Development of a UPLC-MS/MS method for the simultaneous determination of atorvastatin, 2-hydroxy atorvastatin, and naringenin in rat plasma and its application to pharmacokinetic interaction studies.

Recent studies have revealed that the combination therapy of atorvastatin (ATV) with naringenin (NG) can offer meaningful benefits in the treatment of hypercholesterolemia, while decreasing adverse side effects. To investigate whether there are pharmacokinetic interactions among ATV, its metabolite 2-hydroxy atorvastatin (2-ATV), and NG, in the current study, we developed and validated a simple, rapid, and specific UPLC-MS/MS method to simultaneously determine the concentrations of these analytes in the rat plasma. Sample preparation was performed using simple protein precipitation. Chromatographic analysis was carried out on an Acquity UPLC BEH C18 column (1.7 µm, 2.1 × 100 mm) using gradient elution mode, and these three analytes were detected using a Xevo® TQD triple quadrupole tandem mass spectrometer, in the positive ion electrospray ionization interface. The developed method showed good linearity over the following concentrations in rat plasma samples: 3-1200 ng/ml (r = 0.9965) for ATV, 1.5-600 ng/ml (r = 0.9934) for 2-ATV, and 3-1200 ng/ml (r = 0.9964) for NG. The assays were validated and satisfied the acceptance criteria recommended by U.S. Food and Drug Administration guidelines. Upon successful application of the method to a pharmacokinetic interaction study, the results indicated that NG significantly enhanced the bioavailability of ATV and 2-ATV.

Ultra-high performance supercritical fluid chromatography-tandem mass spectrometry method for simultaneous determination of atorvastatin, 2-hydroxy atorvastatin, and tangeretin in rat plasma and its application to the pharmacokinetic study.

Recent studies strongly suggest that atorvastatin combination therapy with tangeretin could be beneficial in the treatment of hyperlipidemia. This study aimed to investigate the pharmacokinetic interactions among atorvastatin, its active metabolite 2-hydroxy atorvastatin, and tangeretin after oral administration of atorvastatin with tangeretin in rats. A rapid, selective, and sensitive assay was developed and validated based on ultra-high performance supercritical fluid chromatography-tandem mass spectrometry for the simultaneous measurement of atorvastatin, 2-hydroxy atorvastatin, and tangeretin concentrations in rat plasma. Chromatographic separation of the analytes was conducted on an ACQUITY Torus 1-AA column in gradient elution mode. The mass transition ion pairs were m/z 559.0→440.0 for atorvastatin, m/z 575.2→440.0 for 2-hydroxy atorvastatin, m/z 373.0→358.1 for tangeretin, and m/z 254.8→136.7 for daidzein (internal standard). Calibration curves showed good linear correlations at the following concentration range: 1-400 (r = 0.9952), 1-400 (r = 0.9980), and 3-1200 (r = 0.9945) for atorvastatin, 2-hydroxy atorvastatin, and tangeretin, respectively. The method was fully validated and satisfied the acceptance criteria recommended by the United States Food and Drug Administration. Finally, it was successfully applied in a pharmacokinetic study in rats to evaluate the pharmacokinetic behavior of atorvastatin, 2-hydroxy atorvastatin, and tangeretin.

CYP3A5*3 and SLCO1B1 c.521T>C Polymorphisms Influence the Pharmacokinetics of Atorvastatin and 2-Hydroxy Atorvastatin

There is a large variability in individual responses to atorvastatin administration. This study assessed the pharmacogenetic effects of solute carrier organic anion transporter family member 1B1 (SLCO1B1, c.388A>G and c.521T>C) and cytochrome P450 3A5 (CYP3A5, CYP3A5*3) genetic polymorphisms on the pharmacokinetics of atorvastatin and its active metabolite, 2-hydroxy (2-OH) atorvastatin, in 46 individuals who were administered a clinically used single oral dosage of 80 mg. The Cmax and AUC of atorvastatin in CYP3A5*3/*3 carriers were 2.6- and 2.8-fold higher, respectively, than those in CYP3A5*1/*1 carriers, and similar results were observed for 2-OH atorvastatin pharmacokinetics. SLCO1B1 c.521T>C also increased the AUC of atorvastatin and 2-OH atorvastatin. The AUC ratio of atorvastatin and 2-OH atorvastatin were not affected by SLCO1B1 c.388A>G or c.521T>C, whereas CYP3A5*3 reduced the AUC ratio. In an analysis evaluating the simultaneous effect of the SLCO1B1 c.521T>C and CYP3A5*3 polymorphisms, SLCO1B1 c.521TT/CYP3A5*1/*1 carriers showed lower Cmax and AUC values for atorvastatin and 2-OH atorvastatin than in individuals with the SLCO1B1 c.521T>C and/or CYP3A5*3 genotypes. Among the participants with the SLCO1B1 c.521TT genotype, the CYP3A5*3 carriers had a higher systemic exposure to atorvastatin and 2-OH atorvastatin than the CYP3A5*1/*1 carriers. Thus, SLCO1B1 c.521T>C and CYP3A5*3 polymorphisms affect the pharmacokinetics of atorvastatin and 2-OH atorvastatin.

Physiologically based pharmacokinetic modeling of disposition and drug-drug interactions for atorvastatin and its metabolites.

Atorvastatin is the most commonly used of all statins to lower cholesterol. Atorvastatin is extensively metabolized in both gut and liver to produce several active metabolites. The purpose of the present study is to develop a physiologically based pharmacokinetic (PBPK) model for atorvastatin and its two primary metabolites, 2-hydroxy-atorvastatin acid and atorvastatin lactone, using in vitro and in vivo data. The model was used to predict the pharmacokinetic profiles and drug-drug interaction (DDI) effect for atorvastatin and its metabolites in different DDI scenarios. The predictive performance of the model was assessed by comparing predicted results to observed data after coadministration of atorvastatin with different medications such as itraconazole, clarithromycin, cimetidine, rifampin and phenytoin. This population based PBPK model was able to describe the concentration-time profiles of atorvastatin and its two metabolites reasonably well in the absence or presence of those drugs at different dose regimens. The predicted maximum concentration (Cmax), area under the concentration-time curve (AUC) values and between-phase ratios were in good agreement with clinically observed data. The model has also revealed the importance of different metabolic pathways on the disposition of atorvastatin metabolites. This PBPK model can be utilized to assess the safety and efficacy of atorvastatin in the clinic. This study demonstrated the feasibility of applying PBPK approach to predict the DDI potential of drugs undergoing complex metabolism.