Multiple Administrations of Itraconazole Increase Plasma Exposure to Pyrotinib in Chinese Healthy Adults

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.

Physiologically Based Pharmacokinetic Modeling to Simulate CYP3A4-Mediated Drug-Drug Interactions for Pyrotinib

INTRODUCTION

Pyrotinib is a newly developed tyrosine kinase inhibitor whose in vivo clearance relies heavily on cytochrome P450 3A4 (CYP3A4) activity. Clinical trials are ongoing to explore the effects of coadministration with CYP3A4 perpetrators on pyrotinib exposure. The present study aims to utilize physiologically based pharmacokinetic (PBPK) modeling to predict CYP3A4-based drug interactions of pyrotinib.

METHODS

Pyrotinib PBPK model was developed in the PK-Sim® multicompartmental physiology structure. Physiochemical parameters were obtained from the literature, and clearance-related parameters were optimized by fitting clinical single-dose pharmacokinetic data. Pharmacokinetic parameters from the model output were compared with the observed data to validate the model predictive performance. Using validated CYP3A4 perpetrator models, we conducted PBPK simulations for drug interactions in a virtual population to explore the impacts of comedication with these perpetrators.

RESULTS

The PBPK model accurately describes pyrotinib single- and multi-dose pharmacokinetics. The model also predicts dramatic exposure change of pyrotinib in the presence of itraconazole and rifampicin, though the impact of rifampicin is somewhat underestimated. According to model predictions, coadministration with typical potent or moderate CYP3A4 perpetrators increases pyrotinib concentration by over sixfold, extinguishing the possibility of dose adjustment for pyrotinib. A weak CYP3A4 inhibitor has minimal influence on pyrotinib pharmacokinetics.

CONCLUSION

PBPK modeling provides valuable information to avoid irrational medication when receiving pyrotinib chemotherapy.

Pyrotinib combining with radiotherapy on breast cancer with brain metastasis

With the extensive application of anti-human epidermal growth factor receptor-2 (HER2) targeted therapy, the prognosis of HER2-positive breast cancer brain metastasis (BCBM) has been improved greatly. Due to the lack of prospective randomized controlled studies; however, the treatment of active brain metastasis (BM) remains a difficulty in clinic. Based upon the retrospective studies, an effective approach of radiotherapy combined with pyrotinib in HER2-positive BCBM treatment was investigated in present research. In all, 29 patients who had active BM in HER2-positive breast cancer (BC) and underwent whole-brain radiotherapy (WBRT) combined with pyrotinib from January 2019 to May 2021 were enrolled. The progression-free survival (PFS), overall survival (OS), clinical benefit rate (CBR), objective response rate (ORR), and drug-related adverse events (AEs) were analyzed among patients undergoing WBRT combined with concurrent or sequence pyrotinib + capecitabine. After the systematic treatments using WBRT combined with pyrotinib + capecitabine, the mPFS and mOS of BM patients were 6.5 months and 15.5 months, respectively. PFS (7.2 vs 6.2 months, p = 0.038) and OS (19.0 vs 14.0 months, p = 0.014) were longer after sequence treatments than those after concurrent treatment. The central nervous system (CNS) ORR of sequence treatment was superior to that of concurrent treatment (80.4% vs 58.6%, p < 0.05). Vomiting (17.2%) and diarrhea (10.3%) were the most common adverse reactions ⩾ grade 3. WBRT combined with pyrotinib is safe and effective for the treatments of active BM in HER2-positive BC. WBRT combined with sequence pyrotinib + capecitabine is more effective and less toxic than concurrent treatment. Therefore, sequence treatment is potentially a preferred regimen for patients with active BM in HER2-positive BC. The size and number of BM lesions, presence or absence of hepatic metastasis, and combination mode of radiotherapy and targeted therapy are independent risk factors for active BM prognosis.

Pyrotinib-based treatments in HER2-positive breast cancer patients with brain metastases

OBJECTIVES

Extensive application of anti-HER2 targeted therapy improves significantly the HER2-positive advanced breast cancer (BC) prognosis, however, it is still difficult to treat brain metastasis. In current study, we explored effective approaches via combining pyrotinib to treat brain metastasis in patients with HER2-positive advanced BC based upon clinical data.

MATERIALS AND METHODS

Current study included 61 HER2-positive BC patients with brain metastases (BM) who were treated by pyrotinib-based regimens. The systemic regimens included pyrotinib combined with capecitabine, pyrotinib combined with nab-paclitaxel, and pyrotinib combined with vinorelbine. Patients' progression-free survival (PFS), overall survival (OS), clinical benefit rate (CBR) and objective response rate (ORR), as well as drug-related adverse events (AEs) in regard of each combination regimen were analyzed.

RESULTS

Pyrotinib-based systemic therapy resulted in 8.6 months median PFS (mPFS) and 18.0 months median OS (mOS) among the BM patients. Regarding different regimens, the combination of pyrotinib with nab-paclitaxel was superior to the combination with capecitabine and vinorelbine with respect to PFS and OS. The central nervous system (CNS) ORR did not showcase significant difference among 3 regimens, however, nab-paclitaxel combined regimen obtained the best peripheral ORR (84.6%) (p ≤ .05).

CONCLUSIONS

Pyrotinib-based combination therapy is safe for HER2-positive brain metastasis treatment. Compared with vinorelbine or capecitabine, pyrotinib combined with nab-paclitaxel is more effective with less toxicity, which is the preferable regimen for HER2-positive brain metastasis.KEY MESSAGESPresent investigation investigated effective methods through combining pyrotinib to treat brain metastasis with HER2-positive advanced brain cancer. The outcomes verified that pyrotinib-based combination therapy was safe and efficient to treat HER2-positive brain metastasis. Therefore, it is effective to treat brain metastasis applying anti-HER2 targeted therapies although pyrotinib showcases efficiency regarding its treatments for the metastasis.

Involvement of Transporters in Intestinal Drug-Drug Interactions of Oral Targeted Anticancer Drugs Assessed by Changes in Drug Absorption Time

(1) Background: Oral targeted anticancer drugs are victims of presystemic pharmacokinetic drug−drug interactions (DDI). Identification of the nature of these DDIs, i.e., enzyme-based or/and transporter-based, is challenging, since most of these drugs are substrates of intestinal and/or hepatic cytochrome P-450 enzymes and of intestinal membrane transporters. (2) Methods: Variations in mean absorption time (MAT) between DDIs and control period (MAT ratios < 0.77 or >1.30) have been proposed to implicate transporters in DDIs at the intestinal level. This methodology has been applied to a large set of oral targeted anticancer drugs (n = 54, involved in 77 DDI studies), from DDI studies available either in the international literature and/or in publicly accessible FDA files. (3) Results: Significant variations in MAT were evidenced in 33 DDI studies, 12 of which could be explained by modulation of an efflux transporter. In 21 DDI studies, modulation of efflux transporters could not explain the MAT variation, suggesting a possible relevant role of influx transporters in the intestinal absorption. (4) Conclusions: This methodology allows one to suggest the involvement of intestinal transporters in DDIs, and should be used in conjunction with in vitro methodologies to help understanding the origin of DDIs.

Prediction of pyrotinib exposure based on physiologically-based pharmacokinetic model and endogenous biomarker

Pyrotinib, a novel irreversible epidermal growth factor receptor dual tyrosine kinase inhibitor, is mainly (about 90%) eliminated through cytochrome P450 (CYP) 3A mediated metabolism in vivo. Meanwhile, genotype is a key factor affecting pyrotinib clearance and 4β-hydroxycholesterol is an endogenous biomarker of CYP3A activity that can indirectly reflect the possible pyrotinib exposure. Thus, it is necessary to evaluate the clinical drug-drug interactions (DDI) between CYP3A perpetrators and pyrotinib, understand potential exposure in specific populations including liver impairment and geriatric populations, and explore the possible relationships among pyrotinib exposure, genotypes and endogenous biomarker. Physiologically-based pharmacokinetic (PBPK) model can be used to replace prospective DDI studies and evaluate external and internal factors that may influence system exposure. Herein, a basic PBPK model was firstly developed to evaluate the potential risk of pyrotinib coadministration with strong inhibitor and guide the clinical trial design. Subsequently, the mechanistic PBPK model was established and used to quantitatively estimate the potential DDI risk for other CYP3A modulators, understand the potential exposure of specific populations, including liver impairment and geriatric populations. Meanwhile, the possible relationships among pyrotinib exposure, genotypes and endogenous biomarker were explored. With the help of PBPK model, the DDI clinical trial of pyrotinib coadministration with strong inhibitor has been successfully completed, some DDI clinical trials may be waived based on the predicted results and clinical trials in specific populations can be reasonably designed. Moreover, the mutant genotypes of CYP3A4*18A and CYP3A5*3 were likely to have a limited influence on pyrotinib clearance, and the genotype-independent linear correlation coefficient between endogenous biomarker and system exposure was larger than 0.6. Therefore, based on the reliable predicted results and the linear correlations between pyrotinib exposure and endogenous biomarker, dosage adjustment of pyrotinib can be designed for clinical practice.

Differential effects of ketoconazole, fluconazole, and itraconazole on the pharmacokinetics of pyrotinib in vitro and in vivo

It has been reported that drug-drug interactions (DDIs) can affect the pharmacokinetics and pharmacodynamics of various oral drugs. To better understand the effects of azole antifungal drugs (ketoconazole, fluconazole, and itraconazole) on pyrotinib’s pharmacokinetics, DDIs between pyrotinib and three azoles were studied with Sprague-Dawley (SD) rat liver microsomes in vitro. Additionally, in vivo pyrotinib metabolic experiment was also performed. Twenty-four male SD rats were randomly divided into four groups: the ketoconazole (40 mg/kg), fluconazole (40 mg/kg), itraconazole (40 mg/kg), and the control group. UPLC-MS/MS was used for the determination of Pyrotinib’s plasma concentration in rats. In vitro experiments showed that IC₅₀ values of ketoconazole, fluconazole and itraconazole were 0.06, 11.55, and 0.27 μM, respectively, indicating that these drugs might reduce the clearance rate of pyrotinib at different degrees. In rat studies, coadministration of pyrotinib with ketoconazole or fluconazole could dramatically increase the C_max and AUC_(0-t) values and decrease the clearance rate of pyrotinib, especially for ketoconazole. However, coadministration with itraconazole had no impact on the pharmacokinetic characters of pyrotinib. These data indicated that ketoconazole and fluconazole could significantly decrease the metabolism of pyrotinib both in vitro and in vivo. More attentions should be paid when pyrotinib is combined with azole antifungal drugs in clinic although further investigation is still required in future.

Clinical study of drug-drug interaction between omeprazole and pyrotinib after meal

AIMS

We aimed to investigate the effect of omeprazole on the pharmacokinetics (PK) of pyrotinib and determine the safety of this combination in healthy Chinese volunteers.

METHODS

Eighteen healthy volunteers were enrolled in this single-dose and self-controlled study. Pyrotinib (400 mg per oral) was administered 30 minutes after the standard meal. Omeprazole was administered from day 6 (D6) to D10 (40 mg, per oral). On D10, the subjects took omeprazole under fasting conditions, followed by pyrotinib 30 minutes after the standard meal. Blood samples for PK analyses in each phase were collected for analysing the drug concentration. Safety was assessed via clinical laboratory tests and physical examinations.

RESULTS

Compared with a single dose of pyrotinib, pyrotinib coadministered with omeprazole showed no significant difference in exposure, elimination, half-life and apparent clearance rate. The mixed-effects model revealed that the least-squares geometric mean ratios of area under the concentration-time curve (AUC)_0-t , AUC_0-∞ and maximum plasma concentration (C_max, 90% confidence intervals) of pyrotinib alone and pyrotinib coadministered with omeprazole were 0.94 (0.82, 1.08), 0.94 (0.83, 1.08) and 0.91 (0.806, 1.038), respectively, indicating the absence of significant differences in AUC_0-t , AUC_0-∞ and C_max . During the treatment period, 6 subjects (33.3%) reported 8 adverse events during pyrotinib monotherapy and omeprazole administration, respectively; 10 subjects (55.6%) reported 34 adverse events in the combined administration phase.

CONCLUSION

Omeprazole, a proton-pump inhibitor, did not significantly impact the PK properties of pyrotinib, and a good safety profile was observed on coadministration.