Dexamethasone is a dose-dependent perpetrator of drug-drug interactions: implications for use in people living with HIV

The CYP3A inducer dexamethasone affects the pharmacokinetics of sunitinib by accelerating its metabolism in rats

Sunitinib, a novel anti-tumor small molecule targeting VEGFR, is prescribed for advanced RCC and GISTs. Sunitinib is primarily metabolized by the CYP3A enzyme. It is well-known that dexamethasone serves as a potent inducer of this enzyme system. Nonetheless, the effect of dexamethasone on sunitinib metabolism remains unclear. This study examined the effect of dexamethasone on the pharmacokinetics of sunitinib and its metabolite N-desethyl sunitinib in rats. The plasma levels of both compounds were measured using UHPLC-MS/MS. Pharmacokinetic parameters and metabolite ratio values were calculated. Compare to control group, the low-dose dexamethasone group and high-dose dexamethasone group decreased the AUC(0-t) values of sunitinib by 47 % and 45 %, respectively. Meanwhile, the AUC(0-t) values of N-desethyl sunitinib were increased by 2.2-fold and 2.4-fold in low-dose dexamethasone group and high-dose dexamethasone group, respectively. The CL values for sunitinib were both approximately 45 % higher in the two dexamethasone groups. Remarkably, metabolite ratio values increased over 5-fold in both low-dose dexamethasone group and high-dose dexamethasone group, indicating a significant enhancement of sunitinib metabolism by dexamethasone. Moreover, the total levels of sunitinib and its metabolite are also significantly increased. The impact of interactions on sunitinib metabolism, as observed with CYP3A inducers such as dexamethasone, is a crucial consideration for clinical practice. To optimize the dosage and prevent adverse drug events, therapeutic drug monitoring can be employed to avoid the toxicity from such interactions.

Review of drug-drug interactions in patients with prostate cancer

OBJECTIVE

The objective of this review is to provide an overview of common drug-drug interactions (DDIs) associated with prostate cancer treatments and outline recommendations for managing polypharmacy.

DATA SOURCES

A literature search of PubMed, Embase, and CINAHL was carried out to identify pharmacokinetic and pharmacodynamic changes caused by DDIs that are relevant for prostate cancer patients, DDIs between prostate cancer therapies and co-administered medications (both prescription and over-the-counter), and measures to prevent DDIs. Medication package inserts were used to identify the impact of DDI on the prostate cancer therapy and suggested interventions.

DATA SUMMARY

No DDIs are expected for the LHRH agonists leuprolide acetate, histrelin, goserelin, or leuprolide mesylate. However, DDIs have been reported for GnRH antagonists, anti-androgens, PARP inhibitors, and taxanes. Although there are no confirmed DDIs for sipuleucel-T to date, it is not generally recommended to use sipuleucel-T concurrently with immunosuppressive medications. Interventions to prevent DDIs include the use of software that can detect clinically significant DDIs, up-to-date medication reconciliation, the inclusion of dedicated clinical pharmacists in cancer treatment teams, and patient/caregiver education.

CONCLUSIONS

Prostate cancer patients have a high risk of potential DDIs due to numerous new anti-cancer therapies, the increased use of treatment combinations, and the likelihood of comorbid conditions also requiring drug therapy. Drug-drug interaction screening software, up-to-date medication reconciliation, inclusion of oncology pharmacists on healthcare teams, and patient/caregiver education will aid the development of treatment plans that focus on achieving an optimal risk-benefit profile whilst reducing the risk of DDIs.

Preclinical murine models for the testing of antimicrobials against Mycobacterium abscessus pulmonary infections: Current practices and recommendations

Mycobacterium abscessus, a rapidly growing nontuberculous mycobacterium, is increasingly recognized as an important pathogen of the human lung, disproportionally affecting people with cystic fibrosis (CF) and other susceptible individuals with non-CF bronchiectasis and compromised immune functions. M. abscessus infections are extremely difficult to treat due to intrinsic resistance to many antibiotics, including most anti-tuberculous drugs. Current standard-of-care chemotherapy is long, includes multiple oral and parenteral repurposed drugs, and is associated with significant toxicity. The development of more effective oral antibiotics to treat M. abscessus infections has thus emerged as a high priority. While murine models have proven instrumental in predicting the efficacy of therapeutic treatments for M. tuberculosis infections, the preclinical evaluation of drugs against M. abscessus infections has proven more challenging due to the difficulty of establishing a progressive, sustained, pulmonary infection with this pathogen in mice. To address this issue, a series of three workshops were hosted in 2023 by the Cystic Fibrosis Foundation (CFF) and the National Institute of Allergy and Infectious Diseases (NIAID) to review the current murine models of M. abscessus infections, discuss current challenges and identify priorities toward establishing validated and globally harmonized preclinical models. This paper summarizes the key points from these workshops. The hope is that the recommendations that emerged from this exercise will facilitate the implementation of informative murine models of therapeutic efficacy testing across laboratories, improve reproducibility from lab-to-lab and accelerate preclinical-to-clinical translation.

Case report: dose-dependent interaction between dexamethasone and voriconazole in severely ill patients with non-Hodgkin's lymphoma being treated for invasive pulmonary aspergillosis

Background

Voriconazole is primarily metabolized by CYP2C19 and CYP3A4. Drug interactions that affect this pathway can alter its plasma exposures, resulting in untargeted voriconazole concentrations.

Case summary

In this case report, we describe the case of a 64-year-old man who was treated for non-Hodgkin's lymphoma with continuous glucocorticoids co-administrated with voriconazole against invasive pulmonary aspergillosis. A decrease in trough concentration (Cmin) of voriconazole was observed and related with co-administration of dexamethasone in the patient carrying the CYP2C19 *1*2 genotype: voriconazole Cmin/dose ratios of 0.018 (0.1 mg L-1/5.7 mg kg-1 day-1), 0.18 (1 mg L-1/5.7 mg kg-1 day-1), and 0.23 (2 mg L-1/8.6 mg kg-1 day-1) at dexamethasone doses of 20, 12.5, and 2.5 mg, respectively. Sub-therapeutic voriconazole Cmin was associated with high- and moderate-dose dexamethasone (20 and 12.5 mg), leading to failure of antifungal treatment.

Conclusion

The extent of voriconazole-dexamethasone interaction was determined by the dose of dexamethasone and associated with the CYP2C19 *1*2 genotype. Therapeutic drug monitoring of voriconazole is necessary to avoid clinically relevant interactions for optimal antifungal therapy.

Effect of letermovir initiation on tacrolimus concentrations among lung transplant recipients receiving concomitant azole antifungal prophylaxis

BACKGROUND

The antiviral letermovir has been increasingly used as off-label cytomegalovirus prophylaxis in solid organ transplant recipients. Observational studies have reported notable increases in tacrolimus (FK) exposure following letermovir; however, whether a significant interaction occurs in the setting of existing moderate-to-strong CYP3A4 inhibition is unknown. Therefore, the purpose of this study was to evaluate FK trough changes before and after letermovir among lung transplant recipients receiving azole antifungal prophylaxis.

METHODS

This retrospective cohort study included lung transplant recipients newly initiated on letermovir between 2019-2022 following valganciclovir intolerance. Tacrolimus doses and concentrations were collected up to 30 days before and after the letermovir start date. No pre-emptive FK dose adjustments occurred prior to letermovir initiation. Patients admitted to the hospital or lacking an appropriately timed trough in the pre- or post-period were excluded.

RESULTS

A total of 78 lung transplant recipients receiving FK (1.5 mg median total daily dose) and itraconazole (56.4%), isavuconazole (25.6%) or posaconazole (17.9%) prophylaxis were included. Letermovir was started at a median of 8.4 months post-transplant. The pre-/post-letermovir median FK trough was 9.6/9.0 ng/mL (p = .151), median dose-corrected trough was 4.2/4.7 ng/mL/mg (+11.9%, p = .032), and median weight-based dose-corrected trough was 362/326 [ng/mL]/[mg/kg/day] (-9.9%, p = .036). There was no significant difference in the proportion of patients within their goal trough range before and after letermovir initiation (62% vs. 72%, p = .229).

CONCLUSION

Empiric FK dose adjustments do not appear warranted before letermovir initiation in lung transplant recipients receiving antifungal prophylaxis with moderate-to-strong CYP3A4 inhibitors.

Drug-drug interactions between COVID-19 therapeutics and antiretroviral treatment: the evidence to date

INTRODUCTION

With new effective treatments for SARS-CoV-2, patient outcomes have greatly improved. However, new medications bring a risk of drug interactions with other medications. People living with HIV (PLWH) are at particular risk for these interactions due to heightened risk of immunosuppression, polypharmacy, and overlap in affected organs. It is critical to identify drug interactions are a significant barrier to care for PLWH. Establishing a better understanding of the pharmacologic relationships between COVID-19 therapies and antiretrovirals will improve patient-centered care in COVID-19.

AREAS COVERED

Potential drug-drug interactions between Human Immunodeficiency Virus (HIV) and COVID-19 treatments are detailed and reviewed here. The mechanisms seen in these interactions include alterations in metabolic enzymes, drug transporters, pharmacoenhancement, and organ toxicities. We also review the limitations and solutions that can be used to combat drug-drug interactions between these two disease states.

EXPERT OPINION

While current drug interactions are relatively mild between HIV and COVID-19 therapies, improvements in identifying these beforehand must take place as new therapies are approved. Antiretroviral therapy (ART) is essential in PLWH and must be maintained when treating COVID-19. As advancements in care occur, there is the possibility that newly approved drugs may have additional unknown interactions.

Physiologically-Based Pharmacokinetic Modeling Approaches for Patients with SARS-CoV-2 Infection: A Case Study with Imatinib

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection, which causes coronavirus disease 2019 (COVID‐19), manifests as mild respiratory symptoms to severe respiratory failure and is associated with inflammation and other physiological changes. Of note, substantial increases in plasma concentrations of α₁‐acid‐glycoprotein and interleukin‐6 have been observed among patients admitted to the hospital with advanced SARS‐CoV‐2 infection. A physiologically based pharmacokinetic (PBPK) approach is a useful tool to evaluate and predict disease‐related changes on drug pharmacokinetics. A PBPK model of imatinib has previously been developed and verified in healthy people and patients with cancer. In this study, the PBPK model of imatinib was successfully extrapolated to patients with SARS‐CoV‐2 infection by accounting for disease‐related changes in plasma α₁‐acid‐glycoprotein concentrations and the potential drug interaction between imatinib and dexamethasone. The model demonstrated a good predictive performance in describing total and unbound imatinib concentrations in patients with SARS‐CoV‐2 infection. PBPK simulations highlight that an equivalent dose of imatinib may lead to substantially higher total drug concentrations in patients with SARS‐CoV‐2 infection compared to that in patients with cancer, while the unbound concentrations remain comparable between the 2 patient populations. This supports the notion that unbound trough concentration is a better exposure metric for dose adjustment of imatinib in patients with SARS‐CoV‐2 infection, compared to the corresponding total drug concentration. Potential strategies for refinement and generalization of the PBPK modeling approach in the patient population with SARS‐CoV‐2 are also provided in this article, which could be used to guide study design and inform dose adjustment in the future.