Influence of different proton pump inhibitors on the pharmacokinetics of voriconazole

French-Speaking Network of Pharmacogenetics (RNPGx) Recommendations for Clinical Use of Mavacamten

Mavacamten, the first drug in the class of β-cardiac myosin modulator, is used for the treatment of patients with hypertrophic cardiomyopathy. This orally administered drug demonstrates wide interpatient variability in pharmacokinetics parameters, due in part to variant CYP2C19 alleles. Individuals who are CYP2C19 poor metabolizers have increased exposure and are at increased risk of reduced cardiac hypercontractility. To ensure the safety of all patients, European Medicines Agency recommends CYP2C19 preemptive genotyping, and consecutively, to adapt maintenance and initial mavacamten doses, and to manage drug-drug interactions, according to CYP2C19 phenotype. In this article, we summarize evidence from the literature supporting the association between CYP2C19 phenotype and pharmacological features of mavacamten and provide, beyond biologic guidelines, therapeutic recommendations for the use of mavacamten based on CYP2C19 and CYP3A4/CYP3A5 genotype.

Whole Body Physiologically Based Pharmacokinetic Model to Explain A Patient With Drug-Drug Interaction Between Voriconazole and Flucloxacillin

BACKGROUND AND OBJECTIVES

Voriconazole administered concomitantly with flucloxacillin may result in subtherapeutic plasma concentrations as shown in a patient with Staphylococcus aureus sepsis and a probable pulmonary aspergillosis. After switching our patient to posaconazole, therapeutic concentrations were reached. The aim of this study was to first test our hypothesis that flucloxacillin competes with voriconazole not posaconazole for binding to albumin ex vivo, leading to lower total concentrations in plasma.

METHODS

A physiologically based pharmacokinetic (PBPK) model was then applied to predict the mechanism of action of the drug-drug interaction (DDI). The model included non-linear hepatic metabolism and the effect of a severe infectious disease on cytochrome P450 (CYP) enzymes activity.

RESULTS

The unbound voriconazole concentration remained unchanged in plasma after adding flucloxacillin, thereby rejecting our hypothesis of albumin-binding site competition. The PBPK model was able to adequately predict the plasma concentration of both voriconazole and posaconazole over time in healthy volunteers. Upregulation of CYP3A4, CYP2C9, and CYP2C19 through the pregnane X receptor (PXR) gene by flucloxacillin resulted in decreased voriconazole plasma concentrations, reflecting the DDI observations in our patient. Posaconazole metabolism was not affected, or was only limitedly affected, by the changes through the PXR gene, which agrees with the observed plasma concentrations within the target range in our patient.

CONCLUSIONS

Ex vivo experiments reported that the unbound voriconazole plasma concentration remained unchanged after adding flucloxacillin. The PBPK model describes the potential mechanism driving the drug-drug and drug-disease interaction of voriconazole and flucloxacillin, highlighting the large substantial influence of flucloxacillin on the PXR gene and the influence of infection on voriconazole plasma concentrations, and suggests a more limited effect on other triazoles.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Notable drug-drug interaction between omeprazole and voriconazole in CYP2C19 *1 and *2 (rs4244285, 681G>A) alleles in vitro

The drug-drug interaction (DDI) and CYP2C19 genetic variation can lead to a high blood concentration of voriconazole. CYP2C19 is a highly genetically polymorphic enzyme, and CYP2C19*2 is more frequent among Asians associated with reduced metabolism of drugs. Clinical study found that co-administration with omeprazole significantly increased voriconazole concentrations and there was an additive effect in CYP2C19*2 allele.CYP2C19 rs4244285 (681G>A) is the key polymorphism of CYP2C19*2 allele. This study aims to describe the in vitro effects of omeprazole on CYP2C19*1 and *2 (681G>A), and determine how CYP2C19 polymorphisms influence the DDI between omeprazole and voriconazole.Using the lentiviral expression system, we successfully generated HepG2-derived cell lines stably expressing CYP2C19*1 and *2 (681G>A). The results showed that the CYP2C19 mRNA level, protein level, and enzymatic activity were lower in HepG2-CYP2C19*2 (681G>A) than HepG2-CYP2C19*1 cells. Our study also showed that the inhibition rates of omeprazole on voriconazole had no significantly differences between CYP2C19*1 and *2 (681G>A). But the IC50 of omeprazole on CYP2C19*1 slightly lower than CYP2C19*2 (681G>A).Moreover, omeprazole inhibited CYP2C19 protein level in cells carrying CYP2C19*1 and CYP2C19*2 (681G>A). Our study demonstrated that omeprazole could inhibit voriconazole metabolism in both CYP2C19*1 and CYP2C19*2 (681G>A).

Associated factors with voriconazole plasma concentration: a systematic review and meta-analysis

Background: Voriconazole plasma concentration exhibits significant variability and maintaining it within the therapeutic range is the key to enhancing its efficacy. We conducted a systematic review and meta-analysis to estimate the prevalence of patients achieving the therapeutic range of plasma voriconazole concentration and identify associated factors. Methods: Eligible studies were identified through the PubMed, Embase, Cochrane Library, and Web of Science databases from their inception until 18 November 2023. We conducted a meta-analysis using a random-effects model to determine the prevalence of patients who reached the therapeutic plasma voriconazole concentration range. Factors associated with plasma voriconazole concentration were summarized from the included studies. Results: Of the 60 eligible studies, 52 reported the prevalence of patients reaching the therapeutic range, while 20 performed multiple linear regression analyses. The pooled prevalence who achieved the therapeutic range was 56% (95% CI: 50%-63%) in studies without dose adjustment patients. The pooled prevalence of adult patients was 61% (95% CI: 56%-65%), and the pooled prevalence of children patients was 55% (95% CI: 50%-60%) The study identified, in the children population, several factors associated with plasma voriconazole concentration, including age (coefficient 0.08, 95% CI: 0.01 to 0.14), albumin (-0.05 95% CI: -0.09 to -0.01), in the adult population, some factors related to voriconazole plasma concentration, including omeprazole (1.37, 95% CI 0.82 to 1.92), pantoprazole (1.11, 95% CI: 0.17-2.04), methylprednisolone (-1.75, 95% CI: -2.21 to -1.30), and dexamethasone (-1.45, 95% CI: -2.07 to -0.83). Conclusion: The analysis revealed that only approximately half of the patients reached the plasma voriconazole concentration therapeutic range without dose adjustments and the pooled prevalence of adult patients reaching the therapeutic range is higher than that of children. Therapeutic drug monitoring is crucial in the administration of voriconazole, especially in the children population. Particular attention may be paid to age, albumin levels in children, and the use of omeprazole, pantoprazole, dexamethasone and methylprednisolone in adults. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023483728.

Physiologically Based Pharmacokinetic Modeling to Investigate the Disease-Drug-Drug Interactions between Voriconazole and Nirmatrelvir/Ritonavir in COVID-19 Patients with CYP2C19 Phenotypes

Coronavirus disease 2019 (COVID-19)-associated pulmonary aspergillosis superinfection with cytokine storm is associated with increased mortality. This study aimed to establish a physiologically-based pharmacokinetic (PK) model to investigate the disease-drug-drug interactions between voriconazole and nirmatrelvir/ritonavir in patients with COVID-19 with elevated interleukin-6 (IL-6) levels carrying various CYP2C19 phenotypes. The model was constructed and validated using PK data on voriconazole, ritonavir, and IL-6, and was subsequently verified against clinical data from 78 patients with COVID-19. As a result, the model predicted voriconazole, ritonavir, and IL-6 PK parameters and drug-drug interaction-related fold changes in healthy subjects and patients with COVID-19 with acceptable prediction error, demonstrating its predictive capability. Simulations indicated ritonavir could increase voriconazole exposure to CYP2C19 intermediate and poor metabolizers rather than decrease it, in contrast to what is indicated in the drug package insert. However, the predicted ritonavir exposures were comparable across subjects. In patients with COVID-19, both ritonavir and IL-6 increased voriconazole trough concentrations, which may lead to CYP2C19 phenotype-dependent overexposure. In conclusion, COVID-19-induced IL-6 elevation and ritonavir increased voriconazole exposure, and the magnitude of interactions was influenced by CYP2C19 phenotype. Thus, caution is warranted when prescribing voriconazole concomitantly with Paxlovid in patients with COVID-19.

Establishing Virtual Bioequivalence and Clinically Relevant Specifications for Omeprazole Enteric-Coated Capsules by Incorporating Dissolution Data in PBPK Modeling

Currently, Biopharmaceutics Classification System (BCS) classes I and III are the only biological exemptions of immediate-release solid oral dosage forms eligible for regulatory approval. However, through virtual bioequivalence (VBE) studies, BCS class II drugs may qualify for biological exemptions if reliable and validated modeling is used. Here, we sought to establish physiologically based pharmacokinetic (PBPK) models, in vitro-in vivo relationship (IVIVR), and VBE models for enteric-coated omeprazole capsules, to establish a clinically-relevant dissolution specification (CRDS) for screening BE and non-BE batches, and to ultimately develop evaluation criteria for generic omeprazole enteric-coated capsules. To establish omeprazole's IVIVR based on the PBPK model, we explored its in vitro dissolution conditions and then combined in vitro dissolution profile studies with in vivo clinical trials. The predicted omeprazole pharmacokinetics (PK) profiles and parameters closely matched the observed PK data. Based on the VBE results, the bioequivalence study of omeprazole enteric-coated capsules required at least 48 healthy Chinese subjects. Based on the CRDS, the capsules' in vitro dissolution should not be < 28%-54%, < 52%, or < 80% after two, three, and six hours, respectively. Failure to meet these dissolution criteria may result in non-bioequivalence. Here, PBPK modeling and IVIVR methods were used to bridge the in vitro dissolution of the drug with in vivo PK to establish the BE safety space of omeprazole enteric-coated capsules. The strategy used in this study can be applied in BE studies of other BCS II generics to obtain biological exemptions and accelerate drug development.

Physiologically based pharmacokinetic modeling to assess the drug-drug interactions of anaprazole with clarithromycin and amoxicillin in patients undergoing eradication therapy of H. pylori infection

OBJECTIVE

This study aimed to assess the pharmacokinetic (PK) interactions of anaprazole, clarithromycin, and amoxicillin using physiologically based pharmacokinetic (PBPK) models.

METHODS

The PBPK models for anaprazole, clarithromycin, and amoxicillin were constructed using the GastroPlus™ software (Version 9.7) based on the physicochemical data and PK parameters obtained from literature, then were optimized and validated in healthy subjects to predict the plasma concentration-time profiles of these three drugs and assess the predictive performance of each model. According to the analysis of the properties of each drug, the developed and validated models were applied to evaluate potential drug-drug interactions (DDIs) of anaprazole, clarithromycin, and amoxicillin.

RESULTS

The developed PBPK models properly described the pharmacokinetics of anaprazole, clarithromycin, and amoxicillin well, and all predicted PK parameters (Cmax,ss, AUC0-τ,ss) ratios were within 2.0-fold of the observed values. Furthermore, the application of these models to predict the anaprazole-clarithromycin and anaprazole-amoxicillin DDIs demonstrates their good performance, with the predicted DDI Cmax,ss ratios and DDI AUC0-τ,ss ratios within 1.25-fold of the observed values, and all predicted DDI Cmax,ss, and AUC0-τ,ss ratios within 2.0-fold. The simulated results show no need to adjust the dosage when co-administered with anaprazole in patients undergoing eradication therapy of H. pylori infection since the dose remained in the therapeutic range.

CONCLUSION

The whole-body PBPK models of anaprazole, clarithromycin, and amoxicillin were built and qualified, which can predict DDIs that are mediated by gastric pH change and inhibition of metabolic enzymes, providing a mechanistic understanding of the DDIs observed in the clinic of clarithromycin, amoxicillin with anaprazole.

Use of modeling and simulation to predict the influence of triazole antifungal agents on the pharmacokinetics of zanubrutinib and acalabrutinib

Background: Bruton’s tyrosine kinase (BTK) inhibitors are commonly used in the targeted therapy of B-cell malignancies. It is reported that myelosuppression and fungal infections might occur during antitumor therapy of BTK inhibitors, therefore a combination therapy with triazole antifungals is usually required.

Objective: To evaluate the influence of different triazoles (voriconazole, fluconazole, itraconazole) on the pharmacokinetics of BTK inhibitors (zanubrutinib, acalabrutinib) and to quantify the drug-drug interactions (DDIs) between them.

Methods: The physiologically-based pharmacokinetic (PBPK) models were developed based on pharmacokinetic parameters and physicochemical data using Simcyp^® software. These models were validated using clinically observed plasma concentrations data which based on existing published studies. The successfully validated PBPK models were used to evaluate and predict potential DDIs between BTK inhibitors and different triazoles. BTK inhibitors and triazole antifungal agents were simulated by oral administration.

Results: Simulated plasma concentration-time profiles of the zanubrutinib, acalabrutinib, voriconazole, fluconazole, and itraconazole are consistent with the clinically observed profiles which based on existing published studies, respectively. The exposures of BTK inhibitors increase by varying degrees when co-administered with different triazole antifungals. At multiple doses regimen, voriconazole, fluconazole and itraconazole may increase the area under plasma concentration-time curve (AUC) of zanubrutinib by 127%, 81%, and 48%, respectively, and may increase the AUC of acalabrutinib by 326%, 119%, and 264%, respectively.

Conclusion: The PBPK models sufficiently characterized the pharmacokinetics of BTK inhibitors and triazole antifungals, and were used to predict untested clinical scenarios. Voriconazole exhibited the greatest influence on the exposures of BTK inhibitors. The dosage of zanubrutinib or acalabrutinib need to be reduced when co-administered with moderate CYP3A inhibitors.

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

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

Impact of polymorphisms of pharmacokinetics-related genes and the inflammatory response on the metabolism of voriconazole

The effects of inflammatory responses and polymorphisms of the genes encoding cytochrome P450 (CYP) (CYP2C19 and CYP3A5), flavin-containing monooxygenase 3 (FMO3), pregnane X receptor (NR1I2), constitutive androstane receptor (NR1I3), and CYP oxidoreductase (POR) on the ratio of voriconazole (VRCZ) N-oxide to VRCZ (VNO/VRCZ) and steady-state trough concentrations (C0h ) of VRCZ were investigated. A total of 56 blood samples were collected from 36 Japanese patients. Results of multiple linear regression analyses demonstrated that the presence of the extensive metabolizer CYP2C19 genotype, the dose per administration, and the presence of the NR1I2 rs3814057 C/C genotype were independent factors influencing the VNO/VRCZ ratio in patients with CRP levels of less than 40 mg/L (standardized regression coefficients (SRC) = 0.448, -0.301, and 0.390, respectively; all p < .05). With regard to the concentration of VRCZ itself, in addition to the above factors, the presence of the NR1I2 rs7643645 G/G and rs3814055 T/T genotypes were found to be independent factors influencing the VRCZ C0h in these patients (SRC = -0.430, 0.424, -0.326, 0.406 and -0.455, respectively; all p < .05). On the contrary, in patients with CRP levels of at least 40 mg/L, no independent factors were found to affect VNO/VRCZ and VRCZ C0h . Inflammatory responses, and CYP2C19 and NR1I2 polymorphisms may be useful information for the individualization of VRCZ dosages.

Decrease of voriconazole trough levels during therapy with enteral nutrition: a case report

Background

Voriconazole (VRCZ) is the first-line therapy for chronic pulmonary aspergillosis and is available in both intravenous and oral formulations. The bioavailability of the oral form is estimated to be over 90% in healthy volunteers. Some drugs are reported to interact with enteral nutrition (EN), but there are few reports about the trough levels of VRCZ during EN therapy. Here, we describe changes in the VRCZ trough levels in a patient receiving continuous EN therapy.

Case presentation

The patient was a 58-year-old man with esophageal cancer and a history of partial pulmonary resection due to aspergilloma. He was taking oral VRCZ tablets and his VRCZ trough level was about 2 μg/mL before esophageal cancer surgery. Following esophagectomy, VRCZ was restarted on postoperative day 16. Crushed VRCZ tablets were administered via a jejunostomy tube because of swallowing difficulty. He was also receiving EN, which was interrupted only during the administration of VRCZ. When we checked his VRCZ level 5 days after restarting VRCZ, the trough level was 0.80 μg/mL. After increasing the VRCZ dose, reducing EN, and changing the administration route from jejunostomy tube to oral, his trough level increased to 1.87 μg/mL.

Conclusions

A decrease in the VRCZ trough level was observed when VRCZ was administered via a jejunostomy tube while the patient was receiving continuous EN. Careful monitoring of VRCZ levels is needed in such cases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40780-021-00237-4.

Antifungal Drugs TDM: Trends and Update

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Use of Modeling and Simulation to Predict the Influence of Triazole Antifungal Agents on the Pharmacokinetics of Crizotinib

Crizotinib is used for the treatment of c-ros oncogene 1-positive advanced non-small-cell lung cancer. Triazole antifungal agents are widely used for invasive fungal infections in clinical practice. To predict the potential influence of different triazoles (voriconazole, fluconazole, and itraconazole) on the pharmacokinetics of crizotinib by modeling and simulation the physiologically based pharmacokinetic models were established and validated in virtual cancer subjects through Simcyp software based on the essential physicochemical properties and pharmacokinetic data collected. The validated physiologically based pharmacokinetic models were applied to predict the drug-drug interactions between crizotinib and different triazoles (voriconazole, fluconazole, or itraconazole) in patients with cancer. Crizotinib and triazole antifungal agents were administered orally. The predicted plasma concentration vs time profiles of crizotinib, voriconazole, fluconazole, and itraconazole showed good agreement with observed, respectively. The geometric mean area under the plasma concentration-time curve (AUC) of crizotinib was increased by 84%, 58%, and 79% when coadministered with voriconazole, fluconazole, or itraconazole at multiple doses, respectively. The drug-drug interaction results showed increased pharmacokinetic exposure (maximum plasma concentration and area under the plasma concentration-time curve) of crizotinib when coadministrated with different triazoles (voriconazole > itraconazole > fluconazole). Among the 3 triazoles, voriconazole exhibited the most significant influence on the pharmacokinetic exposure of crizotinib. In clinic, adverse drug reactions and toxicity related to crizotinib should be carefully monitored, and therapeutic drug monitoring for crizotinib is recommended to guide dosing and optimize treatment when coadministered with voriconazole, fluconazole, or itraconazole.

Analysis of Combined Effect of CYP2C19 Genetic Polymorphism and Proton Pump Inhibitors Coadministration on Trough Concentration of Voriconazole

Purpose

To analyze the combined effect of CYP2C19 genetic polymorphism and PPIs coadministration on voriconazole trough concentration (VCZ-C_trough) in Chinese patients with hematological disorders.

Patients and Methods

A prospective observational study involved 250 plasma samples from 114 adult patients receiving voriconazole with or without PPIs were analyzed. Demographics and clinical characteristics were obtained from patient’s records. A validated LC-MS/MS was used to quantify the plasma VCZ-C_trough. Genotyping for CYP2C19*2 and CYP2C19*3 variant alleles was performed by PCR-RFLP followed by DNA sequencing. The combined total score (from 2 to 5) was calculated for each patient. The higher the score, the lesser the metabolism of the patient.

Findings

Fifty percent of patients administered with voriconazole were coadministered with PPIs, predominantly omeprazole or esomeprazole. Patients exhibiting CYP2C19 poor metabolizer phenotype showed a significantly higher median VCZ-C_trough, (4.31µg/mL [IQR, 1.64µg/mL–7.36µg/mL]) than patients with normal metabolizer (1.38µg/mL, [IQR, 0.79µg/mL–2.14µg/mL], p < 0.0001). Similarly, patients co-administration with PPIs had higher median VCZ-C_trough (2.86µg/mL [IQR 1.33µg/mL–4.66µg/mL]), than PPIs non-users (1.71µg/mL, [IQR, 0.86µg/mL–3.48µg/mL], p = 0.001). However, we noted that the median VCZ-C_trough for each factor was ranging within the normal recommended therapeutic range in the Chinese population (0.5µg/mL–5µg/mL). But when the two factors were combined, the median VCZ-C_trough was steadily increasing as the metabolic capacity (reflected by combined total score) was increasing. Importantly, the median VCZ-C_trough in PM/PPIs user (total score 5) was significantly elevated to supra-therapeutic levels compared to NM/PPI non-user group (total score 2) (5.83µg/mL [IQR, 2.19µg/mL–9.51µg/mL] versus 1.13µg/mL [IQR, 0.67µg/mL–1.82µg/mL]), respectively, P < 0.0001. Furthermore, we observed that the elevation of median VCZ-C_trough to supra-therapeutic levels was largely contributed by omeprazole or esomeprazole compared to lansoprazole or pantoprazole.

Conclusion

Coadministration with PPIs significantly increased voriconazole trough concentrations and there was an additive effect in CYP2C19 PMs, who were most likely to have supra-therapeutic levels.

The Influence of Wuzhi Capsule on the Pharmacokinetics of Cyclophosphamide

BACKGROUND

Cyclophosphamide is approved for the treatment of a variety of tumors, yet the use of cyclophosphamide is limited by kidney and liver toxicity. In the clinic, the Wuzhi capsule is approved to attenuate cyclophosphamide toxicity in the kidney and liver.

OBJECTIVE

We aimed to investigate the effects of the principal ingredients of Wuzhi capsule, schisandrin A (SIA) and schisantherin A (STA), on the pharmacokinetics of cyclophosphamide.

METHODS

The essential pharmacokinetic data and physicochemical parameters of SIA, STA, and cyclophosphamide were collected. Physiologically based pharmacokinetic (PBPK) models of SIA, STA, and cyclophosphamide were built in Simcyp Simulator and verified using published clinical pharmacokinetic data. The verified PBPK models were used to predict potential herb-drug interactions (HDIs) between cyclophosphamide and SIA and STA in cancer patients.

RESULTS

The area under the plasma concentration-time curve (AUC) of cyclophosphamide was increased by 18% and 1% when co-administered with STA and SIA at a single dose, respectively, and increased by 301% and 29% when co-administered with STA and SIA at multiple doses, respectively. The maximum concentration (Cmax) of cyclophosphamide was increased by 75% and 7% when co-administered with STA and SIA at multiple doses, respectively.

CONCLUSION

The AUC and Cmax of cyclophosphamide were increased when cyclophosphamide was combined with the Wuzhi capsule, compared to cyclophosphamide alone. Our study shows that the adverse drug reactions and toxicity of cyclophosphamide should be closely monitored and an effective dosage adjustment of cyclophosphamide may need to be considered when co-administered with the Wuzhi capsule.

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

Objective

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

Methods

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

Results

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

Conclusions

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

Supplementary Information

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

Impact of CYP2C19 Phenotype and Drug-Drug Interactions on Voriconazole Concentration in Pediatric Patients

Voriconazole (VRC), a first-line agent for the treatment of invasive fungal infections, is mainly metabolized by human cytochrome P450 (CYP) 2C19. In this study, a retrospective analysis was performed to investigate the key factors that influence the plasma trough concentration (C_min) of VRC, and an appropriate dosing regimen for pediatric patients was drafted subsequently. Overall, factors such as age, CYP2C19 phenotype, and combination medication with proton pump inhibitors accounted for 23.4% of variability in dose-normalized C_min values of VRC by a multiple linear regression analysis. Dose-normalized C_min values in the poor metabolizers (PMs) and intermediate metabolizers (IMs) were significantly higher than those in extensive metabolizers (EMs) (P < 0.001). To achieve therapeutic C_min for CYP2C19 ultrarapid metabolizers (UMs) or EMs, patients aged no more than 12 and more than 12 years required doses of 6.53 ± 2.08 and 3.95 ± 0.85 mg/kg of body weight twice daily (P = 0.007). For CYP2C19 PMs or IMs, patients aged under 12 and over 12 years required doses of 5.75 ± 1.73 and 4.23 ± 0.76 mg/kg twice daily, respectively (P = 0.019). Furthermore, coadministration of rifamycin sodium or omeprazole exhibited significant effects on VRC C_min. Taken together, it is necessary to pay attention to the impact of CYP2C19 phenotype and drug-drug interactions to achieve optimal therapy.

Interactive Effects of Glucocorticoids and Cytochrome P450 Polymorphisms on the Plasma Trough Concentrations of Voriconazole

Aims: To explore the interactive influence of glucocorticoids and cytochrome P450 (CYP450) polymorphisms on voriconazole (VRC) plasma trough concentrations (C_min) and provide a reliable basis for reasonable application of VRC.

Methods: A total of 918 VRC C_min from 231 patients was collected and quantified using high-performance liquid chromatography in this study. The genotypes of CYP2C19, CYP3A4, and CYP3A5 were detected by DNA sequencing assay. The effects of different genotypes and the coadministration of glucocorticoids on VRC C_min were investigated. Furthermore, the interactive effects of glucocorticoids with CYP450s on VRC C_min were also analyzed.

Results: The median C_min of oral administration was lower than that of intravenous administration (1.51 vs. 4.0 mg l⁻¹). Coadministration of glucocorticoids (including dexamethasone, prednisone, prednisolone, and methylprednisolone) reduced the VRC C_min/dose, respectively, among which dexamethasone make the median of the VRC C_min/dose ratio lower. As a result, when VRC was coadministrated with glucocorticoids, the proportion of VRC C_min/dose in the subtherapeutic window was increased. Different CYP450 genotypes have different effects on the C_min/dose of VRC. Mutations of CYP2C19*2 and *3 increased C_min/dose of VRC, while CYP2C19*17 and CYP3A4 rs4646437 polymorphisms decreased C_min/dose of VRC. The mutation of CYP3A5 has no significant effect. Furthermore, CYP2C19*17 mutants could strengthen the effects of glucocorticoids and decrease VRC C_min/dose to a larger extent.

Conclusion: Our study revealed that glucocorticoids reduced the C_min/dose levels of VRC and different SNPs of CYP450 have different effects on the C_min/dose ratio of VRC. Glucocorticoids and CYP2C19*17 mutants had a synergistic effect on reducing VRC C_min/dose. The present results suggested that when VRC is combined with glucocorticoids, we should pay more attention to the clinical efficacy of VRC, especially when CYP2C19*17 mutants exist.

A Whole-Body Physiologically Based Pharmacokinetic Model Characterizing Interplay of OCTs and MATEs in Intestine, Liver and Kidney to Predict Drug-Drug Interactions of Metformin with Perpetrators

Transmembrane transport of metformin is highly controlled by transporters including organic cation transporters (OCTs), plasma membrane monoamine transporter (PMAT), and multidrug/toxin extrusions (MATEs). Hepatic OCT1, intestinal OCT3, renal OCT2 on tubule basolateral membrane, and MATE1/2-K on tubule apical membrane coordinately work to control metformin disposition. Drug–drug interactions (DDIs) of metformin occur when co-administrated with perpetrators via inhibiting OCTs or MATEs. We aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model characterizing interplay of OCTs and MATEs in the intestine, liver, and kidney to predict metformin DDIs with cimetidine, pyrimethamine, trimethoprim, ondansetron, rabeprazole, and verapamil. Simulations showed that co-administration of perpetrators increased plasma exposures to metformin, which were consistent with clinic observations. Sensitivity analysis demonstrated that contributions of the tested factors to metformin DDI with cimetidine are gastrointestinal transit rate > inhibition of renal OCT2 ≈ inhibition of renal MATEs > inhibition of intestinal OCT3 > intestinal pH > inhibition of hepatic OCT1. Individual contributions of transporters to metformin disposition are renal OCT2 ≈ renal MATEs > intestinal OCT3 > hepatic OCT1 > intestinal PMAT. In conclusion, DDIs of metformin with perpetrators are attributed to integrated effects of inhibitions of these transporters.

Modeling Approach to Predict the Impact of Inflammation on the Pharmacokinetics of CYP2C19 and CYP3A4 Substrates

PURPOSE

For decades, inflammation has been considered a cause of pharmacokinetic variability, mainly in relation to the inhibitory effect of pro-inflammatory cytokines on the expression level and activity of cytochrome P450 (CYP). In vitro and clinical studies have shown that two major CYPs, CYP2C19 and CYP3A4, are both impaired. The objective of the present study was to quantify the impact of the inflammatory response on the activity of both CYPs in order to predict the pharmacokinetic profile of their substrates according to systemic C-reactive protein (CRP).

METHODS

The relationships between CRP concentration and both CYPs activities were estimated and validated using clinical data first on midazolam then on voriconazole. Finally, clinical data on omeprazole were used to validate the findings. For each substrate, a physiologically based pharmacokinetics model was built using a bottom-up approach, and the relationships between CRP level and CYP activities were estimated by a top-down approach. After incorporating the respective relationships, we compared the predictions and observed drug concentrations.

RESULTS

Changes in pharmacokinetic profiles and parameters induced by inflammation seem to be captured accurately by the models.

CONCLUSIONS

These findings suggest that the pharmacokinetics of CYP2C19 and CYP3A4 substrates can be predicted depending on the CRP concentration.

Predictors of Adverse Events and Determinants of the Voriconazole Trough Concentration in Kidney Transplantation Recipients

Voriconazole is the mainstay for the treatment of invasive fungal infections in patients who underwent a kidney transplant. Variant CYP2C19 alleles, hepatic function, and concomitant medications are directly involved in the metabolism of voriconazole. However, the drug is also associated with numerous adverse events. The purpose of this study was to identify predictors of adverse events using binary logistic regression and to measure its trough concentration using multiple linear modeling. We conducted a prospective analysis of 93 kidney recipients cotreated with voriconazole and recorded 213 trough concentrations of it. Predictors of the adverse events were voriconazole trough concentration with the odds ratios (OR) of 2.614 (P = 0.016), cytochrome P450 2C19 (CYP2C19), and hemoglobin (OR 0.181, P = 0.005). The predictive power of these three factors was 91.30%. We also found that CYP2C19 phenotypes, hemoglobin, platelet count, and concomitant use of ilaprazole had quantitative relationships with voriconazole trough concentration. The fit coefficient of this regression equation was R²  = 0.336, demonstrating that the model explained 33.60% of interindividual variability in the disposition of voriconazole. In conclusion, predictors of adverse events are CYP2C19 phenotypes, hemoglobin, and voriconazole trough concentration. Determinants of the voriconazole trough concentration were CYP2C19 phenotypes, platelet count, hemoglobin, concomitant use of ilaprazole. If we consider these factors during voriconazole use, we are likely to maximize the treatment effect and minimize adverse events.

A Simple Decision Tree Suited for Identification of Early Oral Drug Candidates With Likely Pharmacokinetic Nonlinearity by Intestinal CYP3A Saturation

To identify oral drugs that likely display nonlinear pharmacokinetics due to saturable metabolism by intestinal CYP3A, our previous report using CYP3A substrate drugs proposed an approach using thresholds for the linear index number (LIN3A = dose/K_m; K_m, Michaelis-Menten constant for CYP3A) and the intestinal availability (F_aF_g). Here, we aimed to extend the validity of the previous approach using both CYP3A substrate and non-substrate drugs and to devise a decision tree suited for early drug candidates using in vitro metabolic intrinsic clearance (CL_{int, vitro}) instead of F_aF_g. Out of 152 oral drugs (including 136 drugs approved in Japan, US or both), type I nonlinearity (in which systemic drug exposure increases in a more than dose-proportional manner) was noted with 82 drugs (54%), among which 58 drugs were identified as CYP3A substrates based on public information. Based on practical feasibility, 41 drugs were selected from CYP3A substrates and subjected to in-house metabolic assessment. The results were used to determine the thresholds for CL_{int, vitro} (0.45 μL/min/pmol CYP3A4) and LIN3A (1.0 L). For four drugs incorrectly predicted, potential mechanisms were looked up. Overall, our proposed decision tree may aid in the identification of early drug candidates with intestinal CYP3A-derived type I nonlinearity.

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

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

Potential voriconazole associated posterior reversible leukoencephalopathy in children with malignancies: Report of two cases

INTRODUCTION

The fungal infection has become severe morbidity amongst patients with malignancy. Voriconazole, a new generation of triazole, has shown excellent results in treating invasive fungal infections.

CASE REPORT

Herein, we report two cases of posterior reversible encephalopathy syndrome (PRES), which induced after voriconazole exposure.Management and outcome: Magnetic resonance imaging, and the serum level of voriconazole were investigated in both patients to assess toxicity. The role of methotrexate, as one of the possible causes of PRES, is weakened significantly through precise assessing diffusion-weighted images on magnetic resonance imaging.

DISCUSSION

These unique cases emphasize that voriconazole can induce PRES even at therapeutic levels. Therefore, in the case of neurotoxicity, PRES must be considered, and voriconazole should discontinue. The prognosis seemed promising when voriconazole stopped immediately after clinical suspicion.

Effects of Voriconazole on the Pharmacokinetics of Vonoprazan in Rats

Purpose

The purpose of this study was to examine the effects of voriconazole on the pharmacokinetics of vonoprazan.

Methods

Fifteen Sprague-Dawley rats were randomly divided into three groups: five rats in each group, including control group, single-dose group (a single dose of 30 mg/kg of voriconazole), and multiple-dose group (multiple doses of 30 mg/(kg•day) per dose of voriconazole). Each group of rats was given an oral dose of 10 mg/kg vonoprazan 30 min after the administration of voriconazole or vehicle. After the oral administration of vonoprazan, 50 µL of blood was collected into 1.5-mL heparinized tubes via the caudal vein. The concentration of vonoprazan in plasma was quantified by ultra-performance liquid chromatography/tandem mass spectrometry. Both in vitro effects of voriconazole on vonoprazan and the mechanism of the observed inhibition were studied in rat liver microsomes.

Results

When orally administered, voriconazole increased the area under the plasma concentration-time curve (AUC), prolonged the elimination half-life (t_1/2), and decreased the clearance (CL) of vonoprazan; there was no significant difference between the single-dose and multiple-dose groups. Voriconazole inhibited the metabolism of vonoprazan at an IC50 of 2.93 μM and showed mixed inhibition. The results of the in vivo experiments were consistent with those of the in vitro experiments.

Conclusion

Our findings provide the evidence of drug-drug interactions between voriconazole and vonoprazan that could occur with pre-administration of voriconazole. Thus, clinicians should pay attention to the resulting changes in pharmacokinetic parameters and accordingly, adjust the dose of vonoprazan in clinical settings.

A Novel Study Design Using Continuous Intravenous and Intraduodenal Infusions of Midazolam and Voriconazole for Mechanistic Quantitative Assessment of Hepatic and Intestinal CYP3A Inhibition

The extent of a drug-drug interaction (DDI) mediated by cytochrome P450 (CYP) 3A inhibitors is highly variable during a dosing interval, as it depends on the temporal course of victim and perpetrator drug concentrations at intestinal and hepatic CYP3A expression sites. Capturing the time course of inhibition is therefore difficult using standard DDI studies assessing changes in area under the curve; thus, a novel design was developed. In a 4-period changeover pilot study, 6 healthy men received intraduodenal or intravenous infusions of the CYP3A substrate midazolam (MDZ) at a rate of 0.26 mg/h for 24 hours. This was combined with intraduodenal or intravenous infusion of the CYP3A inhibitor voriconazole (VRZ), administered at rates of 7.5 mg/h from 8 to 16 hours and of 15 mg/h from 16 to 24 hours, after starting midazolam administration. Plasma and urine concentrations of VRZ, MDZ, and its major metabolites were quantified by liquid chromatography-tandem mass spectrometry and analyzed by semiphysiological population pharmacokinetic nonlinear mixed-effects modeling. A model including mechanism-based inactivation of the metabolizing enzymes (maximum inactivation rate constant k_inact , 2.83 h^-1 ; dissociation rate constant K I , 9.33 μM) described the pharmacokinetics of VRZ well. By introducing competitive inhibition by VRZ on primary and secondary MDZ metabolism, concentration-time profiles, MDZ and its metabolites were captured appropriately. The model provides estimates of local concentrations of substrate and inhibitor at the major CYP3A expression sites and thus of the respective dynamic extent of inhibition. A combination of intravenous and intraduodenal infusions of inhibitors and substrates has the potential to provide a more accurate assessment of DDIs occurring in both gut wall and liver.

Effect of proton pump inhibitors on voriconazole concentrations in Chinese patients with malignant hematological diseases

PURPOSE

To evaluate the influence of three proton pump inhibitors (PPIs) on plasma voriconazole (VOR) concentrations and characterize potential drug-drug interactions (DDIs) between VOR and three PPIs (omeprazole, lansoprazole, and pantoprazole) in Chinese patients with malignant hematological diseases.

METHODS

A simple and reliable 2D-HPLC with internal quality control method was used to ensure accurate concentration measurements. A total of 194 patients in this retrospective study were divided into control (N = 59), omeprazole (OME, N = 57), lansoprazole (LAN, N = 26), and pantoprazole (PAN, N = 52) groups for comparison of plasma VOR trough concentrations. To further validate our retrospective analysis of clinical data, we used molecular docking simulation to analyze the binding affinity of PPIs to the cytochrome P450 2C19 (CYP2C19) and cytochrome P450 3A4 (CYP3A4) enzymes that are integral to the metabolism of PPIs and VOR.

RESULTS

Our findings indicated that VOR trough concentrations were significantly higher in patient on PPIs compared with those who were not (P = 0.012). Patients on LAN (P < 0.01) or OME (P < 0.05) had significantly elevated VOR concentrations compared with the control group, whereas those on PAN did not. Although VOR trough concentrations were not significantly elevated with PAN, more patients in the PAN group reached therapeutic VOR concentrations than in any other group.

CONCLUSION

In conclusion, our retrospective data analysis and molecular docking simulations results indicate that LAN and OME interact with VOR via CYP2C19 and CYP3A4 to increase VOR plasma concentrations. This study helps with selection of PPIs in Chinese patients with malignant hematological cancer administered VOR.

A multicentre prospective study evaluating the impact of proton-pump inhibitors omeprazole and pantoprazole on voriconazole plasma concentrations

Voriconazole is an antifungal metabolised by CYP2C19 enzyme, which can be inhibited by proton-pump inhibitors (PPIs). A prospective observational study was carried out to determine the influence of PPIs on voriconazole pharmacokinetic. The 78 patients included were divided into 4 groups: omeprazole (n = 32), pantoprazole (n = 25), esomeprazole (n = 3) and no PPI (n = 18). Patients with no PPI had no significant difference in plasma voriconazole concentration when compared with those with PPI (2.63 ± 2.13 μg/mL [95% confidence interval {CI} 1.57-3.69] vs 2.11 ± 1.73 μg/mL [95%CI 1.67-2.55], P > .05). However, voriconazole plasma concentration was significantly lower in patients treated with pantoprazole vs those treated with omeprazole (1.44 ± 1.22 μg/mL [95%CI 0.94-1.94) vs 2.67 ± 1.88 μg/mL [95%CI 2.02-3.32], P = .013) suggesting a greater CYP2C19 enzyme inhibitory effect of omeprazole. This study demonstrates the greater CYP inhibition capacity of omeprazole and should be helpful for the choice of PPIs for patients treated with voriconazole.

Pharmacokinetics of intravenous voriconazole in patients with liver dysfunction: A prospective study in the intensive care unit

OBJECTIVES

To characterize the pharmacokinetics (PK) of intravenous voriconazole (VRC) in critically ill patients with liver dysfunction.

METHODS

Patients with liver dysfunction in the intensive care unit (ICU) were included prospectively. The Child-Pugh score was used to categorize the degree of liver dysfunction. The initial intravenous VRC dosing regimen comprised a loading dose of 300 mg every 12 h for the first 24 h, followed by 200 mg every 12 h. The first PK curves (PK curve 1) were drawn within one dosing interval of the first dose for 17 patients; the second PK curves (PK curve 2) were drawn within one dosing interval after a minimum of seven doses for 12 patients. PK parameters were estimated by non-compartmental analysis.

RESULTS

There were good correlations between the area under the curve (AUC_0-12) of PK curve 2 and the corresponding trough concentration (C₀) and peak concentration (C_max) (r² = 0.951 and 0.963, respectively; both p < 0.001). The median half-life (t_1/2) and clearance (CL) of patients in Child-Pugh class A (n = 3), B (n = 5), and C (n = 4) of PK curve 2 were 24.4 h and 3.31 l/h, 29.1 h and 2.54 l/h, and 60.7 h and 2.04 l/h, respectively. In the different Child-Pugh classes, the CL (median) of PK curve 2 were all lower than those of PK curve 1. The apparent steady-state volume of distribution (V_ss) of PK curve 1 was positively correlated with actual body weight (r² = 0.450, p = 0.004). The median first C₀ of 17 patients determined on day 5 was 5.27 (2.61) μg/ml, and 29.4% of C₀ exceeded the upper limit of the therapeutic window (2-6 μg/ml).

CONCLUSIONS

The CL of VRC decreased with increasing severity of liver dysfunction according to the Child-Pugh classification, along with an increased t_1/2, which resulted in high plasma exposure of VRC. Adjusted dosing regimens of intravenous VRC should be established based on Child-Pugh classes for these ICU patients, and plasma concentrations should be monitored closely to avoid serious adverse events.

The Influence of Different Triazole Antifungal Agents on the Pharmacokinetics of Cyclophosphamide

Background: Cyclophosphamide is one of the most important chemotherapeutic drugs. Known as a widely accepted treatment strategy, chemotherapy may damage the immune function of cancer patients; as a result, invasive fungal infections (IFIs) occur. Triazole antifungal agents are the most acceptable drugs for IFI treatment, especially those infections caused by chemotherapy. Objective: We aimed to investigate the effects of different triazole antifungal drugs, including fluconazole, itraconazole, and ketoconazole, on the pharmacokinetics (PK) of cyclophosphamide. In addition, we also characterize the potential drug-drug interactions (DDIs) between cyclophosphamide and various triazole antifungal drugs. Methods: The necessary pharmacokinetic parameters and physicochemical data were obtained from published studies. Physiologically based pharmacokinetic (PBPK) models were developed and validated in virtual subjects using Simcyp software. The validated PBPK models were used to evaluate potential DDIs between cyclophosphamide and different triazole antifungal agents in cancer patients. Triazole antifungal agents were simulated by oral administration, whereas cyclophosphamide was simulated by intravenous administration. Results: Simulated plasma concentration-time curves of fluconazole, itraconazole, ketoconazole, and cyclophosphamide were in good consistency with the observed profiles. Our results suggested that the pharmacokinetic parameters of cyclophosphamide were increased by various extents when coadministered with different triazole antifungals. The area under the plasma concentration-time curve of cyclophosphamide was increased when combined with fluconazole, itraconazole, or ketoconazole. Conclusions and Relevance: Ketoconazole had the greatest effect on the PK of cyclophosphamide among the 3 triazole antifungals. Our study provides clues that the toxicity and adverse drug reactions that are associated with cyclophosphamide should be closely monitored when coadministered with ketoconazole.

Population Pharmacokinetics of Voriconazole and Optimization of Dosage Regimens Based on Monte Carlo Simulation in Patients With Liver Cirrhosis

Because voriconazole metabolism is highly influenced by liver function, the dose regimen of voriconazole should be carefully assessed in patients with liver cirrhosis. We aimed to identify significant factors associated with plasma concentrations. Blood samples were collected from patients with liver cirrhosis who received voriconazole, and voriconazole concentrations were determined. One-compartment model with first-order absorption and elimination appropriately characterized the in vivo process of voriconazole. The typical population value of voriconazole clearance (CL) was 1.45 L/h and the volume of distribution (V) was 132.12 L. The covariate analysis identified that CYP2C19 gene phenotype and Child-Pugh classification were strongly associated with CL and body weight had a significant influence on V. The results of the Monte Carlo simulation suggested that CYP2C19 gene phenotype was a critical factor for determining voriconazole dosage in patients with liver cirrhosis. The extensive metabolizer patients with Aspergillus fumigatus infections could be treated effectively with a recommended dose of 75 mg twice daily in mild to moderate liver cirrhosis and 100 mg once daily in moderate severe liver cirrhosis. However, the recommended dosage for Candida albicans infections patients was not achieved in present study.

Novel insights into the complex pharmacokinetics of voriconazole: a review of its metabolism

Voriconazole, a second-generation triazole frequently used for the prophylaxis and treatment of invasive fungal infections, undergoes complex metabolism mainly involving various (polymorphic) cytochrome P450 enzymes in humans. Although high inter- and intraindividual variability in voriconazole pharmacokinetics have been observed and the therapeutic range for this compound is relatively narrow, the metabolism of voriconazole has not been fully elucidated yet. The available literature data investigating the multiple different pathways and metabolites are extremely unbalanced and thus the absolute or relative contribution of the different pathways and enzymes involved in the metabolism of voriconazole remains uncertain. Furthermore, other factors such as nonlinear pharmacokinetics caused by auto-inhibition or -induction and polymorphisms of the metabolizing enzymes hinder safe and effective voriconazole dosing in clinical practice and have not yet been studied sufficiently. This review aimed at amalgamating the available literature on the pharmacokinetics of voriconazole in vitro and in vivo, with a special focus on metabolism in adults and children, in order to congregate an overall landscape of the current body of knowledge and identify knowledge gaps, opening the way towards further research in order to foster the understanding, towards better therapeutic dosing decisions.

The Pharmacokinetic Prediction of Cyclosporin A after Coadministration with Wuzhi Capsule

We aim to describe the influence of principal ingredients of Wuzhi capsule, schisandrin A (SIA) and schisantherin A (STA), on the pharmacokinetics of cyclosporin A (CsA) and to quantify the herb-drug interactions (HDIs) between SIA, STA, and CsA. CsA is a first-line immunosuppressant for anti-rejection therapy after solid organ transplantation, while narrow therapeutic window associated with strong hepatotoxicity largely limited its use. Wuzhi capsule, a liver-protective drug, was approved for coadministration with CsA to reduce the hepatotoxicity. There are few studies exploring HDIs of CsA when coadministered with Wuzhi capsule. The essential adjusted physicochemical data and pharmacokinetic parameters of SIA, STA, and CsA were collected. Then physiologically based pharmacokinetic (PBPK) models of SIA, STA, and CsA were built and verified in healthy subjects using Simcyp respectively. The refined PBPK models were used to estimate potential HDIs between CsA and SIA, STA. The simulated plasma concentration-time curves of CsA, SIA, and STA were in good accordance with the observed profiles respectively. CsA pharmacokinetics were improved after coadministration. After a single dose and multiple doses, the area under the plasma concentration-time curve (AUC) of CsA was increased by 47% and 226% when coadministered with STA, respectively, and by 8% and 36% when coadministered with SIA, respectively. PBPK models sufficiently described the pharmacokinetics of CsA, SIA, and STA. Compared with SIA, STA inhibited CsA metabolism to a greater extent. Our result revealed the dose of CsA can be reduced to maintain similar profile when used concomitantly with Wuzhi capsule.

Clinical Pharmacokinetics of Second-Generation Triazoles for the Treatment of Invasive Aspergillosis and Candidiasis

Second-generation triazoles were developed in response to the quest for more efficacious and safer therapeutic options for the treatment of severe systemic aspergillosis and candidiasis. These agents include voriconazole, posaconazole, isavuconazole, and ravuconazole. The aim of this review was to present and compare the pharmacokinetic characteristics of second-generation triazoles for the treatment of invasive aspergillosis and candidiasis, emphasizing their clinical implications. The MEDLINE, Scopus, EBSCO, Google Scholar, and SCIndeks databases were searched using advanced search options, including the names of second-generation triazoles and pharmacokinetic terms as keywords. The intravenous administration of voriconazole, posaconazole, and isavuconazole results in stable pharmacokinetics of these drugs, with mostly predictable variations influenced by common and usually known factors in routine clinical settings. The high oral bioavailability of isavuconazole and, to some extent, voriconazole makes them suitable for intravenous-to-oral switch strategies. Except for intravenous voriconazole (due to the accumulation of the toxic vehicle hydroxypropyl betadex), dose reduction of second-generation triazoles is not needed in patients with renal failure; patients with hepatic insufficiency require dose reduction only in advanced disease stages. The introduction of therapeutic drug monitoring could aid attempts to optimize the blood concentrations of triazoles and other drugs that are known to or that possibly interact, thus increasing treatment efficacy and safety. There is a need for new studies that are designed to provide useful data on second-generation triazole pharmacokinetics, particularly in special circumstances such as central nervous system and ocular infections, infections in newborns and infants, and in subjects with genetic polymorphisms of metabolizing enzymes.

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

PURPOSE

The objective of this study was to characterize the population pharmacokinetics of voriconazole and to identify factors that significantly affect pharmacokinetic parameters and to further investigate optimal dosage regimens in Chinese adult patients with hematologic malignancies.

METHODS

A prospective population pharmacokinetic analysis was performed on 186 concentration measurements obtained from 41 adult patients with hematologic malignancies. All enrolled patients were treated with voriconazole for diagnosed or suspected invasive fungal diseases. Oral voriconazole was routinely administered at a maintenance dose of 200 mg q12h. Serial blood samples were collected after steady-state of each patient. Monte Carlo simulation was applied to optimize dosage strategies.

FINDINGS

A one-compartment model with first-order absorption and elimination adequately described the data. The typical voriconazole clearance was 4.18 L/h, the volume of distribution was 88.9 L, and the absorption rate constant was 0.729 h^-1. Clearance and steady-state exposure (AUC_0-12) were found to be significantly associated with age and CYP2C19 phenotype. The average AUC_0-12 of elderly patients (aged 60-90 years) was 2.1 times higher than that of relative younger patients (aged 18-59 years). The average AUC_0-12 of poor metabolizers (PMs) was approximately 2.5 and 1.8 times higher than that of extensive and intermediate metabolizers (IMs), respectively. Considering both efficacy and tolerability, dosage regimens of 100 and 50 mg orally administered every 12 hours were recommended for elderly IMs and PMs, respectively.

IMPLICATIONS

A population pharmacokinetic model for voriconazole in Chinese adult patients with hematologic malignancies was successfully developed and could well capture voriconazole's pharmacokinetic characteristics. Age and CYP2C19 phenotype were found to significantly influence voriconazole clearance and should be taken into consideration clinically for dose optimization. The optimal dosage strategies in specific clinical scenarios were proposed in this study based on model simulation. Because of the high incidence of mutant CYP2C19*2 and *3 alleles, genetic testing seems to be necessary for Asian elderly patients when voriconazole treatment is initiated.

Impact of voriconazole plasma concentrations on treatment response in critically ill patients

WHAT IS KNOWN AND OBJECTIVE

Several authors have demonstrated the relationship between voriconazole concentrations and the risk of therapeutic failure and adverse events However, the information about voriconazole concentrations in the critically ill patient is scarce. The aim of this study was to analyse the plasma concentrations and pharmacokinetic behaviour of voriconazole in critically ill patients and their association with the treatment response and development of toxicity.

METHODS

A prospective, observational study was conducted. Patients admitted to an intensive care unit and on treatment with intravenous voriconazole were included. Plasma concentrations were measured between days 4 and 7 from the start of the treatment. The pharmacokinetic analysis was performed using the NONMEM^® software. A regression model was used to evaluate the variables associated with the values outside the therapeutic range, as well as the relationship between the plasma concentrations and the treatment response and the development of hepatotoxicity.

RESULTS AND DISCUSSION

A total of 33 patients were included. Plasma concentrations outside the therapeutic range (1-5.5 mg/L) were observed in 15 patients, being above the established range in 9 (27.3%) cases, and below it in 6 (18.2%) cases. The presence of a bilirubin value of >1.5 mg/dL and a C-reactive protein >100 mg/dL was associated with supra-therapeutic concentrations. Voriconazole concentrations greater than 5.5 mg/dL were associated with the development of hepatotoxicity.

WHAT IS NEW AND CONCLUSIONS

There is a wide variation in voriconazole concentrations in critically ill patients, being associated with a high frequency of adverse events. Close monitoring of these values is required in order to decrease the risk of therapeutic failure and toxicity.

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

Highly variable and non-linear pharmacokinetics of voriconazole are mainly caused by CYP2C19 polymorphisms. This study aimed to develop a mechanistic population pharmacokinetic model including the CYP2C19 phenotype, and to assess the appropriateness of various dosing regimens based on the therapeutic target. A total of 1,828 concentrations from 193 subjects were included in the population pharmacokinetic analysis. A three-compartment model with an inhibition compartment appropriately described the voriconazole pharmacokinetics reflecting auto-inhibition. Voriconazole clearance in the CYP2C19 intermediate metabolizers (IMs) and poor metabolizers (PMs) decreased by 17% and 53% compared to that in the extensive metabolizers (EMs). There was a time-dependent inhibition of clearance to 16.2% of its original value in the CYP2C19 EMs, and the extent of inhibition differed according to the CYP2C19 phenotypes. The proposed CYP2C19 phenotype-guided initial dosing regimens are 400 mg twice daily (bid) for EMs, 200 mg bid for IMs, and 100 mg bid for PMs. This CYP2C19 phenotype-guided initial dosing regimen will provide a rationale for individualizing the optimal voriconazole therapy.

Inflammation is a potential risk factor of voriconazole overdose in hematological patients

Voriconazole (VRC) overdoses are frequent and expose patients at high risk of adverse effects. This case-control study performed in hematological patients who benefited from VRC therapeutic drug monitoring from January 2012 to December 2015 aimed to identify risk factors of VRC overdose. Pharmacogenetic, biological, and demographic parameters at the time of VRC trough concentration (C_min ) were retrospectively collected from medical records. Cases (VRC overdose: defined by a VRC C_min ≥ 4 mg/L; n = 31) were compared to controls (no VRC overdose: defined by VRC C_min < 4 mg/L; n = 31) using nonparametric or chi-square tests followed by multivariable analysis. VRC overdoses were significantly associated with high CRP and bilirubin levels, intravenous administration, and age in univariable analysis. In contrast, the proportion of CYP genotypes (CYP2C19, CYP3A4, or CYP3A5, considered alone or combined in a combined genetic score) were not significantly different between patients who experienced a VRC overdose and those who did not. In multivariable analysis, the class of CRP level (defined by median CRP levels of 96 mg/L) was the sole independent risk factor of VRC overdose (P < 0.01). Patients with CRP levels > 96 mg/L) had a 27-fold (IC 95%: [6-106]) higher risk of VRC overdose than patients with CRP levels ≤ 96 mg/L. This study demonstrates that inflammatory status, assessed by CRP levels, is the main risk factor of VRC overdose in French hematological patients, whereas pharmacogenetic determinants do not appear to be involved.

Pharmacogenomics of Medications Commonly Used in the Intensive Care Unit

In the intensive care unit (ICU) setting, where highly variable and insufficient drug efficacies, as well as frequent and unpredictable adverse drug reactions (ADRs) occur, pharmacogenomics (PGx) offers an opportunity to improve health outcomes. However, PGx has not been fully evaluated in the ICU, partly due to lack of knowledge of how genetic markers may affect drug therapy. To fill in this gap, we conducted a review to summarize the PGx information for the medications commonly encountered in the ICU.

Effects of medicines used to treat gastrointestinal diseases on the pharmacokinetics of coadministered drugs: a PEARRL Review

Objectives

Drugs used to treat gastrointestinal diseases (GI drugs) are widely used either as prescription or over-the-counter (OTC) medications and belong to both the 10 most prescribed and 10 most sold OTC medications worldwide. The objective of this review article is to discuss the most frequent interactions between GI and other drugs, including identification of the mechanisms behind these interactions, where possible.

Key findings

Current clinical practice shows that in many cases, these drugs are administered concomitantly with other drug products. Due to their metabolic properties and mechanisms of action, the drugs used to treat gastrointestinal diseases can change the pharmacokinetics of some coadministered drugs. In certain cases, these interactions can lead to failure of treatment or to the occurrence of serious adverse events. The mechanism of interaction depends highly on drug properties and differs among therapeutic categories. Understanding these interactions is essential to providing recommendations for optimal drug therapy.

Summary

Interactions with GI drugs are numerous and can be highly significant clinically in some cases. While alterations in bioavailability due to changes in solubility, dissolution rate, GI transit and metabolic interactions can be (for the most part) easily identified, interactions that are mediated through other mechanisms, such as permeability or microbiota, are less well-understood. Future work should focus on characterising these aspects.

Population pharmacokinetics of voriconazole and CYP2C19 polymorphisms for optimizing dosing regimens in renal transplant recipients

AIMS

The aims of the present study were to characterize the pharmacokinetics of voriconazole in renal transplant recipients and to identify factors significantly affecting pharmacokinetic parameters. We also aimed to explore the optimal dosing regimens for patients who developed invasive fungal infections.

METHODS

A total of 105 patients (342 concentrations) were included prospectively in a population pharmacokinetic analysis. Nonlinear mixed-effects models were developed using Phoenix NLME software. Dosing simulations were performed based on the final model.

RESULTS

A one-compartment model with first-order absorption and elimination was used to characterize voriconazole pharmacokinetics. Population estimates of clearance, volume of distribution and oral bioavailability were 2.88 l·h-1 , 169.3 l and 58%, respectively. The allele frequencies of cytochrome P450 gene (CYP) 2C19*2, *3 and *17 variants were 29.2%, 5.2% and 0.5%, respectively. CYP2C19 genotype had a significant effect on the clearance. Voriconazole trough concentrations in poor metabolizers were significantly higher than in intermediate metabolizers and extensive metabolizers alike. The volume of distribution increased with increased body weight. The oral bioavailability was substantially lower within 1 month after transplantation but increased with postoperative time. Dosing simulations indicated that during the early postoperative period, poor metabolizers could be treated with 150 mg intravenously or 250 mg orally twice daily; intermediate metabolizers with 200 mg intravenously or 350 mg orally twice daily; and extensive metabolizers with 300 mg intravenously twice daily.

CONCLUSIONS

Using a combination of CYP2C19 genotype and postoperative time to determine the initial voriconazole dosing regimens followed by therapeutic drug monitoring could help to advance individualized treatment in renal transplantation patients with invasive fungal infections.

Determination of voriconazole and co-administered drugs in plasma of pediatric cancer patients using UPLC-MS/MS: A key step towards personalized therapeutics

Untreated invasive aspergillosis results in high mortality rate in pediatric cancer patients. Voriconazole (VORI), the first line of treatment, requires strict dose monitoring because of its narrow therapeutic index and individual variation in plasma concentration levels. Commonly co-administered drugs; either Esomeprazole (ESO) or Ondansetron (OND) have reported drug-drug interaction with VORI that should adversely alter therapeutic outcomes of the latter. Although VORI, ESO and OND are co-administered to pediatric cancer patients, the combined effect of ESO and OND on the plasma concentration levels of VORI has not been fully explored. In this study, an accurate, reliable and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was developed and validated for simultaneous determination of VORI, ESO, and OND in ultra-low sample volumes (25 μL) of plasma of pediatric cancer patients. Based on the physicochemical properties of the studied drugs and internal standard, liquid-liquid extraction was successfully adopted with methyl t-butyl ether. Consistent and reproducible recovery of the three drugs and the internal standard were calculated using plasma and matrix matched samples (RE% > 72.97%, RSD < 8.29%). Chromatographic separation was carried out using UPLC with C18 column and a mobile phase of acetonitrile:water:methanol (70:25:5 V/V/V) at 0.3 mL/min. Mass spectrometric determination at positive electrospray ionization in the MRM mode was employed. The analysis was achieved within 4 min over a linear concentration range of 1.00-200.00 ng/mL for the three drugs. The assay validity was assessed as per the Food and Drug Administration guidelines for bioanalytical method validation, and satisfactory results were obtained. The accuracy and precision were within the acceptable limits for the three drugs in both quality control and incurred plasma samples. Matrix effect and process efficiency were investigated in neat solvent, post-extraction matrix, and plasma. Correlation of the plasma concentration levels of the three drugs revealed differences from the reported drug-drug interactions. This confirmed the need for simultaneous determination of VORI and co-administered drugs in order to achieve optimal therapeutic outcomes. To achieve this, analysis results of this study, genetic polymorphisms in CYP2C19 and clinical data will be used to establish one model incorporating all possible factors that might lead to variation in therapeutic outcomes.