Model-based Voriconazole Dose Optimization in Chinese Adult Patients With Hematologic Malignancies

Interaction of age and CYP2C19 genotypes on voriconazole steady-state trough concentration in Chinese patients

OBJECTIVES

Both age and CYP2C19 genotypes affect voriconazole plasma concentration; the interaction of age and CYP2C19 genotypes on voriconazole plasma concentration remains unknown. This study aims to investigate the combined effects of age and CYP2C19 genotypes on voriconazole plasma concentration in Chinese patients.

METHODS

A total of 480 patients who received voriconazole treatment were recruited. CYP2C19*2 (rs4244285) and CYP2C19*3 (rs4986893) polymorphisms were genotyped. Patients were divided into the young and the elderly groups by age of 60 years old. Influence of CYP2C19 genotype on steady-state trough concentration (C ss-min ) in overall patients and in age subgroups was analyzed.

RESULTS

Voriconazole C ss-min correlated positively with age, and mean voriconazole C ss-min was significantly higher in the elderly group ( P  < 0.001). CYP2C19 poor metabolizers showed significantly increased mean voriconazole C ss-min in the young but not the elderly group. The percentage of patients with subtherapeutic voriconazole C ss-min (<1.0 mg/l) was higher in the young group and that of supratherapeutic voriconazole C ss-min (>5.5 mg/l) was higher in the elderly patients. When the average C ss-min in the CYP2C19 normal metabolizer genotype was regarded as a reference, CYP2C19 genotypes showed greater impact on voriconazole C ss-min in the young group, while the influence of age on voriconazole C ss-min exceeded CYP2C19 genotypes in the elderly.

CONCLUSION

CYP2C19 genotypes affects voriconazole exposure is age dependent. Influence of CYP2C19 poor metabolizer genotype on increased voriconazoleexposure is prominent in the young, while age is a more important determinant factor for increased voriconazole exposure in the elderly patients.

Population Pharmacokinetics of Voriconazole and Dose Optimization in Elderly Chinese Patients

Voriconazole is commonly recommended as a first-line therapy for invasive aspergillosis infections. Elderly patients are susceptible to infectious diseases owing to their decreased physical function and immune system. Our study aims to establish a population pharmacokinetics model for elderly patients receiving intravenous voriconazole, and to optimize dosing protocols through a simulated approach. An accurate fit to the concentration-time profile of voriconazole was achieved by employing a 1-compartment model featuring first-order elimination. The typical clearance rate of voriconazole was found to be 3.22 L/h, with a typical volume of distribution of 194 L. The covariate analysis revealed that albumin (ALB), gamma-glutamyl transpeptidase, and direct bilirubin had significant impacts on voriconazole clearance. Additionally, body weight was found to be associated with the volume of distribution. Individualized dosing regimens were recommended for different ALB levels based on population pharmacokinetics model prediction. The proposed dosing regimens could provide a rationale for dosage individualization, improve the clinical outcomes, and minimize drug-related toxicities.

Determination of vancomycin exposure target and individualized dosing recommendations for critically ill patients undergoing continuous renal replacement therapy

STUDY OBJECTIVE

Few studies have been conducted to quantify the exposure target of vancomycin in intensive care unit (ICU) patients undergoing continuous renal replacement therapy (CRRT) and provide optimized dosage regimens. We aimed to determine vancomycin exposure target and dosing recommendations using data from an open database in critically ill patients undergoing CRRT.

DESIGN

A retrospective observational cohort study.

DATA SOURCE

A large public database.

PATIENTS

The adult patients who received intravenous vancomycin and CRRT treatment in the database between 2017 and 2019 were reviewed to determine eligibility. A total of 180 patients with 1186 observations were included in the population pharmacokinetic (PPK) model development. The clinical efficacy of vancomycin was analyzed in 159 eligible patients.

METHODS

A PPK model was developed to estimate individual pharmacokinetic (PK) parameters. The area under the concentration-time curve (AUC) was estimated by a Bayesian approach based on individual vancomycin concentrations. Multivariate logistic regression analyses were performed to identify the factors of clinical outcomes. Threshold of vancomycin exposure in predicting efficacy was identified via receiver operating characteristic (ROC) curve. Dosing recommendations were designed using Monte Carlo Simulations (MCS) based on the optimized exposure target.

MEASUREMENTS AND MAIN RESULTS

On covariate analysis, CRRT intensity significantly affected vancomycin PK. The AUC above 427 mg*h/L was the only significant predictor of clinical efficacy (adjusted odds ratio (aOR): 1.008, 95% confidence interval (CI): 1.004-1.011, p = 0.000). MCS indicated that vancomycin dosage regimens of 5 mg/kg q12h or 7.5 mg/kg q12h were recommended for patients with CRRT intensities of 20-25 mL/kg/h or 25.1-45 mL/kg/h, respectively.

CONCLUSIONS

An AUC threshold of 427 mg*h/L (assuming the minimal inhibitory concentration (MIC) = 1 mg/L) was a recommended efficacy exposure target of vancomycin for critically ill patients undergoing CRRT. Vancomycin 5-7.5 mg/kg q12h is recommended as the initial dosage regimens for ICU patients undergoing CRRT.

Voriconazole exposure is influenced by inflammation: A population pharmacokinetic model

BACKGROUND

Voriconazole is an antifungal drug used for the treatment of invasive fungal infections. Due to highly variable drug exposure, therapeutic drug monitoring (TDM) has been recommended. TDM may be helpful to predict exposure accurately, but covariates, such as severe inflammation, that influence the metabolism of voriconazole have not been included in the population pharmacokinetic (popPK) models suitable for routine TDM.

OBJECTIVES

To investigate whether the effect of inflammation, reflected by C-reactive protein (CRP), could improve a popPK model that can be applied in clinical care.

PATIENTS AND METHODS

Data from two previous studies were included in the popPK modelling. PopPK modelling was performed using Edsim++. Different popPK models were compared using Akaike Information Criterion and goodness-of-fit plots.

RESULTS

In total, 1060 voriconazole serum concentrations from 54 patients were included in this study. The final model was a one-compartment model with non-linear elimination. Only CRP was a significant covariate, and was included in the final model and found to affect the maximum rate of enzyme activity (V_max). For the final popPK model, the mean volume of distribution was 145 L [coefficient of variation percentage (CV%)=61%], mean Michaelis-Menten constant was 5.7 mg/L (CV%=119%), mean V_max was 86.4 mg/h (CV%=99%) and mean bioavailability was 0.83 (CV%=143%). Internal validation using bootstrapping resulted in median values close to the population parameter estimates.

CONCLUSIONS

This one-compartment model with non-linear elimination and CRP as a covariate described the pharmacokinetics of voriconazole adequately.

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.

External evaluation of population pharmacokinetic models for voriconazole in Chinese adult patients with hematological malignancy

OBJECTIVES

Patients with hematological malignancies are prone to invasive fungal disease due to long-term chemotherapy or radiotherapy. Voriconazole is a second-generation triazole broad-spectrum antibiotic used to prevent or treat invasive fungal infections. Many population pharmacokinetic (pop PK) models have been published for voriconazole, and various diagnostic methods are available to validate the performance of these pop PK models. However, most of the published models have not been strictly evaluated externally. The purpose of this study is to evaluate these models externally and assess their predictive capabilities.

METHODS

The external dataset consists of adults receiving voriconazole treatment at Fujian Medical University Union Hospital. We re-established the published models based on their final estimated values in the literature and used our external dataset for initial screening. Each model was evaluated based on the following outcomes: prediction-based diagnostics, prediction- and variability-corrected visual predictive check (pvcVPC), normalized prediction distribution errors (NPDE), and Bayesian simulation results with one to two prior observations.

RESULTS

A total of 237 samples from 166 patients were collected as an external dataset. After screening, six candidate models suitable for the external dataset were finally obtained for comparison. Among the models, none demonstrated excellent predictive performance. Bayesian simulation shows that all models' prediction precision and accuracy were significantly improved when one or two prior concentrations were given.

CONCLUSIONS

The published pop PK models of voriconazole have significant differences in prediction performance, and none of the models could perfectly predict the concentrations of voriconazole for our data. Therefore, extensive evaluation should precede the adoption of any model in clinical practice.

Co-Administration with Voriconazole Doubles the Exposure of Ruxolitinib in Patients with Hematological Malignancies

Background

Ruxolitinib is newly approved for glucocorticoid-refractory acute graft-versus-host disease (GVHD) in patients undergoing allo-geneic hematopoietic stem-cell transplantation (allo-HSCT), and voriconazole is commonly used in allo-HSCT recipients for the prophylaxis or treatment of invasive fungal infections (IFIs). Drug–drug interaction (DDI) may occur between them because their metabolic pathways overlap and can be inhibited by voriconazole, including cytochrome P450 (CYP) isozymes 3A4 and 2C9.

Objective

In the present study, we aimed to investigate the DDI between ruxolitinib and voriconazole in patients with hematological malignancies.

Methods

A total of 12 patients with hematologic malignancies were enrolled in this single-arm, single-center, Phase I/II, fixed sequence self-control study. All subjects received 5 mg ruxolitinib alone, followed by the co-administration of ruxolitinib and voriconazole. The plasma concentrations of the two drugs were determined by two well-validated high-performance liquid chromatography-tandem mass spectrometry methods. Phoenix WinNonlin software was used to compare the differences in maximum plasma concentration (C_max), time to C_max (T_max), terminal elimination half-life (T_1/2), and apparent plasma clearance (CL/F), as well as area under the curve from time zero to last (AUC_last) and AUC from time zero to infinity (AUC_inf) between the two periods.

Results

After pre-treatment with voriconazole, no significant change existed in T_max, while C_max, T_1/2, AUC_last, and AUC_inf of ruxolitinib were significantly increased by 50.4%, 81.3%, 110.1%, and 118.3%, respectively, and CL/F was significantly decreased to 43.6% compared with patients receiving ruxolitinib alone.

Conclusion

Our findings confirmed a moderate inhibitory DDI between ruxolitinib and voriconazole as voriconazole decreased the elimination and increased the exposure of ruxolitinib in patients with hematologic malignancies. We recommended a dose reduction regimen when voriconazole and ruxolitinib were coadministered. Drug monitoring might help determine the ruxolitinib treatment concentration for aGVHD patients, improve efficacy, and reduce toxicity.

Antifungal Drugs TDM: Trends and Update

PURPOSE

The increasing burden of invasive fungal infections results in growing challenges to antifungal (AF) therapeutic drug monitoring (TDM). This review aims to provide an overview of recent advances in AF TDM.

METHODS

We conducted a PubMed search for articles during 2016-2020 using "TDM" or "pharmacokinetics" or "drug-drug-interaction" with "antifungal," consolidated for each AF. Selection was limited to English language articles with human data on drug exposure.

RESULTS

More than 1000 articles matched the search terms. We selected 566 publications. The latest findings tend to confirm previous observations in real-life clinical settings. The pharmacokinetic variability related to special populations is not specific but must be considered. AF benefit-to-risk ratio, drug-drug interaction (DDI) profiles, and minimal inhibitory concentrations for pathogens must be known to manage at-risk situations and patients. Itraconazole has replaced ketoconazole in healthy volunteers DDI studies. Physiologically based pharmacokinetic modeling is widely used to assess metabolic azole DDI. AF prophylactic use was studied more for Aspergillus spp. and Mucorales in oncohematology and solid organ transplantation than for Candida (already studied). Emergence of central nervous system infection and severe infections in immunocompetent individuals both merit special attention. TDM is more challenging for azoles than amphotericin B and echinocandins. Fewer TDM requirements exist for fluconazole and isavuconazole (ISZ); however, ISZ is frequently used in clinical situations in which TDM is recommended. Voriconazole remains the most challenging of the AF, with toxicity limiting high-dose treatments. Moreover, alternative treatments (posaconazole tablets, ISZ) are now available.

CONCLUSIONS

TDM seems to be crucial for curative and/or long-term maintenance treatment in highly variable patients. TDM poses fewer cost issues than the drugs themselves or subsequent treatment issues. The integration of clinical pharmacology into multidisciplinary management is now increasingly seen as a part of patient care.

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.

A Large Sample Retrospective Study on the Distinction of Voriconazole Concentration in Asian Patients from Different Clinical Departments

Voriconazole (VRZ) is widely used to prevent and treat invasive fungal infections; however, there are a few studies examining the variability and influencing the factors of VRZ plasma concentrations across different clinical departments. This study aimed to evaluate distinction of VRZ concentrations in different clinical departments and provide a reference for its reasonable use. From 1 May 2014 to 31 December 2020, VRZ standard rates and factors affecting the VRZ trough concentration were analyzed, and a multiple linear regression model was constructed. The standard rates of VRZ in most departments were above 60%. A total of 676 patients with 1212 VRZ trough concentrations using a dosing regimen of 200 mg q12h from seven departments were enrolled in the correlation analysis. The concentration distribution varied significantly among different departments (p < 0.001). Fifteen factors, including department, CYP2C19 phenotype, and gender, correlated with VRZ concentration. A multiple linear regression model was established as follows: VRZ trough concentration = 5.195 + 0.049 × age + 0.007 × alanine aminotransferase + 0.010 × total bilirubin − 0.100 × albumin − 0.004 × gamma-glutamyl transferase. According to these indexes, we can predict possible changes in VRZ trough concentration and adjust its dosage precisely and individually.

Dose Optimization of Vancomycin for Critically Ill Patients Undergoing CVVH: A Prospective Population PK/PD Analysis

The optimal dose of vancomycin in critically ill patients receiving continuous venovenous hemofiltration (CVVH) remains unclear. The objective of this study was to identify factors that significantly affect pharmacokinetic profiles and to further investigate the optimal dosage regimens for critically ill patients undergoing CVVH based on population pharmacokinetics and pharmacodynamic analysis. A prospective population pharmacokinetic analysis was performed at the surgical intensive care unit in a level A tertiary hospital. We included 11 critically ill patients undergoing CVVH and receiving intravenous vancomycin. Serial blood samples were collected from each patient, with a total of 131 vancomycin concentrations analyzed. Nonlinear mixed effects models were developed using NONMEM software. Monte Carlo Simulation was used to optimize vancomycin dosage regimens. A two-compartment model with first-order elimination was sufficient to characterize vancomycin pharmacokinetics for CVVH patients. The population typical vancomycin clearance (CL) was 1.15 L/h and the central volume of distribution was 16.9 L. CL was significantly correlated with ultrafiltration rate (UFR) and albumin level. For patients with normal albumin and UFR between 20 and 35 mL/kg/h, the recommended dosage regimen was 10 mg/kg qd. When UFR was between 35 and 40 mL/kg/h, the recommended dosage regimen was 5 mg/kg q8h. For patients with hypoalbuminemia and UFR between 20 and 25 mL/kg/h, the recommended dosage regimen was 5 mg/kg q8h. When UFR was between 25 and 40 mL/kg/h, the recommended dosage regimen was 10 mg/kg q12h. We recommend clinicians choosing the optimal initial vancomycin dosage regimens for critically ill patients undergoing CVVH based on these two covariates.

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.

Predicting the Outcome of Voriconazole Individualized Medication Using Integrated Pharmacokinetic/Pharmacodynamic Model

Therapeutic drug monitoring is considered to be an effective tool for the individualized use of voriconazole. However, drug concentration measurement alone doesn’t take into account the susceptibility of the infecting microorganisms to the drug. Linking pharmacodynamic data with the pharmacokinetic profile of individuals is expected to be an effective method to predict the probability of a certain therapeutic outcome. The objective of this study was to individualize voriconazole regimens by integrating individual pharmacokinetic parameters and pathogen susceptibility data through Monte Carlo simulations The individual pharmacokinetic parameters of 35 hospitalized patients who received voriconazole were calculated based on a validated population pharmacokinetic model. The area under the concentration-time curve for free drug/minimal inhibitory concentration (fAUC_ss/MIC) > 25 was selected as the pharmacokinetic/pharmacodynamic (PK/PD) parameter predicting the efficacy of voriconazole. The cumulative fraction of response (CFR) of the target value was assessed. To verify this conclusion, a logistic regression analysis was used to explore the relationship between actual clinical efficiency and the CFR value. For the 35 patients, the area under the free drug concentration-time curve (fAUC_ss) was calculated to be 34.90 ± 21.67 mgh/L. According to the dualistic logistic regression analysis, the minimal inhibitory concentration (MIC) value of different kinds of fungi had a great influence on the effectiveness of clinical treatment. It also showed that the actual clinical efficacy and the CFR value of fAUC_ss/MIC had a high degree of consistency. The results suggest that it is feasible to individualize voriconazole dosing and predict clinical outcomes through the integration of data on pharmacokinetics and antifungal susceptibility.

Effects of Letermovir and/or Methylprednisolone Coadministration on Voriconazole Pharmacokinetics in Hematopoietic Stem Cell Transplantation: A Population Pharmacokinetic Study

Objective

The aim of this study was to identify factors affecting blood concentrations of voriconazole following letermovir coadministration using population pharmacokinetic (PPK) analysis in allogeneic hematopoietic stem cell transplant (allo-HSCT) recipients.

Methods

The following data were retrospectively collected: voriconazole trough levels, patient characteristics, concomitant drugs, and laboratory information. PPK analysis was performed with NONMEM^® version 7.4.3, using the first-order conditional estimation method with interaction. We collected data on plasma voriconazole steady-state trough concentrations at 216 timepoints for 47 patients. A nonlinear pharmacokinetic model with the Michaelis–Menten equation was applied to describe the relationship between steady-state trough concentration and daily maintenance dose of voriconazole. After stepwise covariate modeling, the final model was evaluated using a goodness-of-fit plot, case deletion diagnostics, and bootstrap methods.

Results

The maximum elimination rate (V_max) of voriconazole in patients coadministered letermovir and methylprednisolone was 1.72 and 1.30 times larger than that in patients not coadministered these drugs, respectively, resulting in decreased voriconazole trough concentrations. The developed PPK model adequately described the voriconazole trough concentration profiles in allo-HSCT recipients. Simulations clearly showed that increased daily doses of voriconazole were required to achieve an optimal trough voriconazole concentration (1–5 mg/L) when patients received voriconazole with letermovir and/or methylprednisolone.

Conclusions

The development of individualized dose adjustment is critical to achieve optimal voriconazole concentration, especially among allo-HSCT recipients receiving concomitant letermovir and/or methylprednisolone.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40268-021-00365-0.

Population pharmacokinetic model-guided optimization of intravenous voriconazole dosing regimens in critically ill patients with liver dysfunction

STUDY OBJECTIVES

This study aimed to establish a population pharmacokinetic (PPK) model of intravenous voriconazole (VRC) in critically ill patients with liver dysfunction and to explore the optimal dosing strategies in specific clinical scenarios for invasive fungal infections (IFIs) caused by common Aspergillus and Candida species.

DESIGN

Prospective pharmacokinetics study.

SETTING

The intensive care unit in a tertiary-care medical center.

PATIENTS

A total of 297 plasma VRC concentrations from 26 critically ill patients with liver dysfunction were included in the PPK analysis.

METHODS

Model-based simulations with therapeutic range of 2-6 mg/L as the plasma trough concentration (C_min ) target and the free area under the concentration-time curve from 0 to 24 h (ƒAUC₂₄ ) divided by the minimum inhibitory concentration (MIC) (ie, ƒAUC₂₄ /MIC) ≥25 as the effective target were performed to optimize VRC dosing regimens for Child-Pugh class A and B (CP-A/B) and Child-Pugh class C (CP-C) patients.

RESULTS

A two-compartment model with first-order elimination adequately described the data. Significant covariates in the final model were body weight on both central and peripheral distribution volume and Child-Pugh class on clearance. Intravenous VRC loading dose of 5 mg/kg every 12 h (q12h) for the first day was adequate for CP-A/B and CP-C patients to attain the C_min target at 24 h. The maintenance dose regimens of 100 mg q12h or 200 mg q24h for CP-A/B patients and 50 mg q12h or 100 mg q24h for CP-C patients could obtain the probability of effective target attainment of >90% at an MIC ≤0.5 mg/L and achieve the cumulative fraction of response of >90% against C. albicans, C. parapsilosis, C. glabrata, C. krusei, A. fumigatus, and A. flavus. Additionally, the daily VRC doses could be increased by 50 mg for CP-A/B and CP-C patients at an MIC of 1 mg/L, with plasma C_min monitored closely to avoid serious adverse events. It is recommended that an appropriate alternative antifungal agent or a combination therapy could be adopted when an MIC ≥2 mg/L is reported, or when the infection is caused by C. tropicalis but the MIC value is not available.

CONCLUSIONS

For critically ill patients with liver dysfunction, the loading dose of intravenous VRC should be reduced to 5 mg/kg q12h. Additionally, based on the types of fungal pathogens and their susceptibility to VRC, the adjusted maintenance dose regimens with lower doses or longer dosing intervals should be considered for CP-A/B and CP-C patients.

Model-Oriented Dose Optimization of Voriconazole in Critically Ill Children

This study aimed to employ a population pharmacokinetic (PK) model to optimize the dosing regimen of voriconazole (VRC) in children with a critical illness. A total of 99 children aged from 0.44 to 13.58 years were included in this study. The stability and predictive performance of the final model were evaluated by statistical and graphical methods. The optimal dosing regimen was proposed for children with different body weights, CYP2C19 phenotypes, and coadministrations with omeprazole. The PK of VRC was described by a two-compartment model with nonlinear Michaelis-Menten elimination. Body weight, CYP2C19 phenotype, and omeprazole were significant covariates on the maximum velocity of elimination (V_max), which had an estimated typical value of 18.13 mg · h^-1. Bayesian estimation suggested that the dose-normalized concentration and total exposure (peak concentration [C_max]/D, trough concentration [C_min]/D, and area under the concentration-time curve over 24 h [AUC₂₄]/D) were significantly different between extensive metabolizer (EM) patients and poor metabolizer (PM) patients. To achieve the target concentration early, two loading doses of 9 mg · kg^-1 of body weight every 12 h (q12h) were reliable for most children, whereas three loading doses of 6 to 7.5 mg · kg^-1 q8h were warranted for young children weighing ≤18 kg (except for PM patients). The maintenance doses decreased about 30 to 40% in PM patients compared to that in EM patients. For children aged <2 years, in EM patients, the maintenance dose could be as high as 9 mg · kg^-1. The maintenance dose of VRC was supposed to decrease slightly when coadministered with omeprazole. A population PK model of intravenous VRC for critically ill children has been successfully developed. It is necessary to adjust dosing regimens according to the CYP2C19 genotype. Optimal dosing regimens have been recommended based on the final model.

Pharmacokinetic and Adsorptive Analyses of Administration of Oral Voriconazole Suspension via Enteral Feeding Tube in Intensive Care Unit Patients

For intensive care unit (ICU) patients, injectable voriconazole (VRCZ) is difficult to use because the patients often develop acute kidney injury. Since many ICU patients have consciousness disturbance, oral ingestion of tablet formulation is also difficult, and administration of a suspension via enteral feeding tube is required when using VRCZ. In this study, we investigated the in vitro adsorption property of oral VRCZ to feeding tube and performed pharmacokinetic analysis of VRCZ prepared by powdering and simple suspension for ICU patients. VRCZ was tube-administered to five ICU patients at a loading dose of 300 mg and plasma VRCZ concentrations before and at 1, 2, 4, 8, 12 h after the first dose were measured using HPLC. Pharmacokinetic parameters were calculated by non-compartmental model analysis. The recovery rate of VRCZ after infusion of the suspension through feeding tube was 89.8 ± 8.3%, but the cumulative rates after the first and second re-infusion were 102.7 ± 20.7 and 99.3 ± 10.3%, respectively, suggesting almost no residual drug in the tube after re-infusion. Metabolic phenotype was extensive metabolizer (EM) in two patients and intermediate metabolizer (IM) in three patients. The values of total clearance (CL_tot/F) calculated by moment analysis were 0.51 and 0.55 L/h/kg in two EM patients, and 0.09, 0.29 and 0.31 L/h/kg in three IM patients. The CL_tot/F was apparently lower in IM patients compared to EM. In conclusion, powdered and suspended VRCZ administered via enteral feeding tube showed pharmacokinetics depending on CYP2C19 gene polymorphism, similar to that observed in usual oral administration.

Contribution of Population Pharmacokinetics of Glycopeptides and Antifungals to Dosage Adaptation in Paediatric Onco-hematological Malignancies: A Review

The response to medications in children differs not only in comparison to adults but also between children of the different age groups and according to the disease. This is true for anti-infectives that are widely prescribed in children with malignancy. In the absence of pharmacokinetic/pharmacodynamic paediatric studies, dosage is frequently based on protocols adapted to adults. After a short presentation of the drugs, we reviewed the population pharmacokinetic studies available for glycopeptides (vancomycin and teicoplanin, n = 5) and antifungals (voriconazole, posaconazole, and amphotericin B, n = 9) currently administered in children with onco-hematological malignancies. For each of them, we reported the main study characteristics including identified covariates affecting pharmacokinetics and proposed paediatric dosage recommendations. This review highlighted the very limited amount of data available, the lack of consensus regarding PK/PD targets used for dosing optimization and regarding dosage recommendations when available. Additional PK studies are urgently needed in this specific patient population. In addition to pharmacokinetics, efficacy may be altered in immunocompromised patients and prospective clinical evaluation of new dosage regimen should be provided as they are missing in most cases.

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

This study aimed to identify factors that significantly influence the pharmacokinetics of voriconazole in Thai adults with hematologic diseases, and to determine optimal voriconazole dosing regimens. Blood samples were collected at steady state in 65 patients (237 concentrations) who were taking voriconazole to prevent or treat invasive aspergillosis. The data were analyzed using a nonlinear mixed-effects modeling approach. Monte Carlo simulation was applied to optimize dosage regimens. Data were fitted with the one-compartment model with first-order absorption and elimination. The apparent oral clearance (CL/F) was 3.43 L/h, the apparent volume of distribution (V/F) was 47.6 L, and the absorption rate constant (Ka) was fixed at 1.1 h⁻¹. Albumin and omeprazole ≥ 40 mg/day were found to significantly influence CL/F. The simulation produced the following recommended maintenance doses of voriconazole: 50, 100, and 200 mg every 12 h for albumin levels of 1.5–3, 3.01–4, and 4.01–4.5 g/dL, respectively, in patients who receive omeprazole ≤ 20 mg/day. Patients who receive omeprazole ≥ 40 mg/day and who have serum albumin level 1.5–3 and 3.01–4.5 g/dL should receive voriconazole 50 and 100 mg, every 12 h, respectively. Albumin level and omeprazole dosage should be carefully considered when determining the appropriate dosage of voriconazole in Thai patients.