Pharmacogenetics of steady-state metabolism, pharmacokinetics, and adverse effects of voriconazole in healthy participants

Yanting (Phoebe) Wu; Ayşe Gelal; Chisook Moon; Ingrid F Metzger; Jessica BL Lu; John T Callaghan; Todd C Skaar; Zeruesenay Desta

doi:10.1016/j.dmd.2025.100156

. Author manuscript; available in PMC: 2026 Jan 21.

Published in final edited form as: Drug Metab Dispos. 2025 Sep 3;53(10):100156. doi: 10.1016/j.dmd.2025.100156

Pharmacogenetics of steady-state metabolism, pharmacokinetics, and adverse effects of voriconazole in healthy participants

Yanting (Phoebe) Wu ¹, Ayşe Gelal ¹, Chisook Moon ¹, Ingrid F Metzger ¹, Jessica BL Lu ¹, John T Callaghan ¹, Todd C Skaar ¹, Zeruesenay Desta ^1,^*

PMCID: PMC12818346 NIHMSID: NIHMS2129916 PMID: 41027046

Abstract

Voriconazole, a broad-spectrum antifungal, exhibits significant interpatient variability in efficacy and safety. This study assessed the influence of genetic and nongenetic factors on its steady-state pharmacokinetics and adverse effects. In vitro studies characterized voriconazole metabolism. An ancillary analysis was conducted on data from a completed trial involving 61 healthy participants who received a loading dose of 400 mg twice daily on first day, followed by 200 mg twice daily for 8 days. On the third day of voriconazole treatment, plasma and urine samples were collected over a 12-hour period after dose administration. Multiple trough concentrations, adverse events, and laboratory values were recorded throughout the study. Voriconazole and its metabolites were quantified using liquid chromatography—tandem mass spectrometry methods. Genotyping for CYP2C9, CYP2C19, CYP3A4, and CYP3A5 variants was performed using TaqMan assays. In vitro, CYP2C19 predominantly catalyzed the formation of voriconazole N-oxide and methyl hydroxy voriconazole, whereas CYP3A4/5 catalyzed fluoropyrimidine ring hydroxylation. Steady-state voriconazole area under the concentration-time curve (AUC_0-ԏ) was significantly associated with CYP2C19 genotypes (P < .01); over 9-fold reduction in AUC_0-ԏ was noted in CYP2C19 *17/*17 genotype compared with CYP2C19 *2/*2 carriers. We identified voriconazole N-glucuronide in plasma for the first time. Noncompliant subjects exhibited lower voriconazole exposure (P = .0002). Visual and neurologic/psychiatric adverse effects occurred in 79.7% and 72.9% of subjects, respectively, predominantly during the loading dose phase, but showed no association with CYP2C19 genotypes. No liver abnormalities were observed. CYP2C19 polymorphisms and medication adherence significantly influence voriconazole pharmacokinetics but not safety outcomes. These findings support the consideration of CYP2C19 genotyping and adherence monitoring to optimize voriconazole therapy.

Keywords: Voriconazole, Pharmacogenomics, CYP2C19 genotypes, Metabolism, Pharmacokinetics, Adverse effects

1. Introduction

Voriconazole, a broad-spectrum triazole antifungal agent, is widely used to treat invasive fungal infections, including aspergillosis and candidiasis, particularly in immunocompromised individuals.^1-4 However, voriconazole exhibits significant interindividual variability in clinical outcomes and adverse effects,^5,6 primarily due to interpatient differences in voriconazole exposure.^5,7,8 Plasma concentrations below 0.5 mg/L and above 6 mg/L are at increased risk for treatment failure and adverse effects, respectively.^9-12 This narrow therapeutic range, nonlinear pharmacokinetics, extensive interindividual variability in its exposure,^6,13-16 and high propensity for drug-drug interactions (DDIs)^2,17,18 compromise optimal and safe use of voriconazole.

Voriconazole is primarily eliminated through hepatic metabolism (Supplemental Fig. 1), with approximately 98% of the orally administered dose converted to metabolites.¹⁹ The major metabolic pathway involves N-oxidation, predominantly catalyzed by CYP2C19, with contributions from CYP3A4, CYP2C9, and flavin-containing monooxygenases 1/3.^20-23 Minor pathways include hydroxylation at the fluoropyrimidine ring and methyl group,^19,21 as well as direct N-glucuronidation by UGT1A4²⁴ (Supplemental Fig. 1), though the in vivo relevance of these routes remains unclear. Variability in voriconazole exposure among individuals is largely attributed to differences in these metabolic processes. This variability is influenced by genetic factors, notably CYP2C19 polymorphisms. Several studies conducted in both healthy participants and patient populations have reported a marked effect of CYP2C19 genetic polymorphisms on voriconazole exposure.^6,25-29 This gene variation is estimated to account for approximately 40% of voriconazole interpatient variability in exposure.^16,30 The Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline has been published to support associations of CYP2C19 phenotypes and voriconazole exposure and offer therapeutic recommendations based on CYP2C19 genotypes.³¹

However, even after accounting for CYP2C19 genetic variations, a considerable interpatient variability in voriconazole exposure is observed due to the effects of several nongenetic factors including age, sex, comorbidities, adherence, DDIs, and inflammation.^6,13-16,32 Therefore, despite notable advances, several knowledge gaps persist in our understanding of the determinants of voriconazole metabolism and pharmacokinetics. First, the specific enzymes responsible for voriconazole hydroxylation^15,21 and the contributions of these pathways to voriconazole clearance remain unclear (Supplemental Fig. 1). Second, a marked effect of the CYP2C19 *17 allele on the disposition of a single dose of voriconazole was reported,²⁷ and clinical studies in patients indicate a marked effect of this allele on voriconazole trough concentrations, but formal steady-state pharmacokinetic studies quantifying the effect of the *17 allele on voriconazole disposition are limited. Third, predictors of voriconazole-induced adverse effects, including hepatotoxicity, visual adverse effects, and neurotoxicity,^17,33 are not well defined, making it challenging to identify at-risk patients. Fourth, pill counts are commonly used to measure adherence in clinical trials, but their accuracy is questionable unless complemented by objective measures of adherence.³⁴ Fifth, the in vivo presence of voriconazole N-glucuronide has not been confirmed, although it was detected in vitro.²⁴ Thus, addressing these gaps would contribute to improving the understanding of voriconazole disposition and effects.

In this study, we investigated voriconazole metabolism and pharmacokinetics through in vitro assays using human liver microsomes (HLMs) and human intestinal microsomes (HIMs), as well as recombinant enzymes. Additionally, we analyzed data from a clinical trial involving 61 healthy participants who received a 400 mg loading dose twice daily on day 1, followed by 200 mg twice daily for 8 days. Our objectives included characterizing steady-state pharmacokinetics, assessing acute safety and adverse events (AEs), examining associations between genetic variants (CYP2C19, CYP2C9, CYP3A4, and CYP3A5) and voriconazole exposure and effect, evaluating the impact of noncompliance through trough concentration measurements, and detecting voriconazole N-glucuronide in plasma.

2. Materials and methods

2.1. Chemicals

Voriconazole, voriconazole N-oxide, hydroxy voriconazole (fluoropyrimidine site), and nevirapine were purchased from Toronto Research Chemicals. Formic acid, β-glucuronidase type H-5 from Helix pomatia, and glycine were purchased from Sigma-Aldrich. Methanol, ethyl acetate, sodium hydroxide, sodium chloride, and sodium azide were purchased from Fisher Scientific Company LLC. Sodium acetate was obtained from J. B. Baker. Water for liquid chromatography—mass spectrometry was prepared using a Nanopure Infinity UV system (Barnstead Thermolyne). Other chemicals were of high-performance liquid chromatography (HPLC) grade.

2.2. In vitro studies

In our clinical study, consistent with previous report,¹⁹ we identified and quantified 2 hydroxylated metabolites of voriconazole: methyl hydroxylation and fluoropyrimidine hydroxylation. Initially, CYP3A was reported to catalyze methyl hydroxylation,²¹ but the enzymes responsible for fluoropyrimidine hydroxylation remains unknown although some reviews implicate CYP2C19¹⁵ (Supplemental Fig. 1). To address these uncertainties, we conducted in vitro metabolism studies using HLMs and HIMs, as well as recombinant enzymes, aiming to pinpoint the enzyme catalyzing the formation of the second hydroxylated metabolite and to confirm that CYP3A catalyzes methyl hydroxylation. Voriconazole’s N-oxidation, primarily mediated by CYP2C19, served as a positive control in our experiments.

2.2.1. Incubation conditions

We investigated voriconazole metabolism using pooled HLMs, HIMs, and recombinant cytochrome P450 (P450) enzymes. Incubation and sample processing were performed in a 96-well plate.

Voriconazole (21 μL of 5 mg/mL in methanol) was evaporated to dryness and reconstituted in phosphate buffer (pH 7.4), and then serially diluted with phosphate buffer to desired concentrations. Incubations were conducted in 96-well plates, each containing 100 μL of substrate solution (Thomas Scientific) and either 30 μL of HLMs/HIMs (0.5 mg/mL protein) or 10-20 μL of expressed P450s, all prewarmed on an Isotemp heater (Fisher Scientific) at 37 °C for 5 minutes. Reactions were initiated by adding 20 μL of 1 mM NADPH, bringing the total volume to 150 μL, yielding the required final concentrations of voriconazole, HLMs, and HIMs (0.5 mg/mL protein) or expressed P450s (10 pmol) and NADPH (1 mM).

Time-course studies were performed with 0.1 μM voriconazole at intervals of 0, 15, 30, 45, 60, and 90 minutes. For kinetic analyses, voriconazole concentrations ranging from 0 to 500 μM were incubated in HLMs and HIMs for 20 minutes under linear conditions. Expressed enzymes were incubated with single concentration of voriconazole (25 μM) for 20 minutes. Reactions were terminated by transferring 100 μL of the incubation mixture into another clear 96-well plate (0.65 mL tubes) containing 20 ng/mL nevirapine (internal standard [IS]) in 300 μL of ice cold methanol solution. Samples were mixed and shaken for 2 minutes at 2500 rpm on a bench mixer (Benchmark) and centrifuged at 4 ° C for 20 minutes on AllgeraTM 6R centrifuge (Beckmen Coulter), and 140 μL of supernatant was transferred to a new plate. A 10 μL aliquot was analyzed using high performance liquid chromatography—tandem mass spectrometry. Calibration standards were prepared similarly, omitting the 37 °C incubation.

Apparent kinetic constants ( $V_{\max}$ and $K_{m}$ ) were estimated by fitting appropriate kinetic equations to the formation rate of voriconazole metabolism to the respective metabolites versus voriconazole concentration using nonlinear regression analysis in GraphPad Prism version 7.04 for Windows (GraphPad; www.graphpad.com). In vitro intrinsic clearance ( ${CL}_{int}$ ) was calculated by dividing $V_{\max}$ by $K_{m}$ . In vitro ${CL}_{int}$ was scaled to the organ level (liver and intestine) by accounting for microsomal protein content and organ weight using established equations and literature values.^35,36 Organ clearance was subsequently estimated using the Well-Stirred model, incorporating blood flow and the fraction of unbound (fu) drug in plasma.

2.3. Clinical study

This study presents ancillary data from a previously completed clinical trial conducted at Indiana University’s Clinical Research Center, which investigated the impact of steady-state voriconazole on CYP2B6 activity.³⁷ The trial involved 61 healthy participants who received a clinical regimen consisting of a loading dose of 400 mg voriconazole twice daily on day 1, followed by 200 mg twice daily for 8 days to achieve steady-state concentrations. CYP2B6 activity was assessed by evaluating the metabolism and disposition of a single 100 mg oral dose of efavirenz. The study protocol was approved by the Indiana University School of Medicine Institutional Review Board, and informed consent was obtained from all participants. The trial is registered at http://www.clinicaltrials.gov (trial identifier number: NCT01104376).

2.3.1. Study participants

Nonpregnant adults aged 18—55 years with a body mass index of ≤32 were enrolled in this study. Participants were deemed healthy based on a comprehensive pre-enrollment screening, which included medical history, physical examination, standard laboratory tests (blood and urine), and ECG. Further details on the inclusion and exclusion criteria are available in our previous publication.³⁷

2.3.2. Study design

This study was a one-sequence, open-label, sequential trial designed to determine the effect of steady-state voriconazole on CYP2B6 activity, measured by the metabolism and pharmacokinetics of efavirenz and its metabolites. The clinical trial lasted 17 days and was conducted in 3 phases, including 2 full-day inpatient sessions and 8 outpatient visits. The components of the study design and procedures are detailed in our previous publication.³⁷ Here, we focus on procedures related to voriconazole treatment to steady state, pharmacokinetics, and adverse effects.

Voriconazole dosing and schedule of assessments are summarized in Supplemental Table 1. Prior to initiating voriconazole treatment (days 1—8), plasma (0—168 hours) and urine (0-48 hours) pharmacokinetics of a single 100-mg dose of efavirenz were collected. The extended sampling time for efavirenz was necessitated by its long half-life.³⁸ In addition, standard safety laboratory tests, including a complete metabolic panel, vital signs, and ECG, were performed before efavirenz administration and served as control laboratory values. After the final blood sample on the morning of day 8 (168 hours), marking the end of the efavirenz-only phase at the outpatient clinic, subjects received a 400 mg voriconazole loading dose in the morning immediately after the blood draw and another 400 mg in the evening on day 8.

On day 9, participants switched to maintenance doses of 400 mg/day (200 mg in the morning and 200 mg in the evening) and continued this treatment until day 16. On the morning of day 10, participants were admitted to the clinical research center for an inpatient stay. Standard safety laboratory tests, including a complete metabolic panel, vital signs, and ECG, were performed and blood and urine samples were obtained before voriconazole administration. Participants then received their morning dose (200 mg) of voriconazole orally on day 10, followed by a 100-mg dose of efavirenz orally 1 hour later. Blood and urine samples were collected for 12 hours after voriconazole dosing for voriconazole steady-state determination. Further blood sample collection continued up to 168 hours after efavirenz administration for efavirenz pharmacokinetics.

Participants were asked to record their voriconazole intake and any adverse effects experienced during treatment (days 8—16) in a hand-held diary, noting both morning (am) and evening (pm) entries. Pre—dose administration blood samples were collected on the mornings of days 11, 12, 13, and 15, immediately before the next morning dose of voriconazole, and at exit on day 17, to assess compliance and steady-state achievement. On day 17, participants returned to the research center for final blood sampling and comprehensive exit examinations, including standard safety laboratory tests—a complete metabolic panel, vital signs, and ECG. Study diaries were collected, and a pill count was conducted, marking the conclusion of the research study.

Plasma samples were separated by centrifugation at 3000 rpm, and two 10-mL urine aliquots were collected after recording the total volume. Both plasma and urine samples were stored at −80 °C until analysis for efavirenz, voriconazole, and their respective metabolites.

2.3.3. Voriconazole safety assessments

Participants recorded all AEs experienced during a 9-day voriconazole treatment period in a structured diary. For each AE, subjects documented the severity, time of onset, and peak intensity following both morning (am) and evening (pm) doses. Severity was rated on a standardized scale: none = “0”, mild = “1”, mild, moderate = “2”, severe = “3”. AEs were categorized into 4 primary groups: (1) visual AEs (VAEs), including blurred vision, photophobia, color vision changes, and visual field defects; (2) neurologic and psychiatric AEs (NAEs), encompassing symptoms such as headache, dizziness, lightheadedness, numbness in fingers, and psychiatric symptoms such as nervousness, hallucinations, anxiety, irritability headache, dizziness, and impaired concentration; (3) gastrointestinal AEs (GIAEs), including nausea, diarrhea, abdominal pain, constipation, vomiting, and poor taste; and (4) other AEs (OAEs) for symptoms not fitting into the above categories, including dry mouth, fever, stiff joints, sore throat, frequent urination, and a heavy feeling in the eyes. This structured approach to AE documentation facilitates comprehensive safety monitoring and aids in the early detection of potential drug-related toxicities during voriconazole therapy.

Clinical laboratory tests, including hematology, clinical chemistry, and urinalysis, were conducted at 3 points to assess the potential for voriconazole-induced changes in liver enzymes and other laboratory values: at baseline, day 10 (during voriconazole steady-state treatment), and day 17 (study exit).

2.4. Analysis of voriconazole and metabolites in plasma and urine

A new HPLC—tandem mass spectrometry method was developed to simultaneously measure plasma and urine concentrations of efavirenz, voriconazole, and their respective major metabolites. This method is described in detail in our previous publication.³⁷ Briefly, plasma and urine samples were treated with β-glucuronidase and incubated for 18 hours on a shaker at 37 °C. After deconjugation, ISs were added, and the samples underwent liquid/liquid extraction. The organic layer was dried, reconstituted in the mobile phase, and injected into the liquid chromatography—tandem mass spectrometry system. Calibration curves were generated by spiking blank plasma or urine with known amounts of analytes.

Liquid chromatography—tandem mass spectrometry analysis was performed on an Applied Biosystems API 3200 triplequadrupole mass spectrometer controlled by Analyst software version 1.5.1 (Applied Biosystems/MDS Sciex) on a PC running Windows XP (Microsoft). This MS/MS system was coupled to an HPLC system consisting of 2 LC-20AD pumps, an SIL-20AHT UFLC autosampler, a DGU-20A3 degasser, and a CBM-20A controller (Shimadzu). Chromatographic separation was achieved using a Phenomenex Luna C18 column (150 mm × 4.6 mm, 5-μm particle size) and a Phenomenex Luna C18 4 × 3.00-mm guard column (Phenomenex). Mobile phase A consisted of methanol-formic acid (0.1% in water, 1/99, v/v), and mobile phase B consisted of methanol-formic acid (0.1% in water, 99/1, v/v), delivered in a gradient elution mode at a flow rate of 0.8 mL/min.

Mass spectrometry optimization was achieved by adjusting both compound-dependent and instrument-dependent parameters for efavirenz and its metabolites, dihydroxy (DiOH) voriconazole and methyl hydroxy voriconazole (M3), in negative mode using 30 μL of 1 μg/mL efavirenz-d₄ as an IS. For voriconazole, voriconazole N-oxide, and hydroxyl voriconazole (M2), 500 ng/mL nevirapine was used as the IS in positive mode. The tandem mass spectrometry parameters, optimized conditions for the analytes and ISs in both negative and positive ion modes, as well as the compound-dependent mass spectrometer parameters and the parent and fragment ions used in multiple reaction monitoring mode for quantification, are detailed in our previous publication³⁷ Specifically, multiple reaction monitoring was used to measure Q1/Q3 transitions for voriconazole at 349.98/280.95, voriconazole N-oxide at 365.95/223.94, and hydroxy voriconazole (M2) at 366.00/224.00 in positive mode, and methyl hydroxyl voriconazole (M3) at 364.07/222.00 and DiOH-voriconazole at 380.10/157.10 in negative mode. Details of the assay are described in our previous publication.³⁷

2.5. Analysis of free and conjugated voriconazole and metabolites in plasma

In a subset of human plasma from 14 participants, conjugates of voriconazole and its metabolites were quantified. Plasma samples were processed without β-glucuronidase to preserve both free and conjugated forms of voriconazole and its metabolites, voriconazole N-oxide, methyl hydroxy voriconazole, and hydroxy voriconazole (fluoropyrimidine hydroxy voriconazole), as well as relevant glucuronide conjugates (voriconazole N-glucuronide, hydroxy voriconazole O-glucuronide, and DiOH-voriconazole O-glucuronide). These assays were performed using a QTRAP 6500+ mass spectrometer (Applied Biosystems) fitted with an electrospray ionization source and coupled to an ultra high performance liquid chromatography (UHPLC) system (Shimadzu USA) equipped with 2 AD pumps, an AD autosampler, and an AD column oven. Data acquisition was managed using Analyst software version 1.7.0 with MultiQuant 3.0.2 quantification software. Samples were protein-precipitated with methanol containing 8 ng/mL nevirapine (IS), vortexed, centrifuged (3000 rpm, 4 °C, 20 minutes), and the supernatant was injected (3 μL) into the UHPLC. Chromatographic separation was achieved on a Waters Acquity UHPLC HSS T3 column (150 mm × 2.1 mm, 1.8 μm) at 40 °C, using 0.1% formic acid in water (mobile phase A) and methanol (mobile phase B) at a flow rate of 0.5 mL/min. The gradient program began at 50% B (0—2 minutes), shifted to 100% B (2 minutes), and reverted to 50% B (2.01—7 minutes). Voriconazole, voriconazole N-oxide, hydroxy voriconazole, voriconazole glucuronide, and DiOH glucuronide were analyzed in positive ion mode. Methyl hydroxy voriconazole and DiOH-voriconazole were analyzed in negative mode. Compound and instrument-specific parameters were optimized as detailed in Supplemental Table 2.

Standard curves (0—10,000 ng/mL) and quality controls (8—8000 ng/mL) samples were prepared in human plasma via serial dilution of stock solutions (stored at −80 °C until further use). Samples were protein-precipitated with methanol containing 8 ng/mL nevirapine (IS), vortexed, centrifuged (3000 rpm, 4 ° C, 20 minutes), and the supernatant was injected (3 μL) into the UHPLC. Analyte concentrations were calculated from peak area ratios (analyte/IS) using standard curve slopes. Metabolites lacking individual standards (methyl hydroxy voriconazole, DiOH-voriconazole, and glucuronides) were quantified indirectly using the hydroxy voriconazole (fluoropyrimidine hydroxy voriconazole) standard curve due to structural similarity. The lower limit of quantification for all analytes was 3 ng/mL. Multiple reaction monitoring was used to measure Q1/Q3 transitions for voriconazole, its metabolites and nevirapine are displayed in Supplemental Table 2.

2.6. DNA genotyping

Genomic DNA was extracted from whole blood using a DNA minikit (Qiagen). Genotyping for variants of the CYP genes was performed using 2 platforms: TaqMan assay reagent allelic discrimination kits, according to the supplier's instructions (Applied Biosystems), and/or the OpenArray platform (Applied Biosystems), as previously described.^39,40 The following variants relevant to voriconazole metabolism were assayed: CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), CYP2C19*2 (rs4244285), CYP2C19*3 (rs4986893), CYP2C19*17 (rs12248560), CYP3A4 (rs2246709), CYP3A4*22 (rs35599367), CYP3A5*3 (rs776746), CYP3A5*6 (rs10264272), and CYP3A5*7 (rs41303343).

2.7. Pharmacokinetic analysis

Steady-state pharmacokinetic parameters were estimated by noncompartmental analysis using Phoenix WinNonlin version 8.4 (Certara USA). C_max, time to reach C_max, and minimum plasma concentration (C_min) were recovered directly from observed plasma concentration-versus-time curve. The area under the plasma concentration-versus-time curve (AUC) from time 0 to the last observed concentration at 12 hours (AUC_0-τ) was estimated using the linear/logarithmic trapezoidal method for both absorption and elimination phases of the curve. The λ_z was estimated by linear regression of the terminal portion of the log-transformed concentration-time profile using at least 3 data points. The elimination half-life (t_1/2) was calculated as ln2/λ_z. The apparent volume of distribution during the terminal phase (V_F) was computed by dividing CL_F by λ_z. Additionally, CL_F and V_F were normalized by each subject’s body weight to yield CL_F/kg and V_F/kg. The metabolite-to-parent ratio (AUC_0-τ,metabolite/AUC_0-τ,voriconazole) was calculated by dividing AUC_0-τ of the metabolite by AUC_{_0-τ} of voriconazole.

The amounts of the parent drug and metabolites excreted in urine (A_e) over 12 hours were obtained. Renal clearance (CL_r) of the parent drug and metabolites was calculated by dividing the amount of parent drug or metabolites excreted unchanged in urine over the first 12 hours (A_e) by the corresponding plasma AUC_{_0-τ}. The formation clearance (CL_f) of metabolites from voriconazole was estimated as the quotient of the amount of metabolite recovered in urine (A_e, metabolite) and the AUC_0-τ of voriconazole. DiOH-voriconazole is a sequential metabolite in the voriconazole metabolic pathway. The CL_f of DiOH-voriconazole from the primary metabolites: voriconazole N-oxide and methyl- and fluoropyrimidine hydroxy voriconazole was computed by dividing A_e of DiOH-voriconazole by the sum of AUC_0-τ values for the primary metabolites. The percentage of the dose excreted over the first 12 hours was obtained by dividing the molecular weight-corrected A_e (in μmol) of voriconazole and its metabolites by the 200 mg (572.6 μmol) dose of voriconazole. The urine ratio was calculated by dividing the molecular weight-corrected A_e of the metabolites by the molecular weight-corrected A_e of voriconazole (A_e, metabolite/A_e, voriconazole).

2.8. Statistical analysis

All statistical analyses were performed using GraphPad Prism 10.2.2 (GraphPad). Descriptive statistics were used to summarize the pharmacokinetic data for voriconazole and its metabolites, with results reported as geometric means (GMs) and 95% confidence intervals (CIs). Associations among individual genotypes as well as genotype-predicted phenotypic groups with voriconazole disposition and effects were performed using either nonparametric ANOVA (the Kruskal-Wallis test) to compare multiple independent groups or Mann-Whitney U test to compare 2 independent groups as appropriate. Dunn's test was applied when appropriate to determine which groups significantly differed from each other. Additionally, differences in the frequency of AEs among the 3 groups were analyzed using the chi-square test (or Fisher’s exact test when the frequency of AEs was less than 5). A P value of ≤.05 was considered statistically significant. To quantify the contribution of CYP2C19 genotype to interindividual variability in voriconazole exposure (AUC), a linear regression analysis was conducted.

3. Results

3.1. In vitro studies

3.1.1. Characterization of voriconazole metabolism in vitro

Pilot experiments were performed to identify chromatographic peaks observed in HLMs. Besides the parent drug, 3 peaks were noted in the incubations of voriconazole with HLMs and cofactors, but no metabolites were formed in the negative control experiments (no NADPH, no incubation, no drug or no HLMs). Voriconazole and N-oxide was identified using authentic standards obtained from commercial sources (see above). Two peaks consistent with hydroxy voriconazole (M2 and M3) were identified in the microsomal incubations (data not shown), but we were able to obtain commercially an authentic standard for one of the hydroxy voriconazole and this was consistent with hydroxylation at the fluoropyrimidine site. Because its chromatographic retention time and MS/MS characteristics aligned with that of hydroxy voriconazole (M2), M2 was designated as hydroxy voriconazole (or fluoropyrimidine hydroxy voriconazole). The structure of the second hydroxy voriconazole (M3) remain uncertain, but we speculate that it may represent methyl hydroxylation. In the subsequent descriptions, we used hydroxy voriconazole (or fluoropyrimidine hydroxy voriconazole) to represent M2, and methyl hydroxy voriconazole to denote M3.

The biotransformation of voriconazole to N-oxide, hydroxy voriconazole, methyl hydroxy voriconazole was tested in HLMs, HIMs, and expressed P450s (Fig. 1). Incubation of voriconazole (0.1 μM) with HLMs and NADPH for 0—90 minutes show depletion of the parent drug over time, accompanied by increase in the formation metabolites. The amount formed was highest for voriconazole N-oxide followed by hydroxy voriconazole, with methyl hydroxy voriconazole being formed to a small extent (Fig. 1A). Depletion of voriconazole and formation of the metabolites were not observed in negative control experiments.

Fig. 1. — Voriconazole metabolism in HLMs, HIMs, and expressed P450s. Time course of voriconazole metabolism in HLMs (A), Michaelis-Menten Kinetics for the formation of voriconazole metabolites in HLMs (B) and in HIMs (C), and metabolism of voriconazole to N-oxide (Vori N-oxide) (D), methyl hydroxy-voriconazole (methyl OH-Vori) (E), and hydroxy voriconazole (OH-Vori) (F). Data represent averages of duplicate incubations.

The formation of voriconazole N-oxide, hydroxy voriconazole, methyl hydroxy voriconazole from voriconazole in HLMs and HIMs, respectively, are shown in Fig. 1, B and C, respectively. The kinetic data in both HLMs and HIMs best fit to Michaelis-Menten equation and the corresponding kinetic parameters recovered ( $V_{\max}$ and $K_{m}$ ) as well as the in vitro ${CL}_{int}$ are displayed in Table 1. In both HLMs and HIMs, the in vitro ${CL}_{int}$ for the formation of voriconazole N-oxide was highest. In HLMs, the ${CL}_{int}$ for the formation of voriconazole N-oxide was over 16- and 27-fold higher than the ${CL}_{int}$ of hydroxy voriconazole and methyl hydroxy voriconazole, respectively. Similarly, the ${CL}_{int}$ for the formation of voriconazole N-oxide in HIMs was approximately 27- and 67-fold higher than the ${CL}_{int}$ of hydroxy voriconazole and methyl hydroxy voriconazole, respectively. Based on the in vitro ${CL}_{int}$ , the liver appears to be the primary site for voriconazole metabolism, accounting for approximately 90% of its total ${CL}_{int}$ , with voriconazole N-oxidation representing the major metabolic pathway of voriconazole in both systems (HLMs and HIMs).

Table 1.

Kinetics for the Formation of Voriconazole Metabolite in HLMs and HIMs

The values of $K_{m}$ and $V_{\max}$ were derived by fitting the Michaelis-Menten equation to reaction rates obtained from incubations of voriconazole across a range of concentrations (0-250 μM in HLMs and 0-125 μM in HIMs).

The parameters were computed based on the following equations:

^aIn vitro ${CL}_{int} : {CL}_{int} = \frac{V m a x}{K m}$

^bOrgan scaled: ${CL}_{int, organ}$ = ${CI}_{int}$ × MPPGL/I × Organ Weight.

^cHepatic/Intestinal Clearance (Well-Stirred model): ${CI}_{organ} = \frac{Q * {f u b B}^{*} C L i n t_{, o r g a n}}{Q + (f u B * C L i n t_{, o r g a n})}$

Where; MPPGL/I: microsomal protein per gram liver (40 mg)/intestine (20.6 mg), Organ Weight: liver (~1500 g) and intestine (~800 g), Q: blood flow to liver (87 L/h) and to intestine (66 L/h), and fuB: fraction unbound in blood = fu in plasma * blood plasma ratio (fu in plasma = 0.476; blood plasma ratio was assumed to be 1).

Analytes	$V_{\max}$ pmol/min/mg protein	$K_{m}$ μM	${CL}_{int}^{a}$ μL/min/mg protein	Organ Scaled ${CL}_{int}^{b}$ L/h	Organ Clearance^c L/h
HLM
Voriconazole N-oxide	45.51	35.94	1.27	5.47	2.53
Hydroxy voriconazole	13.71	179.40	0.076	0.33	0.16
Methyl hydroxy voriconazole	0.70	15.15	0.046	0.20	0.095
HIM
Voriconazole N-oxide	7.70	12.76	0.60	0.60	0.29
Hydroxy voriconazole	3.04	135.90	0.022	0.022	0.011
Methyl hydroxy voriconazole	0.21	22.36	0.0093	0.0093	0.0044

Open in a new tab

${CL}_{int}$ values recovered in HLMs and HIMs were scaled to whole liver and intestine using appropriate scaling factor and then used to estimate organ clearances (hepatic and intestinal) using the Well-Stirred model (Table 1).

In expressed P450 enzymes, formation of both voriconazole N-oxide and methyl hydroxy voriconazole were primarily catalyzed via CYP2C19 and to a small extent by CYP3A4 and CYP3A5 (Fig. 1, D and E). Formation of hydroxy voriconazole was predominantly catalyzed by CYP3A4 and CYP3A5 (Fig. 1F).

3.2. Clinical studies

3.2.1. Participant demographics

Sixty-one healthy participants completed all 3 phases of the study. Demographic characteristics stratified by different CYP2C19, CYP3A4/5, and CYP2C9 genotypes and predicted phenotypes, are summarized in Supplemental Tables 3-5, respectively. Most study participants were White (53.3%), followed by African American (45.0%). The mean age of the cohort was 31.9 ± 11.5 years, indicating a relatively young sample with a broad age range. The average weight was 74.8 ± 13.1 kg, and the mean body mass index was 24.9 ± 3.4 kg/m², suggesting a generally healthy population in terms of body composition.

3.2.2. Voriconazole AEs and safety evaluation

Voriconazole AEs and laboratory safety evaluations were collected as described in Supplemental Table 1.

Of the 61 participants, AE information was unavailable for 2 participants (3.3%). Of the 59 participants who completed their diaries and were included in the safety evaluation, 6 (10.2%) did not report any AEs. Most study participants (53/59 or 89.8%) experienced at least one AE, with most participants (41/59 or 67.2%) experiencing more than one type of categorized AE after voriconazole administration. Additionally, the number of participants reporting AEs was tracked in the morning (am) and evening (pm) during the voriconazole regimen (Fig. 2). Most participants reported AEs during the first 2 days of treatment, with VAEs being the most frequent symptoms, likely associated with the high loading dose of voriconazole (400 mg orally twice daily) on the first day of treatment. These AEs subsided during the subsequent treatment phase with 200 mg twice daily.

Fig. 2. — Subject-reported adverse effects of voriconazole. Study subjects (N = 61) received 2 loading doses (400 mg) twice daily on the first day of voriconazole treatment on day 8 of the clinical study, followed by a maintenance dose of 200 mg twice daily (200 mg in the morning, am, and 200 mg in the evening, pm) for the subsequent 8 days. Adverse effects of voriconazole were recorded in the subject diary throughout the course of treatment with voriconazole. The AEs were categorized into VAEs, NAEs, gastrointestinal AEs (GIAEs), and other AEs (OAEs). Displayed are number of subjects experiencing AEs versus time during voriconazole treatment.

The percentage of participants reporting AEs, stratified by the 4 main categories, along with a detailed breakdown of AEs under each category, are summarized in Table 2. Most participants (79.7%) reported VAEs, with light sensitivity and abnormal vision being the most common manifestations. NAEs occurred in 72.9% of the participants, with headaches being the most common (59.3%). Gastrointestinal AEs were less frequent (22.0%), with nausea being the most prevalent symptom, reported by 10.2% of participants (Table 2). Moreover, the severity assessment based on self-reported scores did not indicate any severe AEs. The highest average score of 1.57, falling within the mild to moderate range, was reported on the morning of the first day of voriconazole treatment, and the severity/score gradually decreased over the course of voriconazole treatment.

Table 2.

AE Profiles after Voriconazole Administration

AEs data were recorded in study diary and reported by study subjects during oral treatment with voriconazole. All AEs collected during the loading and maintenance doses are included (see Supplemental Table 1). Two of 61 of the study subjects did not provide dairy for AE recording. Therefore, 59 subjects who reported AEs were included in the analysis, and 6 of 59 subjects did not report any AEs. The AEs were categorized into VAEs, NAEs, GIAEs, and OAEs, with each category further subdivided (see Materials and methods). The data illustrate the number and proportion (percentage) of participants in the study who encountered at least one of the symptoms detailed in each respective subcategory.

AEs	No. of Subjects	Percentage
VAEs
Light sensitivity (photophobia)	37	62.7
Visual abnormalities^a	34	57.6
Blurred vision, hazy vision	26	44.1
Seeing bright light, white spots, strobing lights	13	22.0
Change of colors, seeing colors (dyschromatopsia)	8	13.6
Wavy lines	4	6.8
Diminished night vision	1	1.7
Haze in dark	1	1.7
Total number of subjects experiencing at least one VAE	47	79.7
NAEs
Symptoms related to neurological and cognitive system^a	39	66.1
Headache	35	59.3
Dizziness, lightheadedness	8	13.6
Drowsiness, sleepy, hard to focus, heavy head	8	13.6
Disorientation	1	1.7
Numbness in fingers	1	1.7
Weakness, fatigue, tired, sluggishness	4	6.8
Psychiatric symptoms^a	2	3.4
Nervousness, anxiousness	2	3.4
Irritability	1	1.7
Sleep disturbance^a	2	3.4
Intense dream	1	1.7
Unable to sleep	1	1.7
Total number of subjects experiencing at least one NAE	43	72.9
GIAEs
Nausea	6	10.2
Diarrhea	3	5.1
Slimy feeling mouth, wired taste	2	3.4
Constipation	2	3.4
Stomachache	1	1.7
Total number of subjects experiencing at least 1 GIAE	13	22.0
OAEs
Dry mouth	4	6.8
Fever	1	1.7
Stiff joints	1	1.7
Sore throat	1	1.7
Frequent urination	1	1.7
Heavy eye feeling	1	1.7
Total number of subjects experiencing at least one OAE	8	13.6
None	6	10.2

Open in a new tab

VAEs, visual adverse events; NAEs, neurological and psychiatric adverse events; GIAEs, gastrointestinal adverse events; OAEs, other adverse events.

Each AE category was further subdivided (see Methods section). The data illustrates the number and proportion (percentage) of participants in the study who encountered at least one of the symptoms detailed in each respective sub-category.

Liver function and other standard laboratory values were obtained at 3 time points (Supplemental Table 1): baseline (before voriconazole administration), on day 10 (steady-state voriconazole), and on day 17 (exit test). None of the study participants exhibited abnormal aspartate aminotransferase, alanine aminotransferase, or alkaline phosphatase levels. Moreover, overall, changes in these liver enzymes were not significantly different from the baseline values or achieved the US Food and Drug Administration—provided safety threshold of 3 times the upper limit of normal values for these enzymes at any time point of the study period (Supplemental Fig. 2A-C).

When comparing laboratory values throughout the study period, there was a statistically significant reduction in bilirubin levels among the 3 time points of safety (P = .0037); Dunn’s pot hoc test indicates that there was a significant difference between the baseline values versus values on day 17 (exit) (Supplemental Fig. 2D). Only 1 of 61 participants had a bilirubin level greater than 1.5× the upper limit of normal (1.5 mg/dL) on day 10, but this participant did not report any relevant symptoms. A statistically significant difference was observed among the 3 time points regarding albumin (Supplemental Fig. 2E, P = .0006) and protein levels (Supplemental Fig. 2F, P < .0001); Dunn’s post hoc test reveal that day 10 values were significantly lower than baseline or day 17 values. However, these effects appeared to be transient, as albumin and protein levels returned to normal by day 17.

3.3. Plasma pharmacokinetics of voriconazole and metabolites

Steady-state pharmacokinetic data were available for all 61 healthy individuals who completed voriconazole treatment. In addition, multiple trough concentrations were obtained from each participant during voriconazole treatment (Supplemental Table 1) to assess compliance and steady-state achievement.

Fig. 3 shows the means, with 95% CIs, of the plasma concentration-versus-time profiles of voriconazole and its metabolites for the entire cohort (N = 61) during the steady-state dosing interval (0-τ or 0—12 hours) period (Fig. 3A). The extended pharmacokinetics profiles including the multiple trough concentrations throughout voriconazole treatment are shown in Fig. 3B. Based on the mean plasma concentration values, it appears that voriconazole steady-state conditions were achieved throughout voriconazole treatment and full treatment compliance was ensured, which was consistent with the pill count method and self-report of study participants (data not shown).

The corresponding steady-state pharmacokinetic parameters for the data presented in Fig. 3A are displayed in Supplemental Table 6 as GM, with 95% CIs. Voriconazole was rapidly absorbed with a median t_max of 1.5 hours. The GMs (95% CI) of the half-life, $C_{\max}$ , steady-state area under the concentration-time from 0 to dosing interval or 12 hour (AUC_0-τ), and the weight-adjusted apparent oral steady-state clearance (CL_F/Wt) of voriconazole were 7.3 (6.2—8.7) hours, 1956 (1747—2190) ng/mL, 11,791 (11,019—13,877) h*ng/mL, and 217 (185—255) mL/h/kg, respectively.

As shown in Supplemental Table 6 and Fig. 3, voriconazole N-oxide was the major circulating metabolite in plasma, with a relative plasma exposure of approximately 3 times higher than that of voriconazole. The exposure of both voriconazole and voriconazole N-oxide in our study was slightly higher than previously reported values,⁴¹ possibly attributed to the deconjugation process we used during quantification. The terminal elimination half-life of voriconazole N-oxide was also 3.3 times longer than voriconazole and thus the plasma concentrations versus time profile of voriconazole N-oxide indicate an elimination-rate—limited process, whereas hydroxy voriconazole (M2) and methyl hydroxy voriconazole (M3) declined in parallel with voriconazole plasma concentrations, suggesting formation-rate—limited processes (Fig. 3A). The exposure of hydroxy voriconazole (M2) was more than 20 times lower than that of voriconazole, with a similar half-life as voriconazole (Fig. 3A; Supplemental Table 6). Methyl hydroxy voriconazole and DiOH-voriconazole were present at much lower concentrations in plasma (over 200 times lower exposure) than that of voriconazole, while their half-lives were comparable with voriconazole.

In this study population, the pharmacokinetic parameters of voriconazole and its metabolites exhibited substantial interindividual variability, as reflected by the high coefficient of variation (Supplemental Table 6).

3.4. Exploratory analysis of voriconazole conjugates in human plasma

The comparison of GMs with 95% CI of voriconazole exposure between deconjugated and non-deconjugated samples (N = 14) is summarized in Supplemental Table 7 and Supplemental Fig. 3. As expected, the deconjugation process recovered higher plasma exposure ( $C_{\max}$ and AUC_0-τ) of voriconazole and its metabolites, as the conjugates were hydrolyzed by glucuronidase and converted back to voriconazole and metabolites. Without deconjugation process, 3 voriconazole conjugates were identified, with plasma exposure following the trend: voriconazole N-glucuronide > hydroxy voriconazole O-glucuronide > DiOH-voriconazole O-glucuronide.

3.5. Urine pharmacokinetics of voriconazole and its metabolites

The GM with 95% CI of the steady-state urine pharmacokinetic parameters of voriconazole and its metabolites for all 61 participants who completed the study are summarized in Supplemental Table 8. The GM amount excreted (A_e) during the steady-state dosing interval period (0-τ or 0—12 hours) after the administration of a 200-mg dose of voriconazole at steady state was approximately 2436, 26,024, 186, 157 and 4540 μg for voriconazole, voriconazole N-oxide, hydroxy voriconazole, methyl hydroxy voriconazole and DiOH-voriconazole, respectively. Accordingly, the percent dose recovered over 12 hours (0-τ) was 1.2%, 12%, 0.085%, 0.077%, and 2.1%, respectively. Therefore, voriconazole N-oxide accounted for the largest proportion of the dose excreted in the urine, followed by DiOH-voriconazole and voriconazole, while the dose excreted as hydroxy voriconazole and methyl hydroxy voriconazole was small (<0.1%). Voriconazole N-oxide also exhibited the largest CL_f (37 mL/min), while that of hydroxy voriconazole and methyl hydroxy voriconazole were below 0.5 mL/min. Accordingly, the urine metabolic ratio (N-oxide/voriconazole) was highest at 10 followed by DiOH-voriconazole at 1.8; this ratio was quite small (<0.1) for hydroxy voriconazole and methyl hydroxy voriconazole. Overall, voriconazole N-oxide was the dominant metabolite both in urine and plasma.

When compared with total apparent oral clearance of voriconazole which was 13,020 mL/h or 217 mL/min, the CL_r of voriconazole (204 mL/h or 3.4 mL/min) was over 60-fold lower (Supplemental Table 8). The CL_r of DiOH-voriconazole was highest (approximately 1452 mL/min) followed by methyl hydroxy voriconazole, which was 39 mL/min, voriconazole N-oxide (12 mL/min), and hydroxy voriconazole (5.6 mL/min).

3.6. Plasma and urine pharmacokinetics stratified by compliance status

Based on participant-oriented report, all 61 participants claimed that they completed their voriconazole regimen as instructed. According to pill count at the end of the study, no evidence was found regarding voriconazole treatment noncompliance. As described in the methods section, in addition to determining the steady-state pharmacokinetics of voriconazole and its metabolites, multiple trough concentrations were collected from each participant to assess compliance and confirm that steady state was achieved. The extended mean plasma concentration, with 95% CI, versus time profiles that include multiple trough concentrations determined throughout voriconazole treatment appears that steady-state conditions were achieved and maintained throughout voriconazole treatment (Fig. 3B). However, upon further inspection of the pharmacokinetics profiles of individual participants, we found that only 52 of 61 participants consistently achieved steady state (referred to as “completers”), while 9 participants did not (referred to as “noncompleters”) (Supplemental Fig. 4). The trough concentrations in noncompleters were well below 100 ng/mL, which was 5 times below the expected therapeutic range (500—6000 ng/mL) over multiple consecutive time points, suggesting possible nonadherence. While intraindividual variability may arise from nongenetic factors such as diet, prior studies indicate that high fat food reduces voriconazole exposure by only approximately 22%,⁴² which is unlikely to account for the marked differences observed between completers and noncompleters in our healthy cohort. Consequently, based on these observations and criteria, we compared pharmacokinetic parameters between completers and noncompleters. As shown in Supplemental Table 9, the half-life (t_1/2) of voriconazole and hydroxy voriconazole (M2) was shorter in noncompleters compared with completers. The exposure ( $C_{\max}$ and AUC_0-τ) values of voriconazole, voriconazole N-oxide and hydroxy voriconazole was also significantly lower in noncompleters compared with completers.

In addition, analysis of urine pharmacokinetics stratified by completion status (52 completers vs 9 noncompleters) revealed significantly lower amounts excreted in urine (A_e) and a lower percentage of the dose excreted (% dose) for voriconazole in noncompleters compared with completers. Noncompleters exhibited significantly higher urine metabolic ratios (A_e voriconazole N-oxide /A_e voriconazole), mainly attributed to the decrease in voriconazole urinary excretion (completers: 9.3, noncompleters: 17, P = .0064). Except for a marginal decrease in CL_r of DiOH-voriconazole (P = .046) in noncompleters, no meaningful differences were observed in any of the urine pharmacokinetic parameters for voriconazole metabolites (data not shown).

3.7. Associations of variants in voriconazole disposition genes with plasma and urine pharmacokinetics of voriconazole and metabolites

Analysis of genetic variants in CYP3A4 and CYP3A5 did not reveal any significant associations with voriconazole exposure (data not shown). Similarly, variants in CYP2C9 genes did not show any significant association with voriconazole exposure (data not shown). This lack of association may be due to small effect sizes, the limited sample size, and/or the minimal influence of the enzymes encoded by these genes on voriconazole metabolism in vivo, despite their involvement in vitro. As a result, analysis of associations data for these genetic variants are not presented in this paper in the interest of space.

Our initial pharmacokinetic analysis revealed a strong association between variants in the CYP2C19 gene and voriconazole exposure. Participants were genotyped for 3 CYP2C19 allele variants: *2, *3, and *17. Genotype data were available for 60 participants. Genotype information was missing in one participant. The individual genotypes were *17/*17 (N = 2), *1/*17 (N = 17), *1/*1 (N = 18), *2/*17 (N = 4), *1/*2 (N = 17), and *2/*2 (N = 2). Demographic characteristics for the 60 participants, stratified by the individual CYP2C19 genotypes are summarized in Supplemental Table 3. The distribution of the individual CYP2C19 genotypes across the cohort varied, with a roughly equal representation of females and males in the *1/*1, *2/*17, *1/*2, and *2/*2 genotype groups. Two individuals with the *17/*17 genotype were both White, and Black participants were predominantly represented in the *1/*2 genotype group. We first conducted a more detailed analysis of this gene using data from all 60 participants using individual CYP2C19 genotypes.

Analysis was repeated with consolidated CYP2C19 genotype-predicted phenotypes. Due to sample size considerations of the individual genotypes, data-driven CYP2C19 genotype-predicted phenotypes were consolidated into 3 metabolizer status: rapid metabolizers (RMs, N = 19), normal metabolizers (NMs, N = 22), and intermediate metabolizers (IMs, N = 19). The RM group included participants with *17/*17 (N = 2) and *1/*17 (N = 17) genotypes, the NM group comprised those with *1/*1 (N = 18) and *2/*17 (N = 4) genotypes, and the IM group consisted of individuals with *1/*2 (N = 17) and *2/*2 (N = 2) genotypes. Demographic characteristics were similar across the 3 genotype-predicted phenotypes (Supplemental Table 3). We found no major differences when associations were tested using the completers alone or together with noncompleters (data not shown). Thus, the full dataset data which included both compliant and noncompliant participants were used in this analysis.

To ensure robustness and clinical relevance, we conducted a secondary analysis using a CPIC guideline-aligned classification of CYP2C19 phenotypes for poor metabolizer.³¹ Given that poor metabolizers (PMs, *2/*2) are known to exhibit significantly higher voriconazole exposure due to markedly reduced enzyme activity, we separated them from the predicted IM group to evaluate whether this clinically meaningful distinction influenced our findings. Therefore, in this secondary analysis, the RM group included participants with *17/*17 (N = 2) and *1/*17 (N = 17) genotypes; the NM group comprised *1/*1 (N = 18) and *2/*17 (N = 4); the IM group included *1/*2 (N = 17); and the PM group included *2/*2 carriers (N = 2). This approach allowed us to compare results from the data-driven grouping with the CPIC-aligned classification.

Hence, in this study, we systematically evaluated the influence of CYP2C19 genetic variation on voriconazole pharmacokinetics using 3 analytical approaches: (1) assessment of individual CYP2C19 genotypes, (2) analysis of consolidated genotype-predicted phenotypes (categorized as RM, NM, and IM), and (3) evaluation of a 4-phenotype classification aligned with CPIC guidelines, wherein *2/*2 carriers were designated as a distinct PM group due to their markedly reduced metabolic capacity.

3.7.1. Associations with individual CYP2C19 genotypes

Associations of the individual CYP2C19 genotypes and steady-state plasma pharmacokinetics of voriconazole are summarized in Fig. 4. The average steady-state plasma concentration-versus-time profiles of voriconazole for each individual CYP2C19 genotype group is shown in Fig. 4A. Plasma concentrations of voriconazole were highest in *2/*2 genotype, following the rank order: *2/*2 > *1/*2 > *2/*17 ≈ *1/*1 ≈ *1/*17 > *17/*17. A more distinction among the genotypes was observed in the average plasma concentration metabolic ratios (voriconazole N-oxide/voriconazole) over time, with greater ratios in *17/*17 genotype, following decreasing rank order: *17/*17 << *1/*17 < *1/*1 < *2/*17 < *1/*2 < *2/*2 (Fig. 4B). The steady-state exposure of voriconazole for each individual CYP2C19 genotype is shown in Fig. 4. The C_max (Fig. 4C), C_min (Fig. 4D), and AUC (Fig. 4E) of voriconazole were highest in the *2/*2 genotype and lowest in the *17/*17 genotype, with AUC showing more than a 9-fold difference between these 2 groups (Fig. 4E). The weight-corrected apparent clearance was lowest in *2/*2 and highest in *17/*17 (data not shown). C_max, C_min, AUC, and weight-adjusted clearance of voriconazole showed statistically significant difference among the genotypes (P < .01; the Kruskal-Wallis test). Accordingly, the plasma C_max and AUC ratios (voriconazole N-oxide/voriconazole) displayed in Fig. 4, F and G, respectively, revealed that the lowest ratio was observed in *2/*2 and the highest in *17/*17, with statistically significant differences among the genotypes (both P < .0001). Notably, the *2/*17 genotype (N = 4) showed a phenotypic overlap with the *1/*1 genotype. Additionally, simple regression analysis revealed that CYP2C19 genotype significantly contributed to interindividual variability in voriconazole exposure (AUC), accounting for approximately 36% of the observed variance (adjusted R² = 0.36, P = .0007).

3.7.2. Associations with CYP2C19 genotype-predicted phenotypes

Given the small sample sizes of the *2/*2 (N = 2), *17/*17 (N = 2), and *2/*17 (N = 4) genotypes, a data-driven approach was employed to consolidate the genotype-predicted phenotypes based on similar pharmacokinetic trends observed in Fig. 4, as well as previously established genotype-phenotype relationships. The limited number of PMs (*2/*2, N = 2), the *2/*17 group (N = 4), and ultra-RMs (*17/*17, N = 2) were combined with the nearest phenotype showing similar pharmacokinetics to enhance statistical power for comparisons. As a result, the following CYP2C19 genotype-predicted phenotypes were established: RMs: N = 19 (includes *17/*17 [N = 2] and *1/*17 [N = 17]); NMs: N = 22 (includes *1/*1 [N = 18] and *2/*17 [N = 4]); IMs: N = 19 (includes *1/*2 [N = 17] and *2/*2 [N = 2]). All subsequent analyses on the associations between CYP2C19 genetic polymorphisms, pharmacokinetics of voriconazole and its metabolites (both plasma and urine), and adverse effects were conducted using the consolidated CYP2C19 genotype-predicted phenotypes (RM, NM, and IM).

Associations between genotype-predicted phenotype and steady-state voriconazole disposition are summarized in Fig. 5. The average steady-state voriconazole plasma concentrations and metabolic ratios (voriconazole N-oxide/voriconazole) over time for the CYP2C19 phenotypes (RM, NM, and IM) are shown in Fig. 5, A and B, respectively. Plasma concentrations of voriconazole were markedly higher in the IM phenotype compared with the NM and RM phenotypes, with the rank order: IM >>> NM > RM. Conversely, the metabolic ratio (voriconazole N-oxide/voriconazole) was lowest in IM, following the rank order: IM << NM << RM. Steady-state exposure parameters (C_max, C_min, AUC_0-τ) of voriconazole across the CYP2C19 phenotypes are presented in Fig. 5C-E, respectively. Details of the pharmacokinetic parameters stratified by CYP2C19 phenotype are listed in Table 3. Kruskal-Wallis test results indicated statistically significant differences among the 3 phenotype groups for the pharmacokinetic parameters including C_max (P < .01), AUC_0-τ (P < .001), and weight-adjusted apparent oral clearance (P < .001) (Fig. 5 and Table 3). Following Dunn’s post hoc test for multiple comparisons, C_max was significantly higher in IM versus NM (P < .05) and RM (P < .01) and AUC_0-τ was higher in IM compared with NM (P < .01) and RM (P < .001). Accordingly, the weight-adjusted apparent oral clearance was significantly lower in the IM phenotype compared with the NM and RM phenotypes (both P < .01). Specifically, C_max was 1.6- and 1.4-fold higher in IM than in RM and NM, respectively, and AUC_0-τ of voriconazole was approximately 2.1- and 1.9-fold higher in IM than in RM and NM, respectively. Consequently, weight-adjusted apparent oral clearance was significantly reduced by 50% and 45% in IM compared with RM and NM phenotypes, respectively. While the half-life of voriconazole was slightly increased in IM (10 hours) compared with RM (6.1 hours), this difference did not reach statistical significance (adjusted P = .077). No significant differences were observed in any of the voriconazole pharmacokinetic parameters between RM and NM phenotypes (Fig. 5 and Table 3). The plasma C_max and AUC ratios (voriconazole N-oxide/voriconazole) displayed in Fig. 5, F and G, respectively, revealed that the lowest ratio was observed in IM and the highest in RM, with statistically significant differences among the phenotypes (Kruskal-Wallis test both P < .0001). Following Dunn’s post hoc test for multiple comparisons, C_max metabolic ratios was significantly lower in IM than RM (P < .0001), while NM was lower than RM ratios (P < .01). AUC metabolic ratios were significantly lower in IM than RM (P < .0001) and NM (P < .01).

Table 3.

Steady-State Pharmacokinetic Parameters of Voriconazole (Vori) and Its Metabolites Stratified by the 3 CYP2C19 Genotype-Predicted Phenotypes

The CYP2C19 genotype-predicted phenotype were RM (N = 19), which contains *17/*17 (N = 2) and *1/*17 genotypes (N = 17); NM (N = 22) containing *1/*1 (N = 18) and *2/*17 genotypes (N = 4); and IM (19), which consists of *1/*2 (N = 17) and *2/*2 genotypes (N = 2). Data are presented as the GM, with 95% CI. The Kruskal-Wallis test was performed to compare differences among the multiple CYP2C19 phenotypes indicated by the overall P value followed by the Dunn’s multiple comparisons test to compare between groups. P values were bolded to indicate statistical significance.

PK Parameters	GM, with 95% CIs			P Values
PK Parameters	RM (N = 19)	NM (N = 22)	IM (N = 19)	Overall	RM vs NM	NM vs IM	RM vs IM
	Voriconazole
t_1/2 (h)	6.1 (4.4—8.3)	6.5 (4.9—8.6)	10 (7.1—14)	.048	>.99	.12	.077
C_max (ng/mL)	1613 (1340—1941)	1839 (1499—2257)	2608 (2221—3064)	.0013	.62	.043	.001
C_min (ng/mL)	404 (256—639)	304 (146—633)	1111 (822—1501)	.0008	>.99	.0033	.0027
AUC_0-τ (h*ng/mL)	9090 (6680—12,370)	10,038 (7666—13,143)	18,964 (15,727—22,867)	.0003	>.99	.0023	.0007
CL_F/Wt (mL/h/kg)	279 (206—377)	255 (194—334)	141 (119—166)	.0005	>.99	.0030	.0013
	Voriconazole N-oxide
t $1 ∕ 2$ (h)	21 (15—29)	23 (16—31)	27 (19—38)	.70	>.99	>.99	>.99
C_max (ng/mL)	4544 (4038—5113)	3481 (2967—4083)	2759 (1779—4277)	.0005	.014	.82	.0005
C_min (ng/mL)	3004 (2564—3520)	2432 (2059—2873)	2511 (2147—2937)	.079	.12	>.99	.19
AUC_0-τ (h*ng/mL)	41,229 (36,086—47,105)	31,559 (26,661—37,358)	32,386 (29,075—36,074)	.0046	.024	>.99	.0077
Metabolic ratio^a	4.5 (3.5—5.9)	3.1 (2.5—3.9)	1.8 (1.5—2.1)	<.0001	.23	.0033	<.0001
	Hydroxy voriconazole
t_1/2 (h)	4.8 (3.4—7)	5.8 (4.2—7.9)	15 (11—21)	<.0001	>.99	.0017	.0002
C_max (ng/mL)	88 (63—122)	84 (64—111)	105 (83—131)	.51	>.99	.75	>.99
C_min (ng/mL)	22 (13—36)	22 (14—34)	53 (38—73)	.0026	>.99	.0076	.0088
AUC_0-τ (h*ng/mL)	459 (324—652)	492 (363—667)	819 (627—1070)	.017	>.99	.039	.039
Metabolic ratio^a	0.06 (0.04—0.08)	0.05 (0.04—0.06) e	0.043 (0.033—0.056)	.36	>.99	>.99	.47
	Methyl hydroxy voriconazole
t_1/2 (h)	13 (8.1—20)	8.8 (6.1—13)	9.3 (7.1—12)	.41	.55	>.99	>.99
C_max (ng/mL)	11 (7.9—15)	6.5 (4.6—9.1)	6.3 (4.3—9.1)	.036	.070	>.99	.088
C_min (ng/mL)	4.7 (3.5—6.5)	2.3 (1.5—3.7)	2.6 (1.7—3.9)	.016	.026	>.99	.063
AUC_0-τ (h*ng/mL)	83 (62—112)	48 (35—66)	45 (31—68)	.015	.035	>.99	.04
Metabolic ratio^a	0.008 (0.005—0.01)	0.005 (0.003—0.008)	0.002 (0.002—0.004)	.004	.32	.20	.0027
	DiOH-voriconazole
t_1/2 (h)	9.3 (6.2—14)	12 (7.1—20)	9.5 (6.9—13)	.39	.78	.66	>.99
C_max (ng/mL)	8.2 (4.3—16)	5.7 (3.1—11)	4 (1.7—9.5)	.35	.83	>.99	.50
C_min (ng/mL)	4.6 (2.5—8.4)	2.7 (1.4—5.2)	2.1 (0.87—4.9)	.23	.55	>.99	.32
AUC_0-τ (h*ng/mL)	65 (33—128)	44 (23—84)	33 (14—79)	.40	.91	>.99	.59
Metabolic ratio^a	0.007 (0.004—0.01)	0.004 (0.002—0.01)	0.002 (0.0007—0.004)	.047	>.99	.35	.043

Open in a new tab

CL, clearance; PK, pharmacokinetics; t_1/2, terminal elimination half-life.

Metabolic ratios are obtained by dividing AUC_0-τ of the metabolite by AUC_0-τ of voriconazole.

Pharmacokinetic parameters of voriconazole metabolites and their respective metabolic ratios are also summarized in Table 3. A significant overall P value was found for voriconazole N-oxide C_max (P = .0005), AUC_0-τ (P = .0046), and metabolic ratios (AUC voriconazole N-oxide/voriconazole) (P < .0001). Post hoc testing revealed significantly higher voriconazole N-oxide C_max in RMs compared with NMs (P = .014) and IMs (P = .0005), whereas AUC_0-τ was significantly higher in RM than NM (P = .024) and IM (P = .0077). Accordingly, the metabolic ratios were significantly higher in RM than NM (P =.0033) and IM (P < .0001). The half-life of voriconazole N-oxide did not differ among the phenotype groups.

For hydroxy voriconazole (M2), the half-life was significantly longer in IM compared with NM and RM overall P value, P < .0001). The half-life of M2 was prolonged approximately 3.1- and 2.6-fold in IM (15 hours) compared with RM (4.8 hours) (P = .0002) and NM (5.8 hours) (P = .0017), respectively (Table 3). C_max and metabolic ratios of M2 did not show associations with CYP2C19 phenotypes, but C_min (P = .0026) and AUC_0-τ (P = .017) was significantly different among the phenotypes, with significantly higher exposure of C_min and AUC_0-τ IM compared with NM (P < .05) and RM (P < .05).

The pharmacokinetic parameters (C_max, C_min, AUC_0-τ and metabolic ratios of methyl hydroxy voriconazole (M3) differed significantly among the 3 phenotypes (P < .05). The exposure pattern of M3 appeared to be dependent on CYP2C19 activity, with the highest exposure observed in RM, followed by NM and IM (Table 3). The AUC of M3 was significantly higher in RM compared with NM or IM phenotypes (P < .05), and similar trends were observed for C_max, C_min, and metabolic ratios (Table 3).

Lastly, none of the pharmacokinetic parameters of DiOH-voriconazole showed an association with CYP2C19 phenotypes, except for the metabolic ratios, which were highest in RM (rank order: RM > NM > IM) (Table 3).

The urinary pharmacokinetics of voriconazole, stratified by the 3 CYP2C19 genotype-predicted phenotypes, are presented in Table 4. Significant increases in voriconazole urinary excretion (A_e), CL_r, and percentage of dose (% dose) were observed with reduced CYP2C19 enzyme activity, with overall P values ranging from .008 to < .0001. Specifically, the A_e and % dose in IMs were approximately 2.3- and 2.8-fold higher than in NM (P = .0057) and RM (P < .0001), respectively. The CLr was statistically significant among the 3 phenotypes (overall P value of .008), with greater CL_r in IM than NM and RM phenotypes (both P < .05) (Table 4).

Table 4.

Steady-State Urine Pharmacokinetic Parameters of Voriconazole and Its Metabolites Stratified by the 3 CYP2C19 Genotype-Predicted Phenotypes

The CYP2C19 genotype-predicted phenotype were RM (N = 19), which contains *17/*17 (N = 2) and *1/*17 genotypes (N = 17); NM (N = 22) containing *1/*1 (N = 18) and *2/*17 genotypes (N = 4); and IM (19), which consists of *1/*2 (N = 17) and *2/*2 genotypes (N = 2). Data are presented as the GM, with 95% CI. The Kruskal-Wallis test was performed to compare differences among the multiple CYP2C19 genotype groups (overall P value). Dunn's multiple comparisons test was used to compare between groups. P values were bolded to indicate statistical significance.

PK Parameters	RM (N = 19)	NM (N = 22)	IM (N = 19)	P Value
PK Parameters	RM (N = 19)	NM (N = 22)	IM (N = 19)	Overall	RM vs NM	NM vs IM	RM vs IM
Voriconazole
A_e (μg)	1608 (1231—2100)	2009 (1410—2863)	4539 (3354—6143)	<.0001	.62	.0057	<.0001
CL_r (mL/min)	2.4 (1.5—3.8)	3 (2.3—4)	5.7 (3.8—8.5)	.008	>.99	.028	.0151
% dose	0.8 (0.62—1.1)	1 (0.7—1.4)	2.3 (1.7—3.1)	<.0001	.62	.0057	<.0001
Voriconazole N-oxide
A_e (μg)	27,536 (23,347—32,477)	23,646 (18,691—29,915)	26,549 (18,834—37,422)	.54	>.99	.90	>.99
CL_r (mL/min)	12 (10—15)	12 (9.1—15)	13 (9.2—19)	.44	>.99	.94	.68
% dose	13 (11—16)	11 (8.9—14)	13 (9—18)	.54	>.99	.90	>.99
CL_f (mL/min)	42 (28—62)	35 (27—47)	33 (21—52)	.62	>.99	>.99	>.99
Urine MRs	16 (13—21)	11 (8.5—15)	5.6 (3.8—8.2)	<.0001	.18	.016	<.0001
Hydroxy voriconazole
A_e (μg)	194 (152—247)	160 (119—216)	173 (142—212)	.77	>.99	>.99	>.99
CL_r (mL/min)	6.2 (4.1—9.5)	5 (3.2—7.8)	4.9 (3.1—7.7)	.70	>.99	>.99	>.99
% dose	0.093 (0.073—0.12)	0.077 (0.057—0.1)	0.083 (0.068—0.1)	.77	>.99	>.99	>.99
CL_f (mL/min)	0.29 (0.19—0.45)	0.24 (0.18—0.34)	0.25 (0.17—0.38)	.63	>.99	>.99	>.99
Urine MRs	0.12 (0.085—0.16)	0.077 (0.056—0.1)	0.042 (0.029—0.061)	.0004	.13	.13	.0002
Methyl hydroxy voriconazole
A_e (μg)	197 (143—272)	138 (101—189)	159 (118—214)	.39	.58	>.99	.87
CL_r (mL/min)	50 (27—92)	45 (26—78)	43 (25—74)	.92	>.99	>.99	>.99
% dose	0.094 (0.068—0.13)	0.066 (0.048—0.091)	0.076 (0.056—0.10)	.39	.58	>.99	.87
CL_f (mL/min)	0.3 (0.21—0.43)	0.21 (0.14—0.3)	0.2 (0.13—0.3)	.37	>.99	>.99	.48
Urine MRs	0.12 (0.078—0.17)	0.066 (0.045—0.096)	0.033 (0.022—0.051)	.0002	.2073	.040	.0001
DiOH-voriconazole
A_e (μg)	4742 (3475—6471)	3551 (2345—5375)	5644 (4413—7219)	.26	>.99	.31	>.99
CL_r (mL/min)	2034 (712—5811)	1845 (831—4097)	1521 (698—3316)	.97	>.99	>.99	>.99
% dose	2.2 (1.6—3)	1.6 (1.1—2.5)	2.6 (2.0—3.3)	.26	>.99	.31	>.99
CL_f_vori (mL/min)^a	7.2 (4.8—11)	5.3 (3.6—7.8)	7.7 (5.2—12)	.44	>.99	>.99	.65
CL_f (mL/min)^b	2 (1.5—2.8)	1.7 (1.1—2.5)	3 (2.1—4.2)	.14	>.99	.16	.61
Urine MRs	2.7 (1.8—4.0)	1.6 (1.1—2.4)	1.2 (0.90—1.7)	.014	.17	.83	.012

Open in a new tab

A_e, amount excreted in urine (0-12 hours after dosing); CL, clearance; MR, metabolic ratio (A_e of metabolite/A_e of voriconazole) with corrected molecular weight; PK, pharmacokinetics.

CL_f for diOH-Vori was calculated from dividing amount of diOH-Vori excreted in urine by AUC_0-τ of voriconazole.

CL_f for diOH-Vori was calculated from dividing amount of diOH-Vori excreted in urine by the sum of AUC_0-τ of the primary metabolites: voriconazole N-oxide and hydroxyl voriconazole (M2 and M3).

There was no significant difference among the 3 phenotypes (RM, NM, and IM) for any of the voriconazole metabolites (N-oxide, M2, M3, and DiOH-voriconazole) with regard to A_e, CL_r, or % dose excreted (Table 4). This suggests that CYP2C19 genotype did not significantly impact the urinary pharmacokinetics of these voriconazole metabolites. However, the overall P value for the metabolic ratios indicates statistically significant differences among the phenotypes (range of P values .014 to < .0001). Generally, the ratios were significantly highest in RM and lowest in IM, with NM values falling in between. Post hoc analysis revealed that the urine metabolic ratios of voriconazole N-oxide and M3 were significantly lower in IM compared with RM (P < .0001 and P = .0001, respectively) and compared with NM (P = .016 and P = .04, respectively) (Table 4). For M2 and DiOH-voriconazole, significant differences were observed among the 3 phenotypes (P = .0004 and P = .014, respectively); metabolic ratios were lower in IM than RM phenotypes (P = .0002 and P = .011, respectively).

3.7.3. Associations with 4 CYP2C19 phenotypes

Recognizing the important clinical impact of CYP2C19 *2/*2 carriers (N = 2), these individuals were separated from the IM group and treated as a distinct PM group for comparison with RMs (*17/*17 and *1/*17, N = 19), NMs(*1/*1 and *2/*17, N = 22), and IMs (*1/*2, N = 17). This classification, aligned with CPIC guidelines, allowed us to evaluate whether separating PM from IM influenced the observed pharmacokinetic trends.

The same analysis conducted in the data-driven approach was repeated using this 4-phenotype classification. Associations between the 4 CYP2C19 phenotype groups and steady-state voriconazole disposition are summarized in Supplemental Fig. 5 and Supplemental Table 10. Overall trends were consistent with the data-driven approach: voriconazole C_min, AUC, and weight-corrected clearance differed significantly between the RM and IM groups, as well as between the NM and IM groups. As expected, voriconazole exposure increased and clearance decreased with decreasing CYP2C19 activity. Due to small sample size in the PM group (N = 2), significant differences in voriconazole disposition might not be observed with other metabolic groups. Similar patterns were observed for voriconazole metabolites as data-driven approach. However, the data-driven approach, which consolidates individuals based on observed pharmacokinetic distributions, may have greater statistical power to detect differences in metabolite disposition across CYP2C19 activity levels (Table 3 and Supplemental Table 10).

Voriconazole urine pharmacokinetics were also examined across these 4 phenotype groups (Supplemental Table 11). Similar to data-driven approach, overall significance was detected in voriconazole urinary excretion (A_e), CL_r, and percentage of dose (% dose) across 4 CYP2C19 phenotypes (RM, NM, IM, and PM), with overall P values ranging from .015 to .0002. However, due to the small sample size in the PM group (N = 2), the direct comparison between PM and other phenotype groups might be underpowered. For voriconazole metabolites, the overall P value for the urine metabolic ratios (MR) indicates statistically significant differences among the 4 phenotypes. Notably, urine MR was significantly higher in the RM group than in the PM group for voriconazole N-oxide, hydroxy voriconazole (M2) and methyl hydroxy voriconazole (M3) (Supplemental Table 11).

3.8. Associations of variants in the CYP2C19 gene with voriconazole AEs

Given the associations between CYP2C19 metabolic status and voriconazole disposition, and the potential for voriconazole-induced adverse effects (AEs) to be related to drug exposure, we explored whether any of the AEs were associated with CYP2C19 genotypes or phenotypes. However, no statistically significant differences were found among the phenotypes in the number of participants experiencing any AEs. Additionally, analysis of the impact of CYP2C19 polymorphisms on self-reported severity scores, onset, and peak times of AEs did not differ statistically among the 3 phenotypes (data not shown). Similarly, none of the laboratory values across the 3 phenotypic groups (RM, NM, IM) were statistically significant.

4. Discussion

We identified the sites of voriconazole hydroxylation (methyl and fluoropyrimidine groups) and the enzymes responsible and assessed their contributions to overall metabolism. We quantified voriconazole N-glucuronide in human plasma. Confirming and expanding on previous findings, we showed CYP2C19 genetic polymorphisms significantly affect voriconazole metabolism and pharmacokinetics, causing marked interindividual variability. We found that objective compliance measurements are more reliable than pill counts or self-reports in detecting individuals at risk for low drug exposure. We report over 70% of participants experienced mild visual and neurological/psychiatric effects during the loading dose; no change in indicators of liver toxicity. These findings clarify the multiple factors including metabolic pathways, genetics, compliance, and side effects that may influence voriconazole disposition and response.

This is the first study to pinpoint voriconazole’s exact hydroxylation sites and responsible enzymes. While Murayama et al. attributed methyl hydroxylation to CYP3A4,²¹ we found CYP3A4/5 drives fluoropyrimidine hydroxylation using an authentic standard unlike prior work that lacked one. In contrast, methyl hydroxylation, which represents a minor pathway probably due to steric hinderance, was found to be catalyzed primarily via CYP2C19 in contrast to earlier reports.²¹ Our in vitro data show N-oxidation by CYP2C19 accounts for approximately 95% of ${CL}_{int}$ , with hydroxylation contributing minimally. Overall, CYP2C19 is the main metabolic driver: it mediates methyl hydroxylation and dominates N-oxidation, while CYP3A4/5 catalyzes fluoropyrimidine hydroxylation.

Our steady-state urine and plasma pharmacokinetic data showing extensive metabolism, with large interindividual variability, broadly agree with previous studies in healthy volunteers.^3,19 Voriconazole N-oxide was identified as the major circulating metabolite in plasma, its clinical relevance limited as it does not contribute to the drug's antifungal activity. Moreover, among voriconazole metabolites, only voriconazole N-oxide has been implicated in its toxicity, yet its role in dermatological AEs remains uncertain.^29,43-45 While some in vitro studies suggest that voriconazole N-oxide and its photoproduct are phototoxic to cultured human keratinocytes,^43,45 spectroscopic evidence indicates that voriconazole N-oxide may not act as a photosensitizer.⁴⁴ N-oxide is also a predominant metabolite excreted in urine. These data along with our in vitro findings support that N-oxidation predominantly mediated by CYP2C19 is a major clearance mechanism for voriconazole, while the contribution of hydroxylation pathways is limited. In contrast, a single-dose study in healthy volunteers²⁶ and a steady-state pharmacokinetic study in cancer patients⁴¹ suggests that hydroxylation more than N-oxidation pathway may contribute significantly to voriconazole clearance. It is possible that metabolic patterns at single-dose studies may not accurately reflect steady-state metabolism because autoinhibition, particularly via CYP3A,⁴⁶ and metabolic saturation⁴⁷ occurs after repeated dosing with voriconazole. Moreover, inflammatory states, often present in cancer patients, can significantly suppress CYP2C19-mediated N-oxidation of voriconazole.⁴⁸ This is consistent with findings from Geist et al,⁴¹ who observed approximately 2-fold lower plasma concentration of voriconazole N-oxide than voriconazole in contrast to approximately 3-fold higher N-oxide found in healthy volunteers (present data and Liu et al⁴⁹). These observations underscore the complex interplay between study design, dose- and time-dependent enzyme dynamics, and disease-related physiological factors in shaping voriconazole metabolism. Further research is warranted to clarify these relationships and their implications for clinical practice.

We observed strong associations between CYP2C19 genetic variations and steady-state voriconazole exposure, aligning with findings from previous studies in both healthy volunteers^25,28 and patient populations.^50,51 Notably, our research represents the first formal steady-state pharmacokinetic study with intensive sampling to demonstrate over a 9-fold lower exposure of voriconazole in individuals with the *17/*17 genotype compared with the *2/*2 genotype. In a single-dose study involving healthy volunteers,²⁷ carriers of the *1/*17 genotype exhibited approximately 6.6-fold lower voriconazole exposure compared with those with the *2/*2 genotype. These data underscore that the *17 allele, particularly the *17/*17 genotype, may be at increased risk for subtherapeutic concentrations and potential antifungal treatment failure, necessitating higher or more frequent dosing to achieve therapeutic concentrations.¹⁴ In contrast, PMs, characterized by genotypes such as *2/*2, *2/*3 or *3/*3, may experience an increased risk for adverse effects, potentially requiring dose reductions or alternative antifungal therapies to minimize toxicity. The *17 allele frequency is notably high in certain populations, including White, African American, Hispanic, and Middle Eastern groups, while PM-defining alleles are prevalent in East Asian and Pacific Islander populations.^52-55 These racial and ethnic variations in allele frequencies may suggest the need of tailored pharmacogenetic approaches in diverse populations.

We observed that CYP2C19*2/*17 genotype exhibit voriconazole pharmacokinetic profiles similar to those with the *1/*1 genotype. Consistent with our findings, others have reported that the *2/*17 genotype-predicted phenotype is closer to *1/*1 than to *1/*2 using escitalopram⁵⁶ and pantoprazole⁵⁷ as substrates. The CPIC guideline currently classifies the *2/*17 genotype as a provisional IM assuming that CYP2C19*17 increased function allele may be unable to completely compensate for the no function CYP2C19*2 allele.³¹ Although our sample size is small (N = 4), the present data and the existing literature suggest that the *17 compensate the effect of null allele. However, more research with adequate sample size is needed to conclusively determine the genotype-predicted phenotype of diplotypes containing one null allele and the *17 allele combination.

The lack of significant associations between CYP3A4, CYP3A5, or CYP2C9 genetic polymorphisms and voriconazole exposure in this study aligns with previous findings showing similar findings.^16,58,59 Any associations observed are either not replicated or the effect sizes were generally quite small compared with the influence of CYP2C19 polymorphisms. Collectively, while CYP3A4, CYP3A5, CYP2C9 are involved in voriconazole metabolism in vitro, their contributions in the overall clearance of voriconazole in vivo appears to be limited. Currently available data reinforces the prevailing understanding that CYP2C19 is the primary enzyme influencing voriconazole metabolism and the importance of considering CYP2C19 genotype for personalized voriconazole dosing to optimize therapeutic outcomes.

Voriconazole N-glucuronidation via UGT1A4 was described in vitro,²⁴ but, to our knowledge, ours is the first to report voriconazole N-glucuronide in human plasma and to show that it exhibits the highest plasma exposure among all conjugates measured, indicating that in addition to oxidative reactions, direct N-glucuronidation of voriconazole represents another primary metabolic pathway. Exploratory analysis suggest that the plasma exposure of voriconazole glucuronide was higher in IM compared with NM of CYP2C19 (Supplemental Fig. 3), consistent with a previous report showing PM excrete a greater amount of voriconazole in urine than NM after deconjugation.²⁶ Similarly, higher exposure of hydroxy voriconazole in IM than NM (Table 3). Consequently, UGT1A4 and CYP3A mediated metabolism may serve as an alternative elimination pathway for individuals with reduced or absent CYP2C19 function. However, the exact contribution of voriconazole N-glucuronidation to the overall clearance of voriconazole and the influence of CYP2C19 genotypes on it needs further study.

Our findings underscore the limitations of relying solely on pill counts and self-reports for assessing treatment adherence in clinical trial. Direct measurement of drug concentrations provides a more accurate evaluation of adherence, which may be important for optimizing voriconazole treatment efficacy.³²

A distinctive feature of this study is the thorough documentation of safety laboratory results and adverse effects associated with voriconazole. Although VAEs and NAEs were quite frequent (in >70% of participants), which agree with findings from previous studies,³³ they were mild and mostly occurred during the loading doses and subsided during the maintenance dosing. Voriconazole-induced hepatotoxicity has been well-documented in patients with pre-existing medical conditions.^60-62 None of the markers of hepatotoxicity were outside the normal range in our study. Neither the adverse effects nor safety laboratory values were linked to CYP2C19 genetic polymorphisms, likely due to the short duration of voriconazole exposure in otherwise healthy participants. Clinical studies on the role of CYP2C19 genotype in predicting voriconazole adverse effects have been inconsistent.³¹

4.1. Limitations

Our data are from healthy participants and may not apply directly to critically ill patients with diverse demographics, clinical conditions, or concurrent treatments.⁶³ Voriconazole exposure is highly susceptible to DDIs, as coadministered medications may inhibit^64,65 or induce^9,25 its metabolism. These interactions may be further amplified in patients with specific CYP2C19 genotypes (eg, PM).^25,66 Additionally, hepatic impairment can reduce voriconazole clearance,⁶⁷ complicating the extrapolation of our results to clinical populations. Furthermore, we did not assess flavin-containing monooxygenase or UGT1A4 genetic variants, which could modestly influence metabolism. Despite these constraints, our findings offer valuable insights into voriconazole pharmacokinetics and pharmacodynamics, guiding future patientbased studies.

5. Conclusion

This study enhances understanding of voriconazole metabolic pathways, pharmacokinetics, acute AEs, and the genetic/nongenetic factors involved. Key findings include: (1) identification of specific hydroxylation sites and enzymes: CYP2C19 for N-oxidation and methyl hydroxylation, and CYP3A4/5 for fluoropyrimidine hydroxylation; (2) first quantification of voriconazole glucuronide in human plasma; (3) *17/*17 genotype carriers have approximately 9-fold lower exposure than *2/*2 individuals, confirming CYP2C19’s major role in drug clearance; (4) nonadherence significantly reduces exposure, underscoring the impact of patient compliance; (5) mild visual/neuropsychiatric symptoms occurred in over 70% of participants during loading doses, but resolving during maintenance, indicating treatment was well tolerated with no dropouts. Ultrarapid and poor CYP2C19 metabolizers may predict treatment failure or toxicity, respectively, but pre-emptive genotyping to guide dosing is not yet standard.^31,68,69 Even with CYP2C19 genotyping, exposure varies in critically ill patients due to age, weight, ethnicity, inflammation, liver function, comedications, comorbidities, and adherence.^31,63,70,71 Optimal therapy likely requires combining genotyping, rigorous therapeutic drug monitoring, and consideration of demographic and clinical factors.

Supplementary Material

NIHMS2129916-supplement-Supplementary_Material.docx^{(755.6KB, docx)}

This article has supplemental material available at dmd.aspetjournals.org.

Significance Statement:

This study elucidated genetic and nongenetic factors contributing to interindividual variability in voriconazole pharmacokinetics and adverse effects. In vitro analyses identified CYP2C19 as the primary enzyme mediating voriconazole metabolism, with CYP3A4/5 playing a secondary role. In vivo, CYP2C19 polymorphisms and noncompliance significantly influenced voriconazole exposure. Mild visual and neurological/psychiatric symptoms were common during the loading phase. These findings support incorporating CYP2C19 genotyping and adherence monitoring into voriconazole dosing strategies to optimize therapeutic outcomes.

Financial support

This work was supported by the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) [Grants R01-GM078501 and R35-GM145383] (to Z.D.). Yanting (Phoebe) Wu fellowship was supported by the Grant T32GM008425 (to Z.D.).

Abbreviations

AE: adverse event
AUC: area under the plasma concentration-versus-time curve
AUC_0-τ: area under the plasma concentration-versus-time curve from time 0 to the last observed concentration at 12 hours
CI: confidence interval
CL_f: formation clearance
${CL}_{int}$: intrinsic clearance
CL_r: renal clearance
C _min: minimum plasma concentration
CPIC: Clinical Pharmacogenetics Implementation Consortium
P450: cytochrome P450
DDI: drug-drug interaction
DiOH: dihydroxy
GM: geometric mean
GIAE: gastrointestinal adverse even
HIM: human intestinal microsome
HLM: human liver microsome
HPLC: high-performance liquid chromatography
IM: intermediate metabolizer
IS: internal standard
NAE: neurologic and psychiatric adverse event
NM: normal metabolize
OAE: other adverse event
RM: rapid metabolizer
UHPLC: ultra high performance liquid chromatography
VAE: visual adverse event

Footnotes

Conflict of interest

The authors declare no conflicts of interest.

CRediT authorship contribution statement

Yanting (Phoebe) Wu: Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review and editing, Visualization. Ayşe Gelal: Formal analysis, Investigation, Data curation, Writing – review and editing. Chisook Moon: Formal analysis, Investigation, Data curation, Writing – review and editing. Ingrid F. Metzger: Formal analysis, Investigation, Data curation, Writing – review and editing. Jessica B.L. Lu: Formal analysis, Investigation, Data curation. John T. Callaghan: Conceptualization, Methodology, Writing – review and editing, Supervision. Todd C. Skaar: Conceptualization, Methodology, Writing – review and editing, Supervision. Zeruesenay Desta: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resource, Data curation, Writing – original draft, Writing – review and editing, Visualization, Supervision, Project administration, Funding acquisition.

Data availability

The authors declare that all the summary data supporting the findings of this study are contained in within the paper and its supplemental material. Any individual data including raw data can be made available and will be shared upon request to the corresponding author (Zeruesenay Desta; zdesta@iu.edu).

References

1.Herbrecht R, Denning DW, Patterson TF, et al. Voriconazole versus amphotericin B for primary therapy of invasive aspergillosis. N Engl J Med. 2002;347 (6):408–415. 10.1056/NEJMoa020191 [DOI] [PubMed] [Google Scholar]
2.Scott LJ, Simpson D. Voriconazole: a review of its use in the management of invasive fungal infections. Drugs. 2007;67(2):269–298. 10.2165/00003495-200767020-00009 [DOI] [PubMed] [Google Scholar]
3.Theuretzbacher U, Ihle F, Derendorf H. Pharmacokinetic/pharmacodynamic profile of voriconazole. Clin Pharmacokinet. 2006;45(7):649–663. 10.2165/00003088-200645070-00002 [DOI] [PubMed] [Google Scholar]
4.Johnson LB, Kauffman CA. Voriconazole: a new triazole antifungal agent. Clin Infect Dis. 2003;36(5):630–637. 10.1086/367933 [DOI] [PubMed] [Google Scholar]
5.Dolton MJ, Mikus G, Weiss J, Ray JE, McLachlan AJ. Understanding variability with voriconazole using a population pharmacokinetic approach: implications for optimal dosing. J Antimicrob Chemother. 2014;69(6):1633–1641. 10.1093/jac/dku031 [DOI] [PubMed] [Google Scholar]
6.Owusu Obeng A, Egelund EF, Alsultan A, Peloquin CA, Johnson JA. CYP2C19 polymorphisms and therapeutic drug monitoring of voriconazole: are we ready for clinical implementation of pharmacogenomics? Pharmacotherapy. 2014;34(7):703–718. 10.1002/phar.1400 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Pascual A, Csajka C, Buclin T, et al. Challenging recommended oral and intravenous voriconazole doses for improved efficacy and safety: population pharmacokinetics-based analysis of adult patients with invasive fungal infections. Clin Infect Dis. 2012;55(3):381–390. 10.1093/cid/cis437 [DOI] [PubMed] [Google Scholar]
8.Troke PF, Hockey HP, Hope WW. Observational study of the clinical efficacy of voriconazole and its relationship to plasma concentrations in patients. Antimicrob Agents Chemother. 2011;55(10):4782–4788. 10.1128/AAC.01083-10 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Dolton MJ, Ray JE, Chen SC, Ng K, Pont LG, McLachlan AJ. Multicenter study of voriconazole pharmacokinetics and therapeutic drug monitoring. Antimicrob Agents Chemother. 2012;56(9):4793–4799. 10.1128/AAC.00626-12 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Jin H, Wang T, Falcione BA, et al. Trough concentration of voriconazole and its relationship with efficacy and safety: a systematic review and meta-analysis. J Antimicrob Chemother. 2016;71(7):1772–1785. 10.1093/jac/dkw045 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Kato H, Umemura T, Hagihara M, et al. Development of a therapeutic drugmonitoring algorithm for outpatients receiving voriconazole: a multicentre retrospective study. Br J Clin Pharmacol. 2024;90(5):1222–1230. 10.1111/bcp.16004 [DOI] [PubMed] [Google Scholar]
12.Pascual A, Calandra T, Bolay S, Buclin T, Bille J, Marchetti O. Voriconazole therapeutic drug monitoring in patients with invasive mycoses improves efficacy and safety outcomes. Clin Infect Dis. 2008;46(2):201–211. 10.1086/524669 [DOI] [PubMed] [Google Scholar]
13.Chen J, Wu Y, He Y, Feng X, Ren Y, Liu S. Combined effect of CYP2C19 genetic polymorphisms and C-reactive protein on voriconazole exposure and dosing in immunocompromised children. Front Pediatr. 2022;10:1–12:846411. 10.3389/fped.2022.846411 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Hamadeh IS, Klinker KP, Borgert SJ, et al. Impact of the CYP2C19 genotype on voriconazole exposure in adults with invasive fungal infections. Pharmacogenet Genomics. 2017;27(5):190–196. 10.1097/FPC.0000000000000277 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Schulz J, Kluwe F, Mikus G, Michelet R, Kloft C. Novel insights into the complex pharmacokinetics of voriconazole: a review of its metabolism. Drug Metab Rev. 2019;51(3):247–265. 10.1080/03602532.2019.1632888 [DOI] [PubMed] [Google Scholar]
16.Weiss J, Ten Hoevel MM, Burhenne J, et al. CYP2C19 genotype is a major factor contributing to the highly variable pharmacokinetics of voriconazole. J Clin Pharmacol. 2009;49(2):196–204. 10.1177/0091270008327537 [DOI] [PubMed] [Google Scholar]
17.VFEND. FDA Drug Label. Revised May 2019. Accessed July 1, 2025. https://www.accessdata.fda.gov/drugsatfda_docs/label/2019/021266s039,021267s050,021630s029lbl.pdf
18.Brunet M, van Gelder T, Åsberg A, et al. Therapeutic drug monitoring of tacrolimus-personalized therapy: second consensus report. Ther Drug Monit. 2019;41(3):261–307. 10.1097/FTD.0000000000000640 [DOI] [PubMed] [Google Scholar]
19.Roffey SJ, Cole S, Comby P, et al. The disposition of voriconazole in mouse, rat, rabbit, guinea pig, dog, and human. Drug Metab Dispos. 2003;31(6):731–741. 10.1124/dmd.31.6.731 [DOI] [PubMed] [Google Scholar]
20.Hyland R, Jones BC, Smith DA. Identification of the cytochrome P450 enzymes involved in the N-oxidation of voriconazole. Drug Metab Dispos. 2003;31(5):540–547. 10.1124/dmd.31.5.540 [DOI] [PubMed] [Google Scholar]
21.Murayama N, Imai N, Nakane T, Shimizu M, Yamazaki H. Roles of CYP3A4 and CYP2C19 in methyl hydroxylated and N-oxidized metabolite formation from voriconazole, a new anti-fungal agent, in human liver microsomes. Biochem Pharmacol. 2007;73(12):2020–2026. 10.1016/j.bcp.2007.03.012 [DOI] [PubMed] [Google Scholar]
22.Yanni SB, Annaert PP, Augustijns P, et al. Role of flavin-containing monooxygenase in oxidative metabolism of voriconazole by human liver microsomes. Drug Metab Dispos. 2008;36(6):1119–1125. 10.1124/dmd.107.019646 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Yanni SB, Annaert PP, Augustijns P, Ibrahim JG, Benjamin DK Jr, Thakker DR. In vitro hepatic metabolism explains higher clearance of voriconazole in children versus adults: role of CYP2C19 and flavin-containing monooxygenase 3. Drug Metab Dispos. 2010;38(1):25–31. 10.1124/dmd.109.029769 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Bourcier K, Hyland R, Kempshall S, et al. Investigation into UDP-glucuronosyltransferase (UGT) enzyme kinetics of imidazole- and triazole-containing antifungal drugs in human liver microsomes and recombinant UGT enzymes. Drug Metab Dispos. 2010;38(6):923–929. 10.1124/dmd.109.030676 [DOI] [PubMed] [Google Scholar]
25.Mikus G, Schowel V, Drzewinska M, et al. Potent cytochrome P450 2C19 genotype-related interaction between voriconazole and the cytochrome P450 3A4 inhibitor ritonavir. Clin Pharmacol Ther. 2006;80(2):126–135. 10.1016/j.clpt.2006.04.004 [DOI] [PubMed] [Google Scholar]
26.Scholz I, Oberwittler H, Riedel KD, et al. Pharmacokinetics, metabolism and bioavailability of the triazole antifungal agent voriconazole in relation to CYP2C19 genotype. Br J Clin Pharmacol. 2009;68(6):906–915. 10.1111/j.1365-2125.2009.03534.x [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Wang G, Lei HP, Li Z, et al. The CYP2C19 ultra-rapid metabolizer genotype influences the pharmacokinetics of voriconazole in healthy male volunteers. Eur J Clin Pharmacol. 2009;65(3):281–285. 10.1007/s00228-008-0574-7 [DOI] [PubMed] [Google Scholar]
28.Lee S, Kim BH, Nam WS, et al. Effect of CYP2C19 polymorphism on the pharmacokinetics of voriconazole after single and multiple doses in healthy volunteers. J Clin Pharmacol. 2012;52(2):195–203. 10.1177/0091270010395510 [DOI] [PubMed] [Google Scholar]
29.Mikus G, Scholz IM, Weiss J. Pharmacogenomics of the triazole antifungal agent voriconazole. Pharmacogenomics. 2011;12(6):861–872. 10.2217/pgs.11.18 [DOI] [PubMed] [Google Scholar]
30.Fan X, Zhang H, Wen Z, Zheng X, Yang Y, Yang J. Effects of CYP2C19, CYP2C9 and CYP3A4 gene polymorphisms on plasma voriconazole levels in Chinese pediatric patients. Pharmacogenet Genomics. 2022;32(4):152–158. 10.1097/FPC.0000000000000464 [DOI] [PubMed] [Google Scholar]
31.Moriyama B, Obeng AO, Barbarino J, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for CYP2C19 and voriconazole therapy. Clin Pharmacol Ther. 2017;102(1):45–51. 10.1002/cpt.583 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Hassan A, Burhenne J, Riedel KD, et al. Modulators of very low voriconazole concentrations in routine therapeutic drug monitoring. Ther Drug Monit. 2011;33(1):86–93. 10.1097/FTD.0b013e31820530cd [DOI] [PubMed] [Google Scholar]
33.Levine MT, Chandrasekar PH. Adverse effects of voriconazole: over a decade of use. Clin Transplant. 2016;30(11):1377–1386. 10.1111/ctr.12834 [DOI] [PubMed] [Google Scholar]
34.Rudd P, Byyny RL, Zachary V, et al. The natural history of medication compliance in a drug trial: limitations of pill counts. Clin Pharmacol Ther. 1989;46(2):169–176. 10.1038/clpt.1989.122 [DOI] [PubMed] [Google Scholar]
35.Bamfo NO, Lu JB, Desta Z. Stereoselective metabolism of bupropion to active metabolites in cellular fractions of human liver and intestine. Drug Metab Dispos. 2023;51(1):54–66. 10.1124/dmd.122.000867 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Vanstraelen K, Wauters J, De Loor H, et al. Protein-binding characteristics of voriconazole determined by high-throughput equilibrium dialysis. J Pharm Sci. 2014;103(8):2565–2570. 10.1002/jps.24064 [DOI] [PubMed] [Google Scholar]
37.Desta Z, Metzger IF, Thong N, et al. Inhibition of cytochrome P450 2B6 activity by voriconazole profiled using efavirenz disposition in healthy volunteers. Antimicrob Agents Chemother. 2016;60(11):6813–6822. 10.1128/AAC.01000-16 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Desta Z, Saussele T, Ward B, et al. Impact of CYP2B6 polymorphism on hepatic efavirenz metabolism in vitro. Pharmacogenomics. 2007;8(6):547–558. 10.2217/14622416.8.6.547 [DOI] [PubMed] [Google Scholar]
39.Michaud V, Kreutz Y, Skaar T, et al. Efavirenz-mediated induction of omeprazole metabolism is CYP2C19 genotype dependent. Pharmacogenomics J. 2014;14(2):151–159. 10.1038/tpj.2013.17 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Robarge JD, Metzger IF, Lu J, et al. Population pharmacokinetic modeling to estimate the contributions of genetic and nongenetic factors to efavirenz disposition. Antimicrob Agents Chemother. 2016;61(1):e01813–e01816. 10.1128/AAC.01813-16 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Geist MJ, Egerer G, Burhenne J, Riedel KD, Weiss J, Mikus G. Steady-state pharmacokinetics and metabolism of voriconazole in patients. J Antimicrob Chemother. 2013;68(11):2592–2599. 10.1093/jac/dkt229 [DOI] [PubMed] [Google Scholar]
42.Purkins L, Wood N, Kleinermans D, Greenhalgh K, Nichols D. Effect of food on the pharmacokinetics of multiple-dose oral voriconazole. Br J Clin Pharmacol. 2003;56(suppl 1):17–23. 10.1046/j.1365-2125.2003.01994.x [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Lee V, Gober MD, Bashir H, et al. Voriconazole enhances UV-induced DNA damage by inhibiting catalase and promoting oxidative stress. Exp Dermatol. 2020;29(1):29–38. 10.1111/exd.14038 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Morliere P, Silva AMS, Seixas RSGR, et al. Photosensitisation by voriconazole-N-oxide results from a sequence of solvent and pH-dependent photochemical and thermal reactions. J Photochem Photobiol B. 2018;187:1–9. 10.1016/j.jphotobiol.2018.07.023 [DOI] [PubMed] [Google Scholar]
45.Ona K, Oh DH. Voriconazole N-oxide and its ultraviolet B photoproduct sensitize keratinocytes to ultraviolet A. Br J Dermatol. 2015;173(3):751–759. 10.1111/bjd.13862 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Hohmann N, Kreuter R, Blank A, et al. Autoinhibitory properties of the parent but not of the N-oxide metabolite contribute to infusion rate-dependent voriconazole pharmacokinetics. Br J Clin Pharmacol. 2017;83(9):1954–1965. 10.1111/bcp.13297 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Yamada T, Mino Y, Yagi T, Naito T, Kawakami J. Saturated metabolism of voriconazole N-oxidation resulting in nonlinearity of pharmacokinetics of voriconazole at clinical doses. Biol Pharm Bull. 2015;38(10):1496–1503. 10.1248/bpb.b15-00241 [DOI] [PubMed] [Google Scholar]
48.Veringa A, Ter Avest M, Span LFR, et al. Voriconazole metabolism is influenced by severe inflammation: a prospective study. J Antimicrob Chemother. 2017;72 (1):261–267. 10.1093/jac/dkw349 [DOI] [PubMed] [Google Scholar]
49.Liu P, Foster G, LaBadie RR, Gutierrez MJ, Sharma A. Pharmacokinetic interaction between voriconazole and efavirenz at steady state in healthy male subjects. J Clin Pharmacol. 2008;48(1):73–84. 10.1177/0091270007309703 [DOI] [PubMed] [Google Scholar]
50.Miao Q, Tang JT, van Gelder T, et al. Correlation of CYP2C19 genotype with plasma voriconazole exposure in South-Western Chinese Han patients with invasive fungal infections. Medicine (Baltimore). 2019;98(3):e14137. 10.1097/MD.0000000000014137 [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Zhong X, Tong X, Ju Y, Du X, Li Y. Interpersonal factors in the pharmacokinetics and pharmacodynamics of voriconazole: are CYP2C19 genotypes enough for us to make a clinical decision? Curr Drug Metab. 2018;19(14):1152–1158. 10.2174/1389200219666171227200547 [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Dehbozorgi M, Kamalidehghan B, Hosseini I, et al. Prevalence of the CYP2C19*2 (681 G>A), *3 (636 G>A) and *17 (−806 C>T) alleles among an Iranian population of different ethnicities. Mol Med Rep. 2018;17(3): 4195–4202. 10.3892/mmr.2018.8377 [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Desta Z, Zhao X, Shin JG, Flockhart DA. Clinical significance of the cytochrome P450 2C19 genetic polymorphism. Clin Pharmacokinet. 2002;41(12):913–958. 10.2165/00003088-200241120-00002 [DOI] [PubMed] [Google Scholar]
54.Petrović J, Pešić V, Lauschke VM. Frequencies of clinically important CYP2C19 and CYP2D6 alleles are graded across Europe. Eur J Hum Genet. 2020;28(1): 88–94. 10.1038/s41431-019-0480-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Strom CM, Goos D, Crossley B, et al. Testing for variants in CYP2C19: population frequencies and testing experience in a clinical laboratory. Genet Med. 2012;14(1):95–100. 10.1038/gim.0b013e3182329870 [DOI] [PubMed] [Google Scholar]
56.Rudberg I, Mohebi B, Hermann M, Refsum H, Molden E. Impact of the ultrarapid CYP2C19*17 allele on serum concentration of escitalopram in psychiatric patients. Clin Pharmacol Ther. 2008;83(2):322–327. 10.1038/sj.clpt.6100291 [DOI] [PubMed] [Google Scholar]
57.Gawrońska-Szklarz B, Adamiak-Giera U, Wyska E, et al. CYP2C19 polymorphism affects single-dose pharmacokinetics of oral pantoprazole in healthy volunteers. Eur J Clin Pharmacol. 2012;68(9):1267–1274. 10.1007/s00228-012-1252-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
58.He HR, Sun JY, Ren XD, et al. Effects of CYP3A4 polymorphisms on the plasma concentration of voriconazole. Eur J Clin Microbiol Infect Dis. 2015;34(4): 811–819. 10.1007/s10096-014-2294-5 [DOI] [PubMed] [Google Scholar]
59.Liu S, Yao X, Tao J, et al. Impact of CYP2C19, CYP2C9, CYP3A4, and FMO3 genetic polymorphisms and sex on the pharmacokinetics of voriconazole after single and multiple doses in healthy Chinese subjects. J Clin Pharmacol. 2024;64(8):1030–1043. 10.1002/jcph.2440 [DOI] [PubMed] [Google Scholar]
60.Lo Re III V, Carbonari DM, Lewis JD, et al. Oral azole zntifungal medications and risk of acute liver injury, overall and by chronic liver disease status. Am J Med. 2016;129(3):283–291.e5. 10.1016/j.amjmed.2015.10.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Rakhshan A, Rahmati Kamel B, Saffaei A, Tavakoli-Ardakani M. Hepatotoxicity induced by azole antifungal agents: a review study. Iran J Pharm Res. 2023;22(1):e130336. 10.5812/ijpr-130336 [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Song Y, Jia MX, Yang G, et al. Association of CYP2C19 and UGT1A4 polymorphisms with voriconazole-induced liver injury. Per Med. 2020;17(1):15–22. 10.2217/pme-2019-0042 [DOI] [PubMed] [Google Scholar]
63.Li X, Hu Q, Xu T. Associated factors with voriconazole plasma concentration: a systematic review and meta-analysis. Front Pharmacol. 2024;15:1368274. 10.3389/fphar.2024.1368274 [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Boyd NK, Zoellner CL, Swancutt MA, Bhavan KP. Utilization of omeprazole to augment subtherapeutic voriconazole concentrations for treatment of Aspergillus infections. Antimicrob Agents Chemother. 2012;56(11):6001–6002. 10.1128/AAC.00700-12 [DOI] [PMC free article] [PubMed] [Google Scholar]
65.Mushtaq M, Fatima K, Ahmad A, Mohamed Ibrahim O, Faheem M, Shah Y. Pharmacokinetic interaction of voriconazole and clarithromycin in Pakistani healthy male volunteers: a single dose, randomized, crossover, open-label study. Front Pharmacol. 2023;14:1134803. 10.3389/fphar.2023.1134803 [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Zhu L, Brüggemann RJ, Uy J, et al. CYP2C19 Genotype-dependent pharmacokinetic drug interaction between voriconazole and ritonavir-boosted atazanavir in healthy subjects. J Clin Pharmacol. 2017;57(2):235–246. 10.1002/jcph.798 [DOI] [PubMed] [Google Scholar]
67.Yamada T, Imai S, Koshizuka Y, et al. Necessity for a significant maintenance dosage reduction of voriconazole in patients with severe liver cirrhosis (Child-Pugh Class C). Biol Pharm Bull. 2018;41(7):1112–1118. 10.1248/bpb.b18-00164 [DOI] [PubMed] [Google Scholar]
68.Lee J, Ng P, Hamandi B, Husain S, Lefebvre MJ, Battistella M. Effect of therapeutic drug monitoring and cytochrome P450 2C19 genotyping on clinical outcomes of voriconazole: a systematic review. Ann Pharmacother. 2021;55(4):509–529. 10.1177/1060028020948174 [DOI] [PubMed] [Google Scholar]
69.Zhao YC, Lin XB, Zhang BK, et al. Predictors of adverse events and determinants of the voriconazole trough concentration in kidney transplantation recipients. Clin Transl Sci. 2021;14(2):702–711. 10.1111/cts.12932 [DOI] [PMC free article] [PubMed] [Google Scholar]
70.Hamada Y, Tokimatsu I, Mikamo H, et al. Practice guidelines for therapeutic drug monitoring of voriconazole: a consensus review of the Japanese Society of Chemotherapy and the Japanese Society of Therapeutic Drug Monitoring. J Infect Chemother. 2013;19(3):381–392. 10.1007/s10156-013-0607-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
71.Pappas PG, Kauffman CA, Andes DR, et al. Clinical practice guideline for the management of candidiasis: 2016 update by the Infectious Diseases Society of America. Clin Infect Dis. 2016;62(4):e1–e50. 10.1093/cid/civ933 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material

NIHMS2129916-supplement-Supplementary_Material.docx^{(755.6KB, docx)}

Data Availability Statement

[R1] 1.Herbrecht R, Denning DW, Patterson TF, et al. Voriconazole versus amphotericin B for primary therapy of invasive aspergillosis. N Engl J Med. 2002;347 (6):408–415. 10.1056/NEJMoa020191 [DOI] [PubMed] [Google Scholar]

[R2] 2.Scott LJ, Simpson D. Voriconazole: a review of its use in the management of invasive fungal infections. Drugs. 2007;67(2):269–298. 10.2165/00003495-200767020-00009 [DOI] [PubMed] [Google Scholar]

[R3] 3.Theuretzbacher U, Ihle F, Derendorf H. Pharmacokinetic/pharmacodynamic profile of voriconazole. Clin Pharmacokinet. 2006;45(7):649–663. 10.2165/00003088-200645070-00002 [DOI] [PubMed] [Google Scholar]

[R4] 4.Johnson LB, Kauffman CA. Voriconazole: a new triazole antifungal agent. Clin Infect Dis. 2003;36(5):630–637. 10.1086/367933 [DOI] [PubMed] [Google Scholar]

[R5] 5.Dolton MJ, Mikus G, Weiss J, Ray JE, McLachlan AJ. Understanding variability with voriconazole using a population pharmacokinetic approach: implications for optimal dosing. J Antimicrob Chemother. 2014;69(6):1633–1641. 10.1093/jac/dku031 [DOI] [PubMed] [Google Scholar]

[R6] 6.Owusu Obeng A, Egelund EF, Alsultan A, Peloquin CA, Johnson JA. CYP2C19 polymorphisms and therapeutic drug monitoring of voriconazole: are we ready for clinical implementation of pharmacogenomics? Pharmacotherapy. 2014;34(7):703–718. 10.1002/phar.1400 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R7] 7.Pascual A, Csajka C, Buclin T, et al. Challenging recommended oral and intravenous voriconazole doses for improved efficacy and safety: population pharmacokinetics-based analysis of adult patients with invasive fungal infections. Clin Infect Dis. 2012;55(3):381–390. 10.1093/cid/cis437 [DOI] [PubMed] [Google Scholar]

[R8] 8.Troke PF, Hockey HP, Hope WW. Observational study of the clinical efficacy of voriconazole and its relationship to plasma concentrations in patients. Antimicrob Agents Chemother. 2011;55(10):4782–4788. 10.1128/AAC.01083-10 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] 9.Dolton MJ, Ray JE, Chen SC, Ng K, Pont LG, McLachlan AJ. Multicenter study of voriconazole pharmacokinetics and therapeutic drug monitoring. Antimicrob Agents Chemother. 2012;56(9):4793–4799. 10.1128/AAC.00626-12 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] 10.Jin H, Wang T, Falcione BA, et al. Trough concentration of voriconazole and its relationship with efficacy and safety: a systematic review and meta-analysis. J Antimicrob Chemother. 2016;71(7):1772–1785. 10.1093/jac/dkw045 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] 11.Kato H, Umemura T, Hagihara M, et al. Development of a therapeutic drugmonitoring algorithm for outpatients receiving voriconazole: a multicentre retrospective study. Br J Clin Pharmacol. 2024;90(5):1222–1230. 10.1111/bcp.16004 [DOI] [PubMed] [Google Scholar]

[R12] 12.Pascual A, Calandra T, Bolay S, Buclin T, Bille J, Marchetti O. Voriconazole therapeutic drug monitoring in patients with invasive mycoses improves efficacy and safety outcomes. Clin Infect Dis. 2008;46(2):201–211. 10.1086/524669 [DOI] [PubMed] [Google Scholar]

[R13] 13.Chen J, Wu Y, He Y, Feng X, Ren Y, Liu S. Combined effect of CYP2C19 genetic polymorphisms and C-reactive protein on voriconazole exposure and dosing in immunocompromised children. Front Pediatr. 2022;10:1–12:846411. 10.3389/fped.2022.846411 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Hamadeh IS, Klinker KP, Borgert SJ, et al. Impact of the CYP2C19 genotype on voriconazole exposure in adults with invasive fungal infections. Pharmacogenet Genomics. 2017;27(5):190–196. 10.1097/FPC.0000000000000277 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R15] 15.Schulz J, Kluwe F, Mikus G, Michelet R, Kloft C. Novel insights into the complex pharmacokinetics of voriconazole: a review of its metabolism. Drug Metab Rev. 2019;51(3):247–265. 10.1080/03602532.2019.1632888 [DOI] [PubMed] [Google Scholar]

[R16] 16.Weiss J, Ten Hoevel MM, Burhenne J, et al. CYP2C19 genotype is a major factor contributing to the highly variable pharmacokinetics of voriconazole. J Clin Pharmacol. 2009;49(2):196–204. 10.1177/0091270008327537 [DOI] [PubMed] [Google Scholar]

[R17] 17.VFEND. FDA Drug Label. Revised May 2019. Accessed July 1, 2025. https://www.accessdata.fda.gov/drugsatfda_docs/label/2019/021266s039,021267s050,021630s029lbl.pdf

[R18] 18.Brunet M, van Gelder T, Åsberg A, et al. Therapeutic drug monitoring of tacrolimus-personalized therapy: second consensus report. Ther Drug Monit. 2019;41(3):261–307. 10.1097/FTD.0000000000000640 [DOI] [PubMed] [Google Scholar]

[R19] 19.Roffey SJ, Cole S, Comby P, et al. The disposition of voriconazole in mouse, rat, rabbit, guinea pig, dog, and human. Drug Metab Dispos. 2003;31(6):731–741. 10.1124/dmd.31.6.731 [DOI] [PubMed] [Google Scholar]

[R20] 20.Hyland R, Jones BC, Smith DA. Identification of the cytochrome P450 enzymes involved in the N-oxidation of voriconazole. Drug Metab Dispos. 2003;31(5):540–547. 10.1124/dmd.31.5.540 [DOI] [PubMed] [Google Scholar]

[R21] 21.Murayama N, Imai N, Nakane T, Shimizu M, Yamazaki H. Roles of CYP3A4 and CYP2C19 in methyl hydroxylated and N-oxidized metabolite formation from voriconazole, a new anti-fungal agent, in human liver microsomes. Biochem Pharmacol. 2007;73(12):2020–2026. 10.1016/j.bcp.2007.03.012 [DOI] [PubMed] [Google Scholar]

[R22] 22.Yanni SB, Annaert PP, Augustijns P, et al. Role of flavin-containing monooxygenase in oxidative metabolism of voriconazole by human liver microsomes. Drug Metab Dispos. 2008;36(6):1119–1125. 10.1124/dmd.107.019646 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R23] 23.Yanni SB, Annaert PP, Augustijns P, Ibrahim JG, Benjamin DK Jr, Thakker DR. In vitro hepatic metabolism explains higher clearance of voriconazole in children versus adults: role of CYP2C19 and flavin-containing monooxygenase 3. Drug Metab Dispos. 2010;38(1):25–31. 10.1124/dmd.109.029769 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R24] 24.Bourcier K, Hyland R, Kempshall S, et al. Investigation into UDP-glucuronosyltransferase (UGT) enzyme kinetics of imidazole- and triazole-containing antifungal drugs in human liver microsomes and recombinant UGT enzymes. Drug Metab Dispos. 2010;38(6):923–929. 10.1124/dmd.109.030676 [DOI] [PubMed] [Google Scholar]

[R25] 25.Mikus G, Schowel V, Drzewinska M, et al. Potent cytochrome P450 2C19 genotype-related interaction between voriconazole and the cytochrome P450 3A4 inhibitor ritonavir. Clin Pharmacol Ther. 2006;80(2):126–135. 10.1016/j.clpt.2006.04.004 [DOI] [PubMed] [Google Scholar]

[R26] 26.Scholz I, Oberwittler H, Riedel KD, et al. Pharmacokinetics, metabolism and bioavailability of the triazole antifungal agent voriconazole in relation to CYP2C19 genotype. Br J Clin Pharmacol. 2009;68(6):906–915. 10.1111/j.1365-2125.2009.03534.x [DOI] [PMC free article] [PubMed] [Google Scholar]

[R27] 27.Wang G, Lei HP, Li Z, et al. The CYP2C19 ultra-rapid metabolizer genotype influences the pharmacokinetics of voriconazole in healthy male volunteers. Eur J Clin Pharmacol. 2009;65(3):281–285. 10.1007/s00228-008-0574-7 [DOI] [PubMed] [Google Scholar]

[R28] 28.Lee S, Kim BH, Nam WS, et al. Effect of CYP2C19 polymorphism on the pharmacokinetics of voriconazole after single and multiple doses in healthy volunteers. J Clin Pharmacol. 2012;52(2):195–203. 10.1177/0091270010395510 [DOI] [PubMed] [Google Scholar]

[R29] 29.Mikus G, Scholz IM, Weiss J. Pharmacogenomics of the triazole antifungal agent voriconazole. Pharmacogenomics. 2011;12(6):861–872. 10.2217/pgs.11.18 [DOI] [PubMed] [Google Scholar]

[R30] 30.Fan X, Zhang H, Wen Z, Zheng X, Yang Y, Yang J. Effects of CYP2C19, CYP2C9 and CYP3A4 gene polymorphisms on plasma voriconazole levels in Chinese pediatric patients. Pharmacogenet Genomics. 2022;32(4):152–158. 10.1097/FPC.0000000000000464 [DOI] [PubMed] [Google Scholar]

[R31] 31.Moriyama B, Obeng AO, Barbarino J, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for CYP2C19 and voriconazole therapy. Clin Pharmacol Ther. 2017;102(1):45–51. 10.1002/cpt.583 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R32] 32.Hassan A, Burhenne J, Riedel KD, et al. Modulators of very low voriconazole concentrations in routine therapeutic drug monitoring. Ther Drug Monit. 2011;33(1):86–93. 10.1097/FTD.0b013e31820530cd [DOI] [PubMed] [Google Scholar]

[R33] 33.Levine MT, Chandrasekar PH. Adverse effects of voriconazole: over a decade of use. Clin Transplant. 2016;30(11):1377–1386. 10.1111/ctr.12834 [DOI] [PubMed] [Google Scholar]

[R34] 34.Rudd P, Byyny RL, Zachary V, et al. The natural history of medication compliance in a drug trial: limitations of pill counts. Clin Pharmacol Ther. 1989;46(2):169–176. 10.1038/clpt.1989.122 [DOI] [PubMed] [Google Scholar]

[R35] 35.Bamfo NO, Lu JB, Desta Z. Stereoselective metabolism of bupropion to active metabolites in cellular fractions of human liver and intestine. Drug Metab Dispos. 2023;51(1):54–66. 10.1124/dmd.122.000867 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R36] 36.Vanstraelen K, Wauters J, De Loor H, et al. Protein-binding characteristics of voriconazole determined by high-throughput equilibrium dialysis. J Pharm Sci. 2014;103(8):2565–2570. 10.1002/jps.24064 [DOI] [PubMed] [Google Scholar]

[R37] 37.Desta Z, Metzger IF, Thong N, et al. Inhibition of cytochrome P450 2B6 activity by voriconazole profiled using efavirenz disposition in healthy volunteers. Antimicrob Agents Chemother. 2016;60(11):6813–6822. 10.1128/AAC.01000-16 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R38] 38.Desta Z, Saussele T, Ward B, et al. Impact of CYP2B6 polymorphism on hepatic efavirenz metabolism in vitro. Pharmacogenomics. 2007;8(6):547–558. 10.2217/14622416.8.6.547 [DOI] [PubMed] [Google Scholar]

[R39] 39.Michaud V, Kreutz Y, Skaar T, et al. Efavirenz-mediated induction of omeprazole metabolism is CYP2C19 genotype dependent. Pharmacogenomics J. 2014;14(2):151–159. 10.1038/tpj.2013.17 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R40] 40.Robarge JD, Metzger IF, Lu J, et al. Population pharmacokinetic modeling to estimate the contributions of genetic and nongenetic factors to efavirenz disposition. Antimicrob Agents Chemother. 2016;61(1):e01813–e01816. 10.1128/AAC.01813-16 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R41] 41.Geist MJ, Egerer G, Burhenne J, Riedel KD, Weiss J, Mikus G. Steady-state pharmacokinetics and metabolism of voriconazole in patients. J Antimicrob Chemother. 2013;68(11):2592–2599. 10.1093/jac/dkt229 [DOI] [PubMed] [Google Scholar]

[R42] 42.Purkins L, Wood N, Kleinermans D, Greenhalgh K, Nichols D. Effect of food on the pharmacokinetics of multiple-dose oral voriconazole. Br J Clin Pharmacol. 2003;56(suppl 1):17–23. 10.1046/j.1365-2125.2003.01994.x [DOI] [PMC free article] [PubMed] [Google Scholar]

[R43] 43.Lee V, Gober MD, Bashir H, et al. Voriconazole enhances UV-induced DNA damage by inhibiting catalase and promoting oxidative stress. Exp Dermatol. 2020;29(1):29–38. 10.1111/exd.14038 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R44] 44.Morliere P, Silva AMS, Seixas RSGR, et al. Photosensitisation by voriconazole-N-oxide results from a sequence of solvent and pH-dependent photochemical and thermal reactions. J Photochem Photobiol B. 2018;187:1–9. 10.1016/j.jphotobiol.2018.07.023 [DOI] [PubMed] [Google Scholar]

[R45] 45.Ona K, Oh DH. Voriconazole N-oxide and its ultraviolet B photoproduct sensitize keratinocytes to ultraviolet A. Br J Dermatol. 2015;173(3):751–759. 10.1111/bjd.13862 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R46] 46.Hohmann N, Kreuter R, Blank A, et al. Autoinhibitory properties of the parent but not of the N-oxide metabolite contribute to infusion rate-dependent voriconazole pharmacokinetics. Br J Clin Pharmacol. 2017;83(9):1954–1965. 10.1111/bcp.13297 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R47] 47.Yamada T, Mino Y, Yagi T, Naito T, Kawakami J. Saturated metabolism of voriconazole N-oxidation resulting in nonlinearity of pharmacokinetics of voriconazole at clinical doses. Biol Pharm Bull. 2015;38(10):1496–1503. 10.1248/bpb.b15-00241 [DOI] [PubMed] [Google Scholar]

[R48] 48.Veringa A, Ter Avest M, Span LFR, et al. Voriconazole metabolism is influenced by severe inflammation: a prospective study. J Antimicrob Chemother. 2017;72 (1):261–267. 10.1093/jac/dkw349 [DOI] [PubMed] [Google Scholar]

[R49] 49.Liu P, Foster G, LaBadie RR, Gutierrez MJ, Sharma A. Pharmacokinetic interaction between voriconazole and efavirenz at steady state in healthy male subjects. J Clin Pharmacol. 2008;48(1):73–84. 10.1177/0091270007309703 [DOI] [PubMed] [Google Scholar]

[R50] 50.Miao Q, Tang JT, van Gelder T, et al. Correlation of CYP2C19 genotype with plasma voriconazole exposure in South-Western Chinese Han patients with invasive fungal infections. Medicine (Baltimore). 2019;98(3):e14137. 10.1097/MD.0000000000014137 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R51] 51.Zhong X, Tong X, Ju Y, Du X, Li Y. Interpersonal factors in the pharmacokinetics and pharmacodynamics of voriconazole: are CYP2C19 genotypes enough for us to make a clinical decision? Curr Drug Metab. 2018;19(14):1152–1158. 10.2174/1389200219666171227200547 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R52] 52.Dehbozorgi M, Kamalidehghan B, Hosseini I, et al. Prevalence of the CYP2C19*2 (681 G>A), *3 (636 G>A) and *17 (−806 C>T) alleles among an Iranian population of different ethnicities. Mol Med Rep. 2018;17(3): 4195–4202. 10.3892/mmr.2018.8377 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R53] 53.Desta Z, Zhao X, Shin JG, Flockhart DA. Clinical significance of the cytochrome P450 2C19 genetic polymorphism. Clin Pharmacokinet. 2002;41(12):913–958. 10.2165/00003088-200241120-00002 [DOI] [PubMed] [Google Scholar]

[R54] 54.Petrović J, Pešić V, Lauschke VM. Frequencies of clinically important CYP2C19 and CYP2D6 alleles are graded across Europe. Eur J Hum Genet. 2020;28(1): 88–94. 10.1038/s41431-019-0480-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R55] 55.Strom CM, Goos D, Crossley B, et al. Testing for variants in CYP2C19: population frequencies and testing experience in a clinical laboratory. Genet Med. 2012;14(1):95–100. 10.1038/gim.0b013e3182329870 [DOI] [PubMed] [Google Scholar]

[R56] 56.Rudberg I, Mohebi B, Hermann M, Refsum H, Molden E. Impact of the ultrarapid CYP2C19*17 allele on serum concentration of escitalopram in psychiatric patients. Clin Pharmacol Ther. 2008;83(2):322–327. 10.1038/sj.clpt.6100291 [DOI] [PubMed] [Google Scholar]

[R57] 57.Gawrońska-Szklarz B, Adamiak-Giera U, Wyska E, et al. CYP2C19 polymorphism affects single-dose pharmacokinetics of oral pantoprazole in healthy volunteers. Eur J Clin Pharmacol. 2012;68(9):1267–1274. 10.1007/s00228-012-1252-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R58] 58.He HR, Sun JY, Ren XD, et al. Effects of CYP3A4 polymorphisms on the plasma concentration of voriconazole. Eur J Clin Microbiol Infect Dis. 2015;34(4): 811–819. 10.1007/s10096-014-2294-5 [DOI] [PubMed] [Google Scholar]

[R59] 59.Liu S, Yao X, Tao J, et al. Impact of CYP2C19, CYP2C9, CYP3A4, and FMO3 genetic polymorphisms and sex on the pharmacokinetics of voriconazole after single and multiple doses in healthy Chinese subjects. J Clin Pharmacol. 2024;64(8):1030–1043. 10.1002/jcph.2440 [DOI] [PubMed] [Google Scholar]

[R60] 60.Lo Re III V, Carbonari DM, Lewis JD, et al. Oral azole zntifungal medications and risk of acute liver injury, overall and by chronic liver disease status. Am J Med. 2016;129(3):283–291.e5. 10.1016/j.amjmed.2015.10.029 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R61] 61.Rakhshan A, Rahmati Kamel B, Saffaei A, Tavakoli-Ardakani M. Hepatotoxicity induced by azole antifungal agents: a review study. Iran J Pharm Res. 2023;22(1):e130336. 10.5812/ijpr-130336 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R62] 62.Song Y, Jia MX, Yang G, et al. Association of CYP2C19 and UGT1A4 polymorphisms with voriconazole-induced liver injury. Per Med. 2020;17(1):15–22. 10.2217/pme-2019-0042 [DOI] [PubMed] [Google Scholar]

[R63] 63.Li X, Hu Q, Xu T. Associated factors with voriconazole plasma concentration: a systematic review and meta-analysis. Front Pharmacol. 2024;15:1368274. 10.3389/fphar.2024.1368274 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R64] 64.Boyd NK, Zoellner CL, Swancutt MA, Bhavan KP. Utilization of omeprazole to augment subtherapeutic voriconazole concentrations for treatment of Aspergillus infections. Antimicrob Agents Chemother. 2012;56(11):6001–6002. 10.1128/AAC.00700-12 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R65] 65.Mushtaq M, Fatima K, Ahmad A, Mohamed Ibrahim O, Faheem M, Shah Y. Pharmacokinetic interaction of voriconazole and clarithromycin in Pakistani healthy male volunteers: a single dose, randomized, crossover, open-label study. Front Pharmacol. 2023;14:1134803. 10.3389/fphar.2023.1134803 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R66] 66.Zhu L, Brüggemann RJ, Uy J, et al. CYP2C19 Genotype-dependent pharmacokinetic drug interaction between voriconazole and ritonavir-boosted atazanavir in healthy subjects. J Clin Pharmacol. 2017;57(2):235–246. 10.1002/jcph.798 [DOI] [PubMed] [Google Scholar]

[R67] 67.Yamada T, Imai S, Koshizuka Y, et al. Necessity for a significant maintenance dosage reduction of voriconazole in patients with severe liver cirrhosis (Child-Pugh Class C). Biol Pharm Bull. 2018;41(7):1112–1118. 10.1248/bpb.b18-00164 [DOI] [PubMed] [Google Scholar]

[R68] 68.Lee J, Ng P, Hamandi B, Husain S, Lefebvre MJ, Battistella M. Effect of therapeutic drug monitoring and cytochrome P450 2C19 genotyping on clinical outcomes of voriconazole: a systematic review. Ann Pharmacother. 2021;55(4):509–529. 10.1177/1060028020948174 [DOI] [PubMed] [Google Scholar]

[R69] 69.Zhao YC, Lin XB, Zhang BK, et al. Predictors of adverse events and determinants of the voriconazole trough concentration in kidney transplantation recipients. Clin Transl Sci. 2021;14(2):702–711. 10.1111/cts.12932 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R70] 70.Hamada Y, Tokimatsu I, Mikamo H, et al. Practice guidelines for therapeutic drug monitoring of voriconazole: a consensus review of the Japanese Society of Chemotherapy and the Japanese Society of Therapeutic Drug Monitoring. J Infect Chemother. 2013;19(3):381–392. 10.1007/s10156-013-0607-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R71] 71.Pappas PG, Kauffman CA, Andes DR, et al. Clinical practice guideline for the management of candidiasis: 2016 update by the Infectious Diseases Society of America. Clin Infect Dis. 2016;62(4):e1–e50. 10.1093/cid/civ933 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Pharmacogenetics of steady-state metabolism, pharmacokinetics, and adverse effects of voriconazole in healthy participants

Yanting (Phoebe) Wu

Ayşe Gelal

Chisook Moon

Ingrid F Metzger

Jessica BL Lu

John T Callaghan

Todd C Skaar

Zeruesenay Desta

Abstract

1. Introduction

2. Materials and methods

2.1. Chemicals

2.2. In vitro studies

2.2.1. Incubation conditions

2.3. Clinical study

2.3.1. Study participants

2.3.2. Study design

2.3.3. Voriconazole safety assessments

2.4. Analysis of voriconazole and metabolites in plasma and urine

2.5. Analysis of free and conjugated voriconazole and metabolites in plasma

2.6. DNA genotyping

2.7. Pharmacokinetic analysis

2.8. Statistical analysis

3. Results

3.1. In vitro studies

3.1.1. Characterization of voriconazole metabolism in vitro

Fig. 1.

Table 1.

3.2. Clinical studies

3.2.1. Participant demographics

3.2.2. Voriconazole AEs and safety evaluation

Fig. 2.

Table 2.

3.3. Plasma pharmacokinetics of voriconazole and metabolites

Fig. 3.

3.4. Exploratory analysis of voriconazole conjugates in human plasma

3.5. Urine pharmacokinetics of voriconazole and its metabolites

3.6. Plasma and urine pharmacokinetics stratified by compliance status

3.7. Associations of variants in voriconazole disposition genes with plasma and urine pharmacokinetics of voriconazole and metabolites

3.7.1. Associations with individual CYP2C19 genotypes

Fig. 4.

3.7.2. Associations with CYP2C19 genotype-predicted phenotypes

Fig. 5.

Table 3.

Table 4.

3.7.3. Associations with 4 CYP2C19 phenotypes

3.8. Associations of variants in the CYP2C19 gene with voriconazole AEs

4. Discussion

4.1. Limitations

5. Conclusion

Supplementary Material

Significance Statement:

Financial support

Abbreviations

Footnotes

Data availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases