Impact of Albumin and Omeprazole on Steady-State Population Pharmacokinetics of Voriconazole and Development of a Voriconazole Dosing Optimization Model in Thai Patients with Hematologic Diseases

Influence of C-reactive protein on the pharmacokinetics of voriconazole in relation to the CYP2C19 genotype: a population pharmacokinetics analysis

Voriconazole is a broad-spectrum triazole antifungal agent. A number of studies have revealed that the impact of C-reactive protein (CRP) on voriconazole pharmacokinetics was associated with the CYP2C19 phenotype. However, the combined effects of CYP2C19 genetic polymorphisms and inflammation on voriconazole pharmacokinetics have not been considered in previous population pharmacokinetic (PPK) studies, especially in the Chinese population. This study aimed to analyze the impact of inflammation on the pharmacokinetics of voriconazole in patients with different CYP2C19 genotypes and optimize the dosage of administration. Data were obtained retrospectively from adult patients aged ≥16 years who received voriconazole for invasive fungal infections from October 2020 to June 2023. Plasma voriconazole levels were measured via high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). CYP2C19 genotyping was performed using the fluorescence in situ hybridization method. A PPK model was developed using the nonlinear mixed-effect model (NONMEM). The final model was validated using bootstrap, visual predictive check (VPC), and normalized prediction distribution error (NPDE). The Monte Carlo simulation was applied to evaluate and optimize the dosing regimens. A total of 232 voriconazole steady-state trough concentrations from 167 patients were included. A one-compartment model with first order and elimination adequately described the data. The typical clearance (CL) and the volume of distribution (V) of voriconazole were 3.83 L/h and 134 L, respectively. The bioavailability was 96.5%. Covariate analysis indicated that the CL of voriconazole was substantially influenced by age, albumin, gender, CRP, and CYP2C19 genetic variations. The V of voriconazole was significantly associated with body weight. An increase in the CRP concentration significantly decreased voriconazole CL in patients with the CYP2C19 normal metabolizer (NM) and intermediate metabolizer (IM), but it had no significant effect on patients with the CYP2C19 poor metabolizer (PM). The Monte Carlo simulation based on CRP levels indicated that patients with high CRP concentrations required a decreased dose to attain the therapeutic trough concentration and avoid adverse drug reactions in NM and IM patients. These results indicate that CRP affects the pharmacokinetics of voriconazole and is associated with the CYP2C19 phenotype. Clinicians dosing voriconazole should consider the patient's CRP level, especially in CYP2C19 NMs and IMs.

Pharmacogenetic implementation for CYP2C19 and pharmacokinetics of voriconazole in children with malignancy or inborn errors of immunity

BACKGROUND

Voriconazole pharmacokinetics (PK) are known to be affected by genetic polymorphisms of drug-metabolizing enzymes such as CYP2C19; however, such information is limited for the pediatric population. The primary aim of this study is to establish a voriconazole PK model incorporating CYP2C19 phenotypes in Japanese children with malignancy or inborn errors of immunity.

METHODS

CYP2C19 genotypes were assessed by whole-genome genotyping and defined as follows: *17/*17: ultrarapid metabolizer (URM), *1/*17: rapid metabolizer (RM), *1/*1:normal metabolizer (NM), *1/*2, *1/*3, *2/*17:intermediate metabolizer (IM), and *2/*2, *2/*3, *3/*3: poor metabolizer (PM). Population PK analysis was performed. The voriconazole serum concentration profile was described by a two-compartment model with first-order absorption, mixed linear and nonlinear (Michaelis-Menten) elimination.

RESULTS

Voriconazole concentration data were available from 60 patients with a median age of 5.3 years. The phenotypes predicted from CYP2C19 genotypes were RM in 1 (2 %), NM in 21 (35 %) patients, IM in 27 (45 %) patients, and PM in 11 (18 %) patients. Underlying diseases included 38 (63%) patients with hematological malignancy and 18 (30 %) patients with inborn errors of immunity. Among the CYP2C19 phenotypes, PM was predicted to show complete inhibition (the degree of Vmax inhibition [Vmax, inh] = 100 %; Vmax = 0). The estimated parameters of Vmax,inh were +0.8 higher in patients with gamma-glutamyl transpeptidase (γ-GTP) Grade 2 or higher and +2.7 higher when C-reactive protein (CRP) levels were 2.0 mg/dL or higher.

CONCLUSION

CYP2C19 genetic polymorphisms, γ-GTP, and CRP affect Vmax,inh of voriconazole in children with malignancy or inborn errors of immunity.

Combined impact of hypoalbuminemia and pharmacogenomic variants on voriconazole trough concentration: data from a real-life clinical setting in the Chinese population

Voriconazole (VRC) displays highly variable pharmacokinetics impacting treatment efficacy and safety. To provide evidence for optimizing VRC therapy regimens, the authors set out to determine the factors impacting VRC steady-state trough concentration (Cmin) in patients with various albumin (Alb) level. A total of 275 blood samples of 120 patients and their clinical characteristics and genotypes of CYP2C19, CYP3A4, CYP3A5, CYP2C9, FMO3, ABCB1, POR, NR1I2 and NR1I3 were included in this study. Results of multivariate linear regression analysis demonstrated that C-reactive protein (CRP) and total bilirubin (T-Bil) were predictors of the VRC Cmin adjusted for dose in patients with hypoalbuminemia (Alb < 35 g/L) (R2 = 0.16, P < 0.001). Additionally, in patients with normal albumin level (Alb ≥ 35 g/L), it resulted in a significant model containing factors of the poor metabolizer (PM) CYP2C19 genotype and CRP level (R2 = 0.26, P < 0.001). Therefore, CRP and T-Bil levels ought to receive greater consideration than genetic factors in patients with hypoalbuminemia.

Individualized treatment with voriconazole in the Chinese population: Inflammation level as a novel marker for dose optimization

AIMS

The aim of this study was to explore the influence and possible mechanisms of pharmacokinetics-related gene polymorphisms, especially CYP2C19 polymorphisms, and non-genetic factors combined with the inflammatory status on the voriconazole (VRC) metabolism of the Chinese population.

METHODS

Clinical studies were performed by collecting more than one VRC trough concentration and C-reactive protein (CRP) level. A total of 265 blood samples were collected from 120 patients.

RESULTS

Results of multiple regression analyses demonstrated that CYP2C19 genotypes and albumin (Alb) level remained predictors of Cmin ss/D in patients with no to mild inflammation (R2  = 0.12, P < .001). In addition, in patients with moderate to severe inflammation, it resulted in a significant model containing factors of CRP and total bilirubin (T-Bil) levels (R2  = 0.19, P < .001). In non-clinical studies, 32 rats were divided into control and inflammatory groups, and it was found that the mean residence time (MRT(0-t) ) of VRC in the inflammatory group was significantly longer than that in the control group (P < .001), which may be due to down-regulation of mRNA and protein expression of CYP2C19 (CYP2C6 in rats) through interleukin (IL)-6/signal transducer and activator of transcription (STAT) 3 pathway.

CONCLUSIONS

Therefore, the effect of CYP2C19 polymorphisms on VRC metabolism may be masked by inflammatory status, which should be of more concern than CYP2C19 polymorphisms in patients with moderate to severe inflammation. Additionally, the impact of Alb and T-Bil on VRC metabolism should not be disregarded.

Voriconazole Pharmacokinetics in Critically Ill Patients and Extracorporeal Membrane Oxygenation Support: A Retrospective Comparative Case-Control Study

Voriconazole, an antifungal agent, displays high intra- and inter-individual variability. The predictive pharmacokinetic (PK) index requires a minimum plasma concentration (C_min) in patient serum of between 1-5.5 mg/L. It is common to encounter fungal infections in patients undergoing extracorporeal membrane oxygenation (ECMO) support, and data regarding voriconazole PK changes during ECMO are scarce. Our study compared voriconazole PKs in patients with and without ECMO support in a retrospective cohort of critically-ill patients. Fifteen patients with 26 voriconazole C_min determinations in the non-ECMO group and nine patients with 27 voriconazole C_min determinations in the ECMO group were recruited. The ECMO group had lower C_min (0.38 ± 2.98 vs. 3.62 ± 3.88, p < 0.001) and higher infratherapeutic C_min values (16 vs. 1, p < 0.001) than the non-ECMO group. Multivariate analysis identified ECMO support (-0.668, CI₉₅ -0.978--0.358) and plasma albumin levels (-0.023, CI₉₅ -0.046--0.001) as risk factors for low C_min values. When comparing pre- and post-therapeutic drug optimisation samples from the ECMO group, the dose required to achieve therapeutic C_min was 6.44 mg/kg twice a day. Therapeutic drug optimisation is essential to improve target attainment.

Dosage optimization of voriconazole in children with haematological malignancies based on population pharmacokinetics

WHAT IS KNOWN AND OBJECTIVES

Voriconazole has a complex pharmacokinetic profile and exhibits different pharmacokinetic characteristics in adults and children. Nevertheless, few studies have been conducted on the population pharmacokinetics (PPK) of voriconazole in children with haematological malignancies. This study aims to build a PPK model and propose a suitable voriconazole treatment scheme for children with haematological malignancies.

METHODS

We retrospectively collected 146 samples from 67 children aged from 1.08 to 17.92 years. The PPK model was established using nonlinear mixed effects modelling (NONMEM). Dosage simulations were conducted on the basis of the final model's covariates.

RESULTS AND DISCUSSION

Data were fully characterized by a one-compartment model with first-order absorption and elimination. The weight (WT), CYP2C19 phenotype, and Albumin (ALB) were notable covariates for clearance (CL). The typical values of CL, the volume of distribution (V), and oral bioavailability (F) were 2.29 L/h, 76 L, and 0.902, respectively. The proposed doses for different CYP2C19 genotypes were presented in this ranking: EM (extensive metabolizer) > IM (intermediate metabolizer) > PM (poor metabolizer). Furthermore, higher dosages for light WT patients were recommended while lower ALB levels required lower doses. The probability of achieving the target (PTA) for the recommended doses ranged from 72.2% to 99%.

WHAT IS NEW AND CONCLUSION

We successfully built a voriconazole PPK model for children with hematologic malignancies. Dosing regimens were developed for different patients based on the final model, which could enhance the rational use of voriconazole in children with haematological malignancies.

Population pharmacokinetics of voriconazole and initial dosage optimization in patients with talaromycosis

The high variability and unpredictability of the plasma concentration of voriconazole (VRC) pose a major challenge for clinical administration. The aim of this study was to develop a population pharmacokinetics (PPK) model of VRC and identify the factors influencing VRC PPK in patients with talaromycosis. Medical records and VRC medication history of patients with talaromycosis who were treated with VRC as initial therapy were collected. A total of 233 blood samples from 69 patients were included in the study. A PPK model was developed using the nonlinear mixed-effects models (NONMEM). Monte Carlo simulation was applied to optimize the initial dosage regimens with a therapeutic range of 1.0–5.5 mg/L as the target plasma trough concentration. A one-compartment model with first-order absorption and elimination adequately described the data. The typical voriconazole clearance was 4.34 L/h, the volume of distribution was 97.4 L, the absorption rate constant was set at 1.1 h^-1, and the bioavailability was 95.1%. Clearance was found to be significantly associated with C-reactive protein (CRP). CYP2C19 polymorphisms had no effect on voriconazole pharmacokinetic parameters. ‏Monte Carlo simulation based on CRP levels showed that a loading dose of 250 mg/12 h and a maintenance dose of 100 mg/12 h are recommended for patients with CRP ≤ 96 mg/L, whereas a loading dose of 200 mg/12 h and a maintenance dose of 75 mg/12 h are recommended for patients with CRP > 96 mg/L. The average probability of target attainment of the optimal dosage regimen in CRP ≤ 96 mg/L and CRP > 96 mg/L groups were 61.3% and 13.6% higher than with empirical medication, and the proportion of C_min > 5.5 mg/L decreased by 28.9%. In conclusion, the VRC PPK model for talaromycosis patients shows good robustness and predictive performance, which can provide a reference for the clinical individualization of VRC. Adjusting initial dosage regimens based on CRP may promote the rational use of VRC.

Systematic Evaluation of Voriconazole Pharmacokinetic Models without Pharmacogenetic Information for Bayesian Forecasting in Critically Ill Patients

Voriconazole (VRC) is used as first line antifungal agent against invasive aspergillosis. Model-based approaches might optimize VRC therapy. This study aimed to investigate the predictive performance of pharmacokinetic models of VRC without pharmacogenetic information for their suitability for model-informed precision dosing. Seven PopPK models were selected from a systematic literature review. A total of 66 measured VRC plasma concentrations from 33 critically ill patients was employed for analysis. The second measurement per patient was used to calculate relative Bias (rBias), mean error (ME), relative root mean squared error (rRMSE) and mean absolute error (MAE) (i) only based on patient characteristics and dosing history (a priori) and (ii) integrating the first measured concentration to predict the second concentration (Bayesian forecasting). The a priori rBias/ME and rRMSE/MAE varied substantially between the models, ranging from −15.4 to 124.6%/−0.70 to 8.01 mg/L and from 89.3 to 139.1%/1.45 to 8.11 mg/L, respectively. The integration of the first TDM sample improved the predictive performance of all models, with the model by Chen (85.0%) showing the best predictive performance (rRMSE: 85.0%; rBias: 4.0%). Our study revealed a certain degree of imprecision for all investigated models, so their sole use is not recommendable. Models with a higher performance would be necessary for clinical use.

Effects of cimetidine on ciclosporin population pharmacokinetics and initial dose optimization in aplastic anemia patients

The present study aimed to explore the effects of cimetidine on ciclosporin population pharmacokinetics and initial dose optimization in aplastic anemia patients. Aplastic anemia patients were used to establish a population pharmacokinetic model by the nonlinear mixed effect (NONMEM), and concentrations of ciclosporin were simulated by Monte Carlo method. With the same weight, the ciclosporin clearance rates were 0.387:1 in patients with or without cimetidine, respectively. In the measured ciclosporin concentrations, compared to aplastic anemia patients without cimetidine, ciclosporin concentrations were higher in patients with cimetidine (P < 0.01). Further research found that at the same body weight and same dose, ciclosporin concentrations in aplastic anemia patients with cimetidine were indeed higher than those in patients without cimetidine (P < 0.01). The initial recommended ciclosporin dose for patients without cimetidine were 7mg/kg splited into two doses for weight of 40-60kg, and 6mg/kg splited into two doses for weight of 60-100kg. The patients with cimetidine were recommended to take 3mg/kg ciclosporin splited into two doses for weight of 40-100kg. It was the first time to explore the effects of cimetidine on ciclosporin population pharmacokinetics and initial dose optimization in aplastic anemia patients. Patients coadministration of cimetidine, may need low ciclosporin dose.

Predictive Value of C-Reactive Protein and Albumin for Temporal Within-Individual Pharmacokinetic Variability of Voriconazole in Pediatric Hematopoietic Cell Transplant Patients

Voriconazole is a widely used antifungal agent in immunocompromised patients, but its utility is limited by its variable exposure and narrow therapeutic index. Population pharmacokinetic (PK) models have been used to characterize voriconazole PK and derive individualized dosing regimens. However, determinants of temporal within-patient variability of voriconazole PK were not well-established. We aimed to characterize temporal variability of voriconazole PK within individuals and identify predictive clinical factors. This study was conducted as a part of a single-institution, phase I study of intravenous voriconazole in children undergoing HCT (NCT02227797). We analyzed voriconazole PK study data collected at week 1 and again at week 2 after the start of voriconazole therapy in 59 pediatric HCT patients (age <21 years). Population PK analysis using nonlinear mixed effect modeling was performed to analyze temporal within-individual variability of voriconazole PK by incorporating a between-occasion variability term in the model. A two-compartment linear elimination model incorporating body weight and CYP2C19 phenotype described the data. Ratio of individual voriconazole clearance between weeks 1 to 2 ranged from 0.11 to 3.3 (-9.1 to +3.3-fold change). Incorporation of covariate effects by serum C-reactive protein (CRP) and albumin levels decreased between-occasion variability of clearance (coefficient of variation: from 59.5% to 41.2%) and improved the model fit (p<0.05). As significant covariates on voriconazole PK, CRP and albumin concentrations may potentially serve as useful biomarkers as part of therapeutic drug monitoring. This article is protected by copyright. All rights reserved.