Bioanalytical methods for the determination of itraconazole and hydroxyitraconazole: overview from clinical pharmacology, pharmacokinetic, pharmacodynamic and metabolism perspectives

Genetic variations of CYP3A4 on the metabolism of itraconazole in vitro

Itraconazole is a triazole anti-infective drug that has been proven to prevent and treat a variety of fungal and viral infections and has been considered to be a potential therapeutic remedy for COVID-19 treatment. In this study, we aimed to completely evaluate the impacts of Cytochrome P450 3A4 (CYP3A4) variant proteins and drug interactions on the metabolism of itraconazole in recombinant insect microsomes, and to characterize the potential mechanism of substrate selectivity. Incubations with itraconazole (0.2-15 μM) in the presence/absence of lopinavir or darunavir were assessed by CYP3A4 variants, and the metabolite hydroxyitraconazole concentrations were measured by UPLC-MS/MS. Our data showed that when compared with CYP3A4.1, 4 variants (CYP3A4.9, .10, .28 and .34) displayed no significant differences, and 3 variants (CYP3A4.14, .15 and .19) exhibited increased intrinsic clearance (CLint), whereas the remaining 17 variant proteins showed decreased enzyme activities for the catalysis of itraconazole. Moreover, the inhibitory effects of lopinavir and darunavir on itraconazole metabolism varied in different degrees. Furthermore, different changed trend of the kinetic parameters in ten variants (CYP3A4.5, .9, .10, .16, .19, .24, .28, .29, .31, and .33) were observed, especially CYP3A4.5 and CYP3A4.16, and this may be related to the metabolic site-heme iron atom distance. In the present study, we functionally analyzed the effects of 25 CYP3A4 protein variants on itraconazole metabolism for the first time, and provided comprehensive data on itraconazole metabolism in vitro. This may help to better assess the metabolism and elimination of itraconazole in clinic to improve the safety and efficacy of its clinical treatment and also provide new possibilities for the treatment of COVID-19.

A rapid UPLC-MS/MS assay for the simultaneous measurement of fluconazole, voriconazole, posaconazole, itraconazole, and hydroxyitraconazole concentrations in serum

BACKGROUND

Triazole antifungals are essential to the treatment and prophylaxis of fungal infections. Significant pharmacokinetic variability combined with a clinical need for faster turnaround times has increased demand for in-house therapeutic drug monitoring of these drugs, which is best performed using mass spectrometry-based platforms. However, technical and logistical obstacles to implementing these platforms in hospital laboratories have limited their widespread utilization. Here, we present the development and validation of a fast and simple ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method to measure fluconazole, voriconazole, posaconazole, itraconazole, and hydroxyitraconazole in human serum suitable for incorporation into a hospital clinical laboratory.

METHODS

Serum samples (20 µL) were prepared using protein precipitation in the presence of deuterated internal standards. Chromatographic separation was accomplished using reversed phase UPLC and analysis was performed using positive-mode electrospray ionization and collision-induced dissociation MS.

RESULTS

Total analytical run time was 3 min. All analytes demonstrated linearity (r2>0.998) from 0.1 to 10 µg/mL (1-100 µg/mL for fluconazole), acceptable accuracy and precision (%DEV<15% and %CV<15% at all levels tested), suitable stability under relevant storage conditions, and correlated well with reference laboratory results.

CONCLUSIONS

A simple and rapid UPLC-MS/MS method for monitoring multiple triazole antifungals was developed with a focus on the needs of hospital laboratories. The assay is suitable for clinical utilization and management of patients on these medications.

A semi-mechanistic pharmacokinetic model of saquinavir combined with itraconazole in HIV-1-positive patients

The mechanism of drug-drug interaction between saquinavir, a protease inhibitor used effectively for HIV/AIDS treatment, and itraconazole, an azole antifungal agent, is hypothesized to involve competitive inhibition at CYP3A4 enzyme, an important drug metabolizing enzyme in humans. The resulting interaction between these CYP3A4 substrates can be utilized clinically as a pharmacokinetic booster for prolonging saquinavir dosing regimen and/or decreasing saquinavir dose requirement in HIV/AIDS patients. To quantitatively describe this specific drug-drug interaction, based on the existing data, we aimed to develop a mathematical model incorporated with the competitive inhibition phenomena. PlotDigitizer was used to extract data from literature. Advance Continuous Simulating Language Extreme (ACSLX), a FORTRAN-based computer program, was employed as our developing tool. Our computer model simulations could successfully describe concentration-time course of saquinavir from selected pharmacokinetic studies in HIV-1-positive patients. To extend the model's utility as an aid in saquinavir dosage regimens, the developed model may be applied to other HIV/AIDS patients in genuine clinical settings.

Pharmacokinetic model for the inhibition of simvastatin metabolism by itraconazole

BACKGROUND

Concomitant use of simvastatin, a HMG-CoA reductase inhibitor, with a potent CYP3A4 inhibitor, itraconazole, can result in a serious drug-drug interaction induced severe adverse event, rhabdomyolysis. Even though pharmacokinetic data regarding such interaction are available, they cannot be used for quantitative prediction. For this reason, we aimed to develop a pharmacokinetic model for predicting the magnitude of inhibition of simvastatin metabolism by itraconazole.

METHODS

Published data involving pharmacokinetic of simvastatin, itraconazole, and pharmacokinetic interaction between simvastatin and itraconazole were selected from PubMed search. Serum simvastatin concentrations were subsequently extracted and used for model development. Advanced Continuous Simulating Language Extreme (ACSLX) was used for modeling.

RESULTS

The drug-drug interaction model between simvastatin and itraconazole was simultaneously modeled using a one compartment parent-metabolite model for simvastatin, and a two-compartment model for itraconazole.

CONCLUSION

The final drug-drug interaction model can adequately describe the actual simvastatin concentrations. Model application can be of advantage for dosing adjustment to avoid serious adverse effects resulted from concomitant use of both drugs.