6*wt/*wt and CYP2D6*wt/*10 genotypes. A previous pharmacokinetic study was used to develop the model in CYP2D6*10/*10 genotype. The developed model was validated using other clinical pharmacokinetic studies not used in development. The predicted exposures via the PBPK model in CYP2D6*wt/*10 and CYP2D6*10/*10 genotype was 1.23- and 1.76-fold higher than CYP2D6*wt/*wt genotype, respectively. The simulation profiles were visually similar to the observed profiles, and fold errors of all development and validation datasets were included within the criteria. Therefore, the tamsulosin PBPK model in different CYP2D6 genotypes with regards to CYP2D6*10 alleles was appropriately established. Our model can contribute to the implementation of personalized pharmacotherapy of patients, appropriately predicting the pharmacokinetics of tamsulosin reflecting their demographic and CYP2D6 genotype characteristics without unnecessary drug exposure.

Physiologically based pharmacokinetic (PBPK) modeling for prediction of celecoxib pharmacokinetics according to CYP2C9 genetic polymorphism

Celecoxib is a non-steroidal anti-inflammatory drug (NSAID) and a representative selective cyclooxygenase (COX)-2 inhibitor, which is commonly prescribed for osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, acute pain, and primary dysmenorrhea. It is mainly metabolized by CYP2C9 and partly by CYP3A4 after oral administration. Many studies reported that CYP2C9 genetic polymorphism has significant effects on the pharmacokinetics of celecoxib and the occurrence of adverse drug reactions. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model of celecoxib according to CYP2C9 genetic polymorphism for personalized pharmacotherapy. Initially, a clinical pharmacokinetic study was conducted where a single dose (200 mg) of celecoxib was administered to 39 healthy Korean subjects with CYP2C9*1/*1 or CYP2C9*1/*3 genotypes to obtain data for PBPK development. Based on the conducted pharmacokinetic study and a previous pharmacokinetic study involving subjects with CYP2C9*1/*13 and CYP2C9*3/*3 genotype, PBPK model for celecoxib was developed. A PBPK model for CYP2C9*1/*1 genotype group was developed and then scaled to other genotype groups (CYP2C9*1/*3, CYP2C9*1/*13 and CYP2C9*3/*3). After model development, model validation was performed with comparison of five pharmacokinetic studies. As a result, the developed PBPK model of celecoxib successfully described the pharmacokinetics of each CYP2C9 genotype group and its predicted values were within the acceptance criterion. Additionally, all the predicted values were within two-fold error range in comparison to the previous pharmacokinetic studies. This study demonstrates the possibility of determining the appropriate dosage of celecoxib for each individual through the PBPK modeling with CYP2C9 genomic information. This approach could contribute to the reduction of adverse drug reactions of celecoxib and enable precision medicine.