Development of a rapid HPLC-fluorescence method for monitoring warfarin metabolites formation: In vitro studies for evaluating the effect of piperine on warfarin metabolism and plasma coagulation.

Warfarin, a widely prescribed anticoagulant, is highly effective for various coagulation disorders. However, its efficacy is limited by a narrow therapeutic index and frequent drug interactions, especially those involving metabolism by Cytochrome P450 (CYP450) enzymes. Piperine, found in black and long pepper, possesses blood-thinning properties and has been observed to inhibit CYP3A and CYP2C enzymes linked to warfarin metabolism. This study investigated the effect of piperine on warfarin metabolism in liver microsomes using a rapid and sensitive HPLC-Fluorescence method. The use of PFP (pentafluorophenyl) column with core shell particles provided the selectivity and resolution to resolve warfarin and its 4-, 6-, 7-, and 10-hydroxy metabolites in addition to the internal standard naproxen in less than 3 min. This is the fastest analytical assay for warfarin and its major metabolites reported to date, making it ideal for metabolic studies. The applicability of the method was demonstrated by monitoring the metabolism of S-warfarin in human and rat liver microsomes, and evaluating the inhibitory effect of piperine on metabolite formation. The results showed that piperine inhibited the formation of the major metabolite, 7-hydroxywarfarin, with half-maximal inhibitory concentration (IC50) 14.2 µM and 3.2 µM in human and rat liver microsomes, respectively. Furthermore, coagulation studies in vitro using rat plasma showed that piperine does not affect prothrombin time (PT) and activated partial thromboplastin time (aPTT). This study suggested that piperine may present a potential drug interaction with warfarin at the metabolism level, but has no direct effect on the activation of the extrinsic or intrinsic coagulation cascades. Further clinical investigation is therefore required, as piperine may increase the bioavailability of warfarin, thus increasing risk of serious adverse events in patients.

HPLC methods for studying pharmacokinetics of tivozanib and in vitro metabolic interaction with dexamethasone in rat.

Tivozanib is a recently approved tyrosine kinase inhibitor for the treatment of renal cell carcinoma. In this work, two new HPLC methods coupled with fluorescence (FLD), or photodiode array detectors (PDA) were developed and used for the first time for tivozanib quantification in rat plasma and liver microsomes. The described methods were efficient with a 4-min runtime employing a Gemini-NX C18 column (50 × 2.1 mm, 3 µm) and a mobile phase of acetonitrile and ammonium acetate buffer (pH 4.7, 10 mM) (40:60, v/v) delivered at a flow rate of 0.4 mL/min. The use of HPLC-FLD allowed the quantification of 50 ng/ mL tivozanib using only 100 µL rat plasma. The HPLC-FLD method was validated according to the US food and drug administration (FDA) bioanalytical guidelines and was applied successfully in a rat pharmacokinetic study (n = 7) following oral administration of 1 mg/ kg tivozanib. Furthermore, HPLC-PDA was used for monitoring the depletion of 1 µM (454.9 ng/mL) tivozanib in rat liver microsomes and was applied to study the effect of dexamethasone induction on tivozanib metabolism in vitro. Results showed that dexamethasone enhanced the intrinsic clearance of tivozanib by 60 % suggesting a potential drug-drug interaction at the metabolism level. Dexamethasone is commonly used in the management of cancer disease and thus coadministration with tivozanib therapy may cause treatment failure in patients. The simplicity, speed and cost-effectiveness of the reported methods are ideal for supporting in vivo and in vitro tivozanib studies, including drug-drug interaction studies, particularly in bioanalytical labs lacking LC-MS/MS capabilities.

HPLC with Fluorescence and Photodiode Array Detection for Quantifying Capmatinib in Biological Samples: Application to In Vivo and In Vitro Studies.

Capmatinib, a recently approved tyrosine kinase inhibitor, is used for the treatment of non-small cell lung cancer. We describe two new HPLC methods for capmatinib quantification in vivo and in vitro. HPLC with a fluorescence detection method was used to quantify capmatinib in plasma for the first time. The method was successfully applied in a pharmacokinetic study following a 10 mg/kg oral dose of capmatinib given to rats. The chromatographic separation was performed using a Eurospher II 100-3 C18H (50 × 4 mm, 3 µm) column and a mobile phase containing 10 mM of ammonium acetate buffer (pH 5.5): acetonitrile (70:30, v/v), at a flow rate of 2.0 mL min-1. The study also describes the use of HPLC-PDA for the first time for the determination of capmatinib in human liver microsomes and describes its application to study its metabolic stability in vitro. Our results were in agreement with those reported using LC-MS/MS, demonstrating the reliability of the method. The study utilized a Gemini-NX C18 column and a mobile phase containing methanol: 20 mM ammonium formate buffer pH 3.5 (53:47, v/v), delivered at a flow rate of 1.1 mL min-1. These methods are suitable for supporting pharmacokinetic studies, particularly in bioanalytical labs lacking LC-MS/MS capabilities.

Physiologically-based pharmacokinetic model for alectinib, ruxolitinib, and panobinostat in the presence of cancer, renal impairment, and hepatic impairment.

Renal (RIP) and hepatic (HIP) impairments are prevalent conditions in cancer patients. They can cause changes in gastric emptying time, albumin levels, hematocrit, glomerular filtration rate, hepatic functional volume, blood flow rates, and metabolic activity that can modify drug pharmacokinetics. Performing clinical studies in such populations has ethical and practical issues. Using predictive physiologically-based pharmacokinetic (PBPK) models in the evaluation of the PK of alectinib, ruxolitinib, and panobinostat exposures in the presence of cancer, RIP, and HIP can help in using optimal doses with lower toxicity in these populations. Verified PBPK models were customized under scrutiny to account for the pathophysiological changes induced in these diseases. The PBPK model-predicted plasma exposures in patients with different health conditions within average 2-fold error. The PBPK model predicted an area under the curve ratio (AUCR) of 1, and 1.8, for ruxolitinib and panobinostat, respectively, in the presence of severe RIP. On the other hand, the severe HIP was associated with AUCR of 1.4, 2.9, and 1.8 for alectinib, ruxolitinib, and panobinostat, respectively, in agreement with the observed AUCR. Moreover, the PBPK model predicted that alectinib therapeutic cerebrospinal fluid levels are achieved in patients with non-small cell lung cancer, moderate HIP, and severe HIP at 1-, 1.5-, and 1.8-fold that of healthy subjects. The customized PBPK models showed promising ethical alternatives for simulating clinical studies in patients with cancer, RIP, and HIP. More work is needed to quantify other pathophysiological changes induced by simultaneous affliction by cancer and RIP or HIP.