CYP2C19 Genotype-Dependent Pharmacokinetic Drug Interaction Between Voriconazole and Ritonavir-Boosted Atazanavir in Healthy Subjects

Time Course of the Interaction Between Oral Short-Term Ritonavir Therapy with Three Factor Xa Inhibitors and the Activity of CYP2D6, CYP2C19, and CYP3A4 in Healthy Volunteers

BACKGROUND

We investigated the effect of a 5-day low-dose ritonavir therapy, as it is used in the treatment of COVID-19 with nirmatrelvir/ritonavir, on the pharmacokinetics of three factor Xa inhibitors (FXaI). Concurrently, the time course of the activities of the cytochromes P450 (CYP) 3A4, 2C19, and 2D6 was assessed.

METHODS

In an open-label, fixed sequence clinical trial, the effect and duration of a 5-day oral ritonavir (100 mg twice daily) treatment on the pharmacokinetics of three oral microdosed FXaI (rivaroxaban 25 µg, apixaban 25 µg, and edoxaban 50 µg) and microdosed probe drugs (midazolam 25 µg, yohimbine 50 µg, and omeprazole 100 µg) was evaluated in eight healthy volunteers. The plasma concentrations of all drugs were quantified using validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods and pharmacokinetics were analysed using non-compartmental analyses.

RESULTS

Ritonavir increased the exposure of apixaban, edoxaban, and rivaroxaban, but to a different extent the observed area under the plasma concentration-time curve (geometric mean ratio 1.29, 1.46, and 1.87, respectively). A strong CYP3A4 inhibition (geometric mean ratio > 10), a moderate CYP2C19 induction 2 days after ritonavir (0.64), and no alteration of CYP2D6 were observed. A CYP3A4 recovery half-life of 2.3 days was determined.

CONCLUSION

This trial with three microdosed FXaI suggests that at most the rivaroxaban dose should be reduced during short-term ritonavir, and only in patients receiving high maintenance doses. Thorough time series analyses demonstrated differential effects on three different drug-metabolising enzymes over time with immediate profound inhibition of CYP3A4 and only slow recovery after discontinuation.

CLINICAL TRIAL REGISTRATION

EudraCT number: 2021-006643-39.

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.

The effects of nirmatrelvir/ritonavir on tacrolimus levels in lung transplant recipients: A single-center study

BACKGROUND

Lung transplant recipients (LTRs) have a higher risk of hospitalization and mortality due to COVID-19 compared with the immunocompetent population. The use of nirmatrelvir/ritonavir (NR), an effective oral treatment for COVID-19, is quite challenging due to its potent drug-drug interactions with immunosuppressants and azole antifungals. As there are few clinical reports of the use of NR in LTRs, we measured tacrolimus levels in patients receiving NR in our hospital to improve safety when prescribing NR.

METHODS

In total, 48 adult LTRs who received NR between November 19, 2022, and January 19, 2023, at China-Japan Friendship Hospital were retrospectively included and followed for 20 days after initiating NR. Tacrolimus was held at least 12 h before initiating NR and re-administered based on the trough levels after completing NR treatment. All concomitant medications, drug concentrations, laboratory results, and genotypes were recorded and analyzed.

RESULTS

Most patients showed stable tacrolimus trough levels despite high individual variability. Four patients exhibited supratherapeutic trough levels of tacrolimus (more than 15 ng/mL). Two patients who received 0.5 mg of tacrolimus during NR treatment had trough levels below 3.0 ng/mL. In addition, we found that in 13 patients, the trough levels were 130% of baseline after cessation of tacrolimus, and logistic regression revealed that increased trough level was significantly associated with age more than 60 years.

CONCLUSIONS

NR can be safely used in LTRs with close monitoring of tacrolimus levels and appropriate dose adjustments. However, more attention should be paid to elderly patients, as NR may more severely affect their drug metabolism. Due to the limited sample size, further studies are needed to guide the optimal use of tacrolimus following treatment with NR and explore the risk factors significantly affecting the interactions between NR and tacrolimus.

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Rates of Divergent Pharmacogenes in a Psychiatric Cohort of Inpatients with Depression-Arguments for Preemptive Testing

Background: The international drug agencies annotate pharmacogenes for many years. Pharmacogenetic testing is thus far only established in few settings, assuming that only few patients are actually affected by drug-gene interactions. Methods: 108 hospitalized patients with major depressive disorder were genotyped for CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NAT2, DPYD; VKORC1 and TMTP. Results: We found 583 (mean 5.4, median 5) divergent phenotypes (i.e., divergent from the common phenotypes considered normal, e.g., extensive metabolizer) in the 12 analyzed pharmacokinetic genes. The rate for at least one divergent phenotype was 100% in our cohort for CYP, but also for all 12 important pharmacogenes: patients had at least two divergent phenotypes. Compared to a large Danish cohort, CYP2C9 NM and IM status, CYP2C19 UM, CYP2D6 UM and DYPD (GAS 0, 1, 2) genotypes differed statistical significantly. For CYP2D6 and CYP2C19, 13% of the patients were normal metabolizers for both enzymes in our cohort, but this value was 27.3% in the Danish cohort, which is a highly significant difference (p < 0.0001). Conclusion: Divergent phenotypes in pharmacogenes are not the exception, but the rule. Patients with divergent phenotypes seem more prone for hospitalization, emphasizing the need for pre-emptive testing to avoid inefficacy and adverse drug effects in all patients.

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.

Application of a Physiologically Based Pharmacokinetic Model to Characterize Time-dependent Metabolism of Voriconazole in Children and Support Dose Optimization

Background: Voriconazole is a potent antifungal drug with complex pharmacokinetics caused by time-dependent inhibition and polymorphisms of metabolizing enzymes. It also exhibits different pharmacokinetic characteristics between adults and children. An understanding of these alterations in pharmacokinetics is essential for pediatric dose optimization.

Objective: To determine voriconazole plasma exposure in the pediatric population and further investigate optimal dosage regimens.

Methods: An adult and pediatric physiologically based pharmacokinetic (PBPK) model of voriconazole, integrating auto-inhibition of cytochrome P450 3A4 (CYP3A4) and CYP2C19 gene polymorphisms, was developed. The model was evaluated with visual predictive checks and quantitative measures of the predicted/observed ratio of the area under the plasma concentration-time curve (AUC) and maximum concentration (C_max). The validated pediatric PBPK model was used in simulations to optimize pediatric dosage regimens. The probability of reaching a ratio of free drug (unbound drug concentration) AUC during a 24-h period to minimum inhibitory concentration greater than or equal to 25 (fAUC_24h/MIC ≥ 25) was assessed as the pharmacokinetic/pharmacodynamic index.

Results: The developed PBPK model well represented voriconazole's pharmacokinetic characteristics in adults; 78% of predicted/observed AUC ratios and 85% of C_max ratios were within the 1.25-fold range. The model maintained satisfactory prediction performance for intravenous administration in pediatric populations after incorporating developmental changes in anatomy/physiology and metabolic enzymes, with all predicted AUC values within 2-fold and 73% of the predicted C_max within 1.25-fold of the observed values. The simulation results of the PBPK model suggested that different dosage regimens should be administered to children according to their age, CYP2C19 genotype, and infectious fungal genera.

Conclusion: The PBPK model integrating CYP3A4 auto-inhibition and CYP2C19 gene polymorphisms successfully predicted voriconazole pharmacokinetics during intravenous administration in children and could further be used to optimize dose strategies. The infectious fungal genera should be considered in clinical settings, and further research with large sample sizes is required to confirm the current findings.

[Liquid chromatography tandem mass spectrometry for therapeutic drug monitoring of voriconazole in heat-inactivated blood samples: its application during COVID-19 pandemic]

OBJECTIVE

To investigate the effect of heat inactivation (56℃for 30 min) of SARS-CoV-2 on the results of therapeuticdrug monitoring (TDM) of voriconazole by liquid chromatography tandem mass spectrometry (LC-MS/MS).

METHODS

We collected clinical blood samples from voriconazole-treated patients in heparinized tubes and sterilized the surface of the tubes with 75% ethanol. The whole blood samples were centrifuged to separate the plasma with or without prior heat inactivation, or only the separated plasma was heat inactivated. Heat inactivation of the samples was carried out at 56 ℃ for 30 min followed by protein precipitation with acetonitrile or ethanol. The plasma standard and quality control samples were inactivated in an identical manner and tested with LC-MS/MS along with the treated samples.

RESULTS

The optimized method showed a high imprecision (with mean intra- and inter-day imprecisions of 3.59% and 2.81%, respectively) and a high accuracy (mean 97.37%) for detecting voriconazole in the inactivated samples at different concentration levels. Sample preparation with acetonitrile or ethanol resulted in a high mean recovery (100.56% or 95.90%) with minimal mean matrix effect (102.85% or 93.62%). The measured voriconazole concentrations in inactivated whole blood, inactivated plasma and the samples without inactivation all showed good linear correlations with correlation coefficients all greater than 0.99.

CONCLUSIONS

Heat inactivation at 56 ℃ for 30 min combined with ethanol sample preparation only has limited effects to affect LC-MS-based voriconazole concentration measurement in whole blood samples collected in heparinized tubes, and can be used for therapeutic drug monitoring of voriconazole during the ongoing COVID-19 pandemic.

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

Purpose of Review

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

Recent Findings

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

Summary

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

Drug-drug-gene interactions and adverse drug reactions

The economic and health burden caused by adverse drug reactions has increased dramatically in the last few years. This is likely to be mediated by increasing polypharmacy, which increases the likelihood for drug–drug interactions. Tools utilized by healthcare practitioners to flag potential adverse drug reactions secondary to drug–drug interactions ignore individual genetic variation, which has the potential to markedly alter the severity of these interactions. To date there have been limited published studies on impact of genetic variation on drug–drug interactions. In this review, we establish a detailed classification for pharmacokinetic drug–drug–gene interactions, and give examples from the literature that support this approach. The increasing availability of real-world drug outcome data linked to genetic bioresources is likely to enable the discovery of previously unrecognized, clinically important drug–drug–gene interactions.

Identification of Cytochrome P450-Mediated Drug-Drug Interactions at Risk in Cases of Gene Polymorphisms by Using a Quantitative Prediction Model

BACKGROUND AND OBJECTIVE

The magnitude of drug-drug interactions mediated by cytochrome P450 (CYP) may depend on the genotype of polymorphic cytochromes. The objective of this study was to identify drug-drug interactions with greater magnitude in CYP variant groups than in extensive metabolizers.

METHODS

The in-vivo mechanistic static model was used to predict the area under the curve ratio of drug-drug interactions. Five cytochromes (CYP3A4/5, 2D6, 2C9, 2C19, 1A2) and five groups of genotypes for each polymorphic cytochrome (CYP2D6, 2C9, 2C19) were considered. The area under the curve ratios were calculated for all combinations and all genotypes for 196 substrates and 96 inhibitors. Among the strongest interactions (area under the curve ratio greater than 5), two levels of gene sensitivity of drug-drug interactions were defined: the intermediate sensitivity, with a three- to five-fold stronger interaction in genotype groups other than in extensive metabolizers, and the high sensitivity, with a more than five-fold stronger interaction than in genotype groups other than extensive metabolizers.

RESULTS

A red list of 104 interactions with a sensitivity greater than 3, involving 13 substrates and 24 interactors was obtained. There were 59 and 45 cases of high and intermediate sensitivity, respectively. The genotypes associated with a high sensitivity were CYP2D6 *3-8 *3-8 (sensitivity up to 24.3) and CYP2C19 *2-3*2-3 (sensitivity up to 37.8).

CONCLUSIONS

A cytochrome polymorphism may lead to major drug-drug interactions in poor metabolizers, while these interactions may not be significant in extensive metabolizers. Among the 104 cases studied, the interaction could be of ca. 30-fold larger magnitude in the worst case. Genotyping of the patient and/or therapeutic drug monitoring of the substrate should be carried out when an association mentioned in the red list is prescribed. The concept of gene sensitivity of drug-drug interactions appears promising for the development of precision medicine.

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.

Pharmacokinetics and pharmacodynamics of cytochrome P450 inhibitors for HIV treatment

INTRODUCTION

Drugs used in HIV treatment; all protease inhibitors, some non-nucleoside reverse transcriptase inhibitors, and pharmacoenhancers ritonavir and cobicistat can inhibit cytochrome P450 (CYP) enzymes. CYP inhibition can cause clinically significant drug-drug interactions (DDI), leading to increased drug exposure and potential toxicity. Areas covered: A complete understanding of pharmacodynamics and CYP-mediated DDI is crucial to prevent adverse side effects and to achieve optimal efficacy. We summarized the pharmacodynamics of all the CYP inhibitors used for HIV treatment, followed by a discussion of drug interactions between these CYP inhibitors and other drugs, and a discussion on the effect of CYP polymorphisms. We also discussed the potential advancements in improving the pharmacodynamics of these CYP inhibitors by using nanotechnology strategy. Expert opinion: The drug-interactions in HIV patients receiving ARV drugs are complicated, especially when patients are on CYP inhibitors-based ART regimens. Therefore, evaluation of CYP-mediated drug interactions is necessary prior to prescribing ARV drugs to HIV subjects. To improve the treatment efficacy and minimize DDI, novel approaches such as nanotechnology may be the potential alternative approach. However, further studies with large cohort need to be conducted to provide strong evidence for the use of nano-formulated ARVs to effectively treat HIV patients.

Drug-drug interactions between triazole antifungal agents used to treat invasive aspergillosis and immunosuppressants metabolized by cytochrome P450 3A4

Patients undergoing treatment with immunosuppressant drugs following solid organ or hematopoietic stem cell transplantation are at particular risk for development of serious infections such as invasive aspergillosis. Four triazole antifungal drugs, voriconazole, posaconazole, itraconazole, and isavuconazole, are approved to treat invasive aspergillosis either as first- or second-line therapy. All of these agents are inhibitors of cytochrome P450 3A4, which plays a key role in metabolizing immunosuppressant drugs such as cyclosporine, tacrolimus, and sirolimus. Thus, co-administration of a triazole antifungal drug with these immunosuppressant drugs can potentially increase plasma concentrations of the immunosuppressant drugs, thereby resulting in toxicity, or upon discontinuation, inadvertently decrease the respective concentrations with increased risk of rejection or graft-versus-host disease. In this article, we review the evidence for the extent of inhibition of cytochrome P450 3A4 by each of these triazole antifungal drugs and assess their effects on cyclosporine, tacrolimus, and sirolimus. We also consider other factors affecting interactions of these two classes of drugs. Finally, we examine recommendations and strategies to evaluate and address those potential drug-drug interactions in these patients.

Notable Drug-Drug Interaction Between Etizolam and Itraconazole in Poor Metabolizers of Cytochrome P450 2C19

In this study, impact of a polymorphism of CYP2C19 on drug-drug interaction (DDI) was examined for etizolam. The effect of itraconazole (a strong CYP3A inhibitor) on the pharmacokinetics of etizolam (a substrate of CYP2C19 and CYP3A) was assessed in both extensive metabolizers (EMs) and poor metabolizers (PMs) of CYP2C19. Sixteen participants (8 EMs and 8 PMs) received a single oral dose of etizolam (0.25 mg) on day 1. The participants ingested itraconazole (200 mg twice a day) on days 2-5. On day 5, participants received an oral dose of etizolam (0.25 mg) again. Before coadministration of itraconazole (day 1), the area under the time-plasma concentration curve from time zero to infinity (AUC_∞ ) of etizolam was higher in PMs than in EMs (2.65-fold, P < .01). Coadministration of itraconazole increased the AUC_∞ of etizolam 1.66-fold and 2.34-fold in EMs and PMs, respectively (day 5). Consequently, AUC_∞ was 6.18-fold higher in PMs with itraconazole than that in EMs without itraconazole. The increase by itraconazole was larger in PMs (P < .01). In heterozygous EMs (hEMs), AUC_∞ was simulated to be 2.56-fold higher with itraconazole than that in EMs without itraconazole. We found that in vitro measurements of fraction metabolized (f_m ) using the liver microsome prepared from PM donors would be helpful to predict polymorphism-dependent DDIs. These results suggest that the PMs and hEMs of a polymorphic CYP would be at higher risk of DDIs relative to EMs for drugs metabolized by both polymorphic and nonpolymorphic CYPs such as etizolam.

Pharmacogenomics of Drug Metabolizing Enzymes and Transporters: Relevance to Precision Medicine

The interindividual genetic variations in drug metabolizing enzymes and transporters influence the efficacy and toxicity of numerous drugs. As a fundamental element in precision medicine, pharmacogenomics, the study of responses of individuals to medication based on their genomic information, enables the evaluation of some specific genetic variants responsible for an individual’s particular drug response. In this article, we review the contributions of genetic polymorphisms to major individual variations in drug pharmacotherapy, focusing specifically on the pharmacogenomics of phase-I drug metabolizing enzymes and transporters. Substantial frequency differences in key variants of drug metabolizing enzymes and transporters, as well as their possible functional consequences, have also been discussed across geographic regions. The current effort illustrates the common presence of variability in drug responses among individuals and across all geographic regions. This information will aid health-care professionals in prescribing the most appropriate treatment aimed at achieving the best possible beneficial outcomes while avoiding unwanted effects for a particular patient.