A Personalized CYP2C19 Phenotype-Guided Dosing Regimen of Voriconazole Using a Population Pharmacokinetic Analysis

A physiologically based pharmacokinetic model of voriconazole in human CNS-Integrating time-dependent inhibition of CYP3A4, genetic polymorphisms of CYP2C19 and possible transporter mechanisms

OBJECTIVES

Voriconazole is a classical antifungal drug that is often used to treat CNS fungal infections due to its permeability through the BBB. However, its clinical use remains challenging because of its narrow therapeutic window and wide inter-individual variability. In this study, we proposed an optimised and validated PBPK model by integrating in vitro, in vivo and clinical data to simulate the distribution and PK process of voriconazole in the CNS, providing guidance for clinical individualised treatment.

METHODS

The model structure was optimised and tissue-to-plasma partition coefficients were obtained through animal experiments. Using the allometric relationships, the distribution of voriconazole in the human CNS was predicted. The model integrated factors affecting inter-individual variation and drug interactions of voriconazole-polymorphisms in the CYP2C19 gene and auto-inhibition and then was validated using real clinical data.

RESULTS

The overall AFE value showing model predicted differences was 1.1420 in the healthy population; and in the first prediction of plasma and CSF in actual clinical patients, 89.5% of the values were within the 2-fold error interval, indicating good predictive performance of the model. The bioavailability of voriconazole varied at different doses (39%-86%), and the optimised model conformed to this pattern (46%-83%).

CONCLUSIONS

Combined with the relevant pharmacodynamic indexes, the PBPK model provides a feasible way for precise medication in patients with CNS infection and improve the treatment effect and prognosis.

Renal Replacement Therapy as a New Indicator of Voriconazole Clearance in a Population Pharmacokinetic Analysis of Critically Ill Patients

AIMS

The pharmacokinetic (PK) profiles of voriconazole in intensive care unit (ICU) patients differ from that in other patients. We aimed to develop a population pharmacokinetic (PopPK) model to evaluate the effects of using extracorporeal membrane oxygenation (ECMO) and continuous renal replacement therapy (CRRT) and those of various biological covariates on the voriconazole PK profile.

METHODS

Modeling analyses of the PK parameters were conducted using the nonlinear mixed-effects modeling method (NONMEM) with a two-compartment model. Monte Carlo simulations (MCSs) were performed to observe the probability of target attainment (PTA) when receiving CRRT or not under different dosage regimens, different stratifications of quick C-reactive protein (qCRP), and different minimum inhibitory concentration (MIC) ranges.

RESULTS

A total of 408 critically ill patients with 746 voriconazole concentration-time data points were included in this study. A two-compartment population PK model with qCRP, CRRT, creatinine clearance rate (CLCR), platelets (PLT), and prothrombin time (PT) as fixed effects was developed using the NONMEM.

CONCLUSIONS

We found that qCRP, CRRT, CLCR, PLT, and PT affected the voriconazole clearance. The most commonly used clinical regimen of 200 mg q12h was sufficient for the most common sensitive pathogens (MIC ≤ 0.25 mg/L), regardless of whether CRRT was performed and the level of qCRP. When the MIC was 0.5 mg/L, 200 mg q12h was insufficient only when the qCRP was <40 mg/L and CRRT was performed. When the MIC was ≥2 mg/L, a dose of 300 mg q12h could not achieve ≥ 90% PTA, necessitating the evaluation of a higher dose.

Enhancing voriconazole therapy in liver dysfunction: exploring administration schemes and predictive factors for trough concentration and efficacy

Introduction: The application of voriconazole in patients with liver dysfunction lacks pharmacokinetic data. In previous study, we proposed to develop voriconazole dosing regimens for these patients according to their total bilirubin, but the regimens are based on Monte Carlo simulation and has not been further verified in clinical practice. Besides, there are few reported factors that significantly affect the efficacy of voriconazole. Methods: We collected the information of patients with liver dysfunction hospitalized in our hospital from January 2018 to May 2022 retrospectively, including their baseline information and laboratory data. We mainly evaluated the efficacy of voriconazole and the target attainment of voriconazole trough concentration. Results: A total of 157 patients with liver dysfunction were included, from whom 145 initial and 139 final voriconazole trough concentrations were measured. 60.5% (95/157) of patients experienced the adjustment of dose or frequency. The initial voriconazole trough concentrations were significantly higher than the final (mean, 4.47 versus 3.90 μg/mL, p = 0.0297). Furthermore, daily dose, direct bilirubin, lymphocyte counts and percentage, platelet, blood urea nitrogen and creatinine seven covariates were identified as the factors significantly affect the voriconazole trough concentration. Binary logistic regression analysis revealed that the lymphocyte percentage significantly affected the efficacy of voriconazole (OR 1.138, 95% CI 1.016-1.273), which was further validated by the receiver operating characteristic curve. Conclusion: The significant variation in voriconazole trough concentrations observed in patients with liver dysfunction necessitates caution when prescribing this drug. Clinicians should consider the identified factors, particularly lymphocyte percentage, when dosing voriconazole in this population.

Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data

BACKGROUND AND OBJECTIVES

Model-informed precision dosing (MIPD) frequently uses nonlinear mixed-effects (NLME) models to predict and optimize therapy outcomes based on patient characteristics and therapeutic drug monitoring data. MIPD is indicated for compounds with narrow therapeutic range and complex pharmacokinetics (PK), such as voriconazole, a broad-spectrum antifungal drug for prevention and treatment of invasive fungal infections. To provide guidance and recommendations for evidence-based application of MIPD for voriconazole, this work aimed to (i) externally evaluate and compare the predictive performance of a published so-called 'hybrid' model for MIPD (an aggregate model comprising features and prior information from six previously published NLME models) versus two 'standard' NLME models of voriconazole, and (ii) investigate strategies and illustrate the clinical impact of Bayesian forecasting for voriconazole.

METHODS

A workflow for external evaluation and application of MIPD for voriconazole was implemented. Published voriconazole NLME models were externally evaluated using a comprehensive in-house clinical database comprising nine voriconazole studies and prediction-/simulation-based diagnostics. The NLME models were applied using different Bayesian forecasting strategies to assess the influence of prior observations on model predictivity.

RESULTS

The overall best predictive performance was obtained using the aggregate model. However, all NLME models showed only modest predictive performance, suggesting that (i) important PK processes were not sufficiently implemented in the structural submodels, (ii) sources of interindividual variability were not entirely captured, and (iii) interoccasion variability was not adequately accounted for. Predictive performance substantially improved by including the most recent voriconazole observations in MIPD.

CONCLUSION

Our results highlight the potential clinical impact of MIPD for voriconazole and indicate the need for a comprehensive (pre-)clinical database as basis for model development and careful external model evaluation for compounds with complex PK before their successful use in MIPD.

Establishment of a mathematical prediction model for voriconazole stable maintenance dose: a prospective study

Background

In patients with invasive fungal infection (IFI), the steady-state serum trough concentration (C min) of voriconazole (VCZ) is highly variable and can lead to treatment failure (C min < 0.5 mg/L) and toxicity (C min ≥ 5.0 mg/L). However, It remains challenging to determine the ideal maintenance dose to achieve the desired C min level quickly.

Aims

This randomized, prospective observational single-center study aimed to identify factors affecting VCZ-C min and maintenance dose and create an algorithmic model to predict the necessary maintenance dose. MeThe study enrolled 306 adult IFI patients, split into two groups: non-gene-directed (A) (where CYP2C19 phenotype is not involved in determining VCZ dose) and gene-directed (B) (where CYP2C19 phenotype is involved in determining VCZ dose).

Results

Results indicated that CYP2C19 genetic polymorphisms might significantly impact VCZ loading and maintenance dose selection. CYP2C19 phenotype, C-reaction protein (CRP), and average daily dose/body weight were significant influencers on VCZ-C min, while CYP2C19 phenotype, CRP, and body weight significantly impacted VCZ maintenance dose. A feasible predictive formula for VCZ stable maintenance dose was derived from the regression equation as a maintenance dose (mg) =282.774-0.735×age (year)+2.946×body weight(Kg)-19.402×CYP2C19 phenotype (UM/RM/NM:0, IM:1, PM:2)-0.316×CRP (mg/L) (p < 0.001).

Discussion

DiThis formula may serve as a valuable supplement to the Clinical Pharmacogenetics Implementation Consortium (CPIC®) guideline for CYP2C19 and VCZ therapy, especially for IFI patients with highly variable inflammatory cytokines during VCZ therapy.

Interaction and potential mechanisms between atorvastatin and voriconazole, agents used to treat dyslipidemia and fungal infections

Purpose: Voriconazole (VOR) is combined with atorvastatin (ATO) to treat fungal infections in patients with dyslipidemia in clinical practice. However, the pharmacokinetic interactions and potential mechanisms between them are unknown. Therefore, this study aimed to investigate the pharmacokinetic interactions and potential mechanisms between ATO and VOR. Patients and methods: We collected plasma samples from three patients using ATO and VOR. Rats were administered either VOR or normal saline for 6 days, followed by a single dose of 2 mg/kg ATO, and then plasma samples were collected at different time points. The incubation models of human liver microsomes or HepG2 cells were constructed in vitro. A high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) system was developed to determine the concentration of ATO, 2-hydroxy-ATO, 4-hydroxy-ATO, and VOR. Results: In patients, VOR significantly reduced the metabolism of ATO and slowed the formation of 2-hydroxy- and 4-hydroxy-ATO. In rats pretreated with orally administered VOR for 6 days or normal saline given a single dose of 2 mg/kg ATO administered orally on Day 6, the t1/2 of ATO was significantly prolonged from 3.61 to 6.43 h, and the area under the concentration-time curve (AUC0-24h) values of ATO increased from 53.86 to 176.84 h μg.L-1. However, the pharmacokinetic parameters of VOR (20 mg/kg) with or without pretreatment with ATO (2 mg/kg) only slightly changed. In vitro studies indicated that VOR inhibited the metabolism of ATO and testosterone, and the IC50 values were 45.94 and 49.81 μM. However, no significant change in transporter behaviors of ATO was observed when VOR or transporter inhibitors were co-administered. Conclusion: Our study demonstrated that VOR has significant interactions with ATO, probably due to VOR's inhibition of the CYP3A4-mediated metabolism of ATO. Based on the clinical cases and potential interactions, the basic data obtained in our study are expected to help adjust the dose of ATO and promote the design of rational dosage regimens for pharmacotherapy for fungal infections in patients with dyslipidemia.

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.

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.

Effects Of Voriconazole Exposure on The Pharmacokinetics of Tacrolimus in Lung Transplantation Patients: Based on Therapeutic Drug Monitoring Data

Tacrolimus and voriconazole are usually used simultaneously in lung transplantations. Voriconazole can increase tacrolimus concentrations by inhibiting the CYP enzyme, which poses a great challenge for dose adjustment. The aim of this study is to clarify the correlation between voriconazole exposure and tacrolimus trough concentrations (C₀ ), and to establish a population pharmacokinetic model including voriconazole trough concentrations (VOZ) as a covariate for dose optimization. All data were retrospectively collected from lung transplantation patients who were subjected to the therapeutic drug monitoring of tacrolimus and voriconazole. The correlation between C₀ and VOZ or voriconazole daily doses was analyzed by Spearman's correlation. A total of 52 patients accounting for 351 pairs of tacrolimus and voriconazole trough concentrations were included. C₀ and C₀ /DD had a significant correlation with VOZ (P<0.01) rather than voriconazole daily doses. A linear one-compartment model with first-order absorption and elimination was used as basic model in population pharmacokinetic analysis. The body weight (WT), daily dose of tacrolimus (DD), VOZ, and hematocrit (HCT) were included as covariates in the final model. With the increase in voriconazole concentrations, the apparent total clearance (CL/F) of tacrolimus decreased significantly. The simulation results showed that the highest proportion of C₀ within the target range can only reach lower than 50% when optimal initial drug regimen was given. Therefore, both tacrolimus and voriconazole concentrations need to be continuously monitored during treatments in lung transplantation patients, and the tacrolimus dose can be optimized according to VOZ based on the established pharmacokinetic model. This article is protected by copyright. All rights reserved.

Combined Impact of Inflammation and Pharmacogenomic Variants on Voriconazole Trough Concentrations: A Meta-Analysis of Individual Data

Few studies have simultaneously investigated the impact of inflammation and genetic polymorphisms of cytochromes P450 2C19 and 3A4 on voriconazole trough concentrations. We aimed to define the respective impact of inflammation and genetic polymorphisms on voriconazole exposure by performing individual data meta-analyses. A systematic literature review was conducted using PubMed to identify studies focusing on voriconazole therapeutic drug monitoring with data of both inflammation (assessed by C-reactive protein level) and the pharmacogenomics of cytochromes P450. Individual patient data were collected and analyzed in a mixed-effect model. In total, 203 patients and 754 voriconazole trough concentrations from six studies were included. Voriconazole trough concentrations were independently influenced by age, dose, C-reactive protein level, and both cytochrome P450 2C19 and 3A4 genotype, considered individually or through a combined genetic score. An increase in the C-reactive protein of 10, 50, or 100 mg/L was associated with an increased voriconazole trough concentration of 6, 35, or 82%, respectively. The inhibitory effect of inflammation appeared to be less important for patients with loss-of-function polymorphisms for cytochrome P450 2C19. Voriconazole exposure is influenced by age, inflammatory status, and the genotypes of both cytochromes P450 2C19 and 3A4, suggesting that all these determinants need to be considered in approaches of personalization of voriconazole treatment.

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.

Treatment of invasive fungal diseases in cancer patients-Revised 2019 Recommendations of the Infectious Diseases Working Party (AGIHO) of the German Society of Hematology and Oncology (DGHO)

BACKGROUND

Invasive fungal diseases remain a major cause of morbidity and mortality in cancer patients undergoing intensive cytotoxic therapy. The choice of the most appropriate antifungal treatment (AFT) depends on the fungal species suspected or identified, the patient's risk factors (eg length and depth of granulocytopenia) and the expected side effects.

OBJECTIVES

Since the last edition of recommendations for 'Treatment of invasive fungal infections in cancer patients' of the Infectious Diseases Working Party (AGIHO) of the German Society of Hematology and Medical Oncology (DGHO) in 2013, treatment strategies were gradually moving away from solely empirical therapy of presumed or possible invasive fungal diseases (IFDs) towards pre-emptive therapy of probable IFD.

METHODS

The guideline was prepared by German clinical experts for infections in cancer patients in a stepwise consensus process. MEDLINE was systematically searched for English-language publications from January 1975 up to September 2019 using the key terms such as 'invasive fungal infection' and/or 'invasive fungal disease' and at least one of the following: antifungal agents, cancer, haematological malignancy, antifungal therapy, neutropenia, granulocytopenia, mycoses, aspergillosis, candidosis and mucormycosis.

RESULTS

AFT of IFDs in cancer patients may include not only antifungal agents but also non-pharmacologic treatment. In addition, the armamentarium of antifungals for treatment of IFDs has been broadened (eg licensing of isavuconazole). Additional antifungals are currently under investigation or in clinical trials.

CONCLUSIONS

Here, updated recommendations for the treatment of proven or probable IFDs are given. All recommendations including the levels of evidence are summarised in tables to give the reader rapid access to key information.

Applying Pharmacogenomics to Antifungal Selection and Dosing: Are We There Yet?

Purpose of Review

This review summarizes recent literature for applying pharmacogenomics to antifungal selection and dosing, providing an approach to implementing antifungal pharmacogenomics in clinical practice.

Recent Findings

The Clinical Pharmacogenetics Implementation Consortium published guidelines on CYP2C19 and voriconazole, with recommendations to use alternative antifungals or adjust voriconazole dose with close therapeutic drug monitoring (TDM). Recent studies demonstrate an association between CYP2C19 phenotype and voriconazole levels, clinical outcomes, and adverse events. Additionally, CYP2C19-guided preemptive dose adjustment demonstrated benefit in two prospective studies for prophylaxis. Pharmacokinetic-pharmacodynamic modeling studies have generated proposed voriconazole treatment doses based on CYP2C19 phenotypes, with further validation studies needed.

Summary

Sufficient evidence is available for implementing CYP2C19-guided voriconazole selection and dosing among select patients at risk for invasive fungal infections. The institution needs appropriate infrastructure for pharmacogenomic testing, integration of results in the clinical decision process, with TDM confirmation of goal trough achievement, to integrate antifungal pharmacogenomics into routine clinical care.