Creation of Novel Sensitive Probe Substrate and Moderate Inhibitor Models for a Comprehensive Prediction of CYP2C8 Interactions for Tucatinib.

A physiologically-based pharmacokinetic (PBPK) model was developed to simulate plasma concentrations of tucatinib (TUKYSA®) after single-dose or multiple-dose administration of 300 mg b.i.d. orally. This PBPK model was subsequently applied to support evaluation of drug-drug interaction (DDI) risk as a perpetrator resulting from tucatinib inhibition of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was also applied to support evaluation of DDI risk as a victim resulting from co-administration with CYP3A4 or CYP2C8 inhibitors, or a CYP3A4 inducer. After refinement with clinical DDI data, the final PBPK model was able to recover the clinically observed single and multiple-dose plasma concentrations for tucatinib when tucatinib was administered as a single agent in healthy subjects. In addition, the final model was able to recover clinically observed plasma concentrations of tucatinib when administered in combination with itraconazole, rifampin, or gemfibrozil as well as clinically observed plasma concentrations of probe substrates of CYP3A4, CYP2C8, CYP2C9, P-gp, or MATE1/2-K. The PBPK model was then applied to prospectively predict the potential perpetrator or victim DDIs with other substrates, inducers, or inhibitors. To simulate a potential interaction with a moderate CYP2C8 inhibitor, two novel PBPK models representing a moderate CYP2C8 inhibitor and a sensitive CYP2C8 substrate were developed based on the existing PBPK models for gemfibrozil and rosiglitazone, respectively. The simulated population geometric mean area under the curve ratio of tucatinib with a moderate CYP2C8 inhibitor ranged from 1.98- to 3.08-fold, and based on these results, no dose modifications were proposed for moderate CYP2C8 inhibitors for the tucatinib label.

Rational design and biological evaluation of gemfibrozil modified Xenopus GLP-1 derivatives as long-acting hypoglycemic agents.

Novel methods for peptides structural modification and bioactivity optimization are highly needed in peptide-based drug discovery. Herein, we explored the use gemfibrozil (GFZ) as an albumin binder to enhance the stability and improve the bioactivity of peptides. Short-acting Xenopus glucagon-like peptide-1 (xGLP-1) analogues with anti-diabetic activity were selected as the starting point. Mono-GFZ conjugation, peptide sequence hybridization, and dimeric-GFZ derivatization were successively used to generate novel GFZ-xGLP-1 conjugates, biologically screened by various in vitro and in vivo models. Dimeric-GFZ modified conjugate 3b was finally identified as a promising anti-diabetic candidate with high albumin binding affinity, enhanced in vivo stability in SD rats, and long-acting hypoglycemic activity in db/db mice. Moreover, GFZ endowed 3b with strong lipid-regulating ability in DIO and db/db mice. In a twelve-week study, chronic administration of 3b in db/db mice resulted in sustained glycemic control, to a greater extent than liraglutide and semaglutide. In addition, 3b showed comparable therapeutic efficacies to liraglutide and semaglutide on HbA1c and pancreas islets protection. Our studies reveal 3b as a potential candidate for the treatment of metabolic diseases and indicate dimeric-GFZ modification as a novel method for peptide optimization.

Effects of Strong CYP2C8 or CYP3A Inhibition and CYP3A Induction on the Pharmacokinetics of Brigatinib, an Oral Anaplastic Lymphoma Kinase Inhibitor, in Healthy Volunteers.

In vitro data support involvement of cytochrome P450 (CYP)2C8 and CYP3A4 in the metabolism of the anaplastic lymphoma kinase inhibitor brigatinib. A 3-arm, open-label, randomized, single-dose, fixed-sequence crossover study was conducted to characterize the effects of the strong inhibitors gemfibrozil (of CYP2C8) and itraconazole (of CYP3A) and the strong inducer rifampin (of CYP3A) on the single-dose pharmacokinetics of brigatinib. Healthy subjects (n = 20 per arm) were administered a single dose of brigatinib (90 mg, arms 1 and 2; 180 mg, arm 3) alone in treatment period 1 and coadministered with multiple doses of gemfibrozil 600 mg twice daily (BID; arm 1), itraconazole 200 mg BID (arm 2), or rifampin 600 mg daily (QD; arm 3) in period 2. Compared with brigatinib alone, coadministration of gemfibrozil with brigatinib did not meaningfully affect brigatinib area under the plasma concentration-time curve (AUC0-inf ; geometric least-squares mean [LSM] ratio [90%CI], 0.88 [0.83-0.94]). Coadministration of itraconazole with brigatinib increased AUC0-inf (geometric LSM ratio [90%CI], 2.01 [1.84-2.20]). Coadministration of rifampin with brigatinib substantially reduced AUC0-inf (geometric LSM ratio [90%CI], 0.20 [0.18-0.21]) compared with brigatinib alone. The treatments were generally tolerated. Based on these results, strong CYP3A inhibitors and inducers should be avoided during brigatinib treatment. If concomitant use of a strong CYP3A inhibitor is unavoidable, the results of this study support a dose reduction of brigatinib by approximately 50%. Furthermore, CYP2C8 is not a meaningful determinant of brigatinib clearance, and no dose modifications are needed during coadministration of brigatinib with CYP2C8 inhibitors.

Optimization of chromatography to overcome matrix effect for reliable estimation of four small molecular drugs from biological fluids using LC-MS/MS.

The article describes a systematic study to overcome the matrix effect during chromatographic analysis of gemfibrozil, rivastigmine, telmisartan and tacrolimus from biological fluids using LC-ESI-MS/MS. All four methods were thoroughly developed by the appropriate choice of analytical column, elution mode and pH of mobile phase for improved chromatography and overall method performance. Matrix effect was assessed by post-column analyte infusion, slope of calibration line approach and post-extraction spiking. The best chromatographic conditions established were: Acquity BEH C18 (50 × 2.1 mm, 1.7 µm) column with 5.0 mm ammonium acetate, pH 6.0-methanol as the mobile phase under gradient program for gemfibrozil; Luna CN (50 × 2.0 mm, 3 µm) column with a mobile phase consisting of acetonitrile-10 mm ammonium acetate, pH 7.0 (90:10, v/v) for rivastigmine; Inertsustain C18 (100 × 2.0 mm, 5 µm) column using methanol-2.0 mm ammonium formate, pH 5.5 (80: 20, v/v) as the mobile phase for isocratic elution of telmisartan; and Acquity BEH C18 (50 × 2.1 mm, 1.7 µm) with methanol-10 mm ammonium acetate, pH 6.0 (95:5, v/v) as mobile phase for tacrolimus. The methods were thoroughly validated as per European Medicines Agency and US Food and Drug Administration guidance and were successfully applied for pharmacokinetic studies in healthy subjects.

UPLC-MS/MS method for gemfibrozil determination in plasma with application to a pharmacokinetic study in healthy Brazilian volunteers.

Gemfibrozil (GFZ) is a derivative of fibric acid and is used in the treatment of dyslipidemia. GFZ may affect the metabolism of various drugs, including statins, by inhibiting the sinusoidal influx transporter OATP1B1 and also CYP2C9 and CYP2C8 enzymes. This study presents the development and validation of a rapid, simple, sensitive and reproducible method of GFZ analysis in human plasma using UPLC-MS/MS. The method was applied in a pharmacokinetic study following administration of multiple doses of 600 mg GFZ every 12 h in healthy volunteers (n = 15). GFZ was separated on a C18 column using a mixture of 0.01% formic acid and acetonitrile (40:60, v/v) as the mobile phase at a flow rate of 0.4 mL/min. The method showed linearity in the range from 0.01 µg/mL to 100 µg/mL plasma. The coefficients of variation and the relative standard errors of the accuracy and precision analyses were <15%. The method allowed quantification of plasma concentrations of GFZ in the dose interval of the sixth day of administration of multiple oral doses of GFZ every 12 h. The pharmacokinetic parameters are presented as mean (95% CI): area under the plasma concentration versus time curve 88.84 (72.72-104.96) µg·h/mL, steady state mean plasma concentration 7.40 (6.06-8.75) µg/mL, minimum plasma concentration 1.24 (0.87-1.61) µg/mL, maximum plasma concentration 26.73 (21.31-32.15) µg/mL, time to reach maximum plasma concentration 2.28 (1.42-3.13) h, elimination half-life 2.81 (2.22-3.40) h, apparent total clearance 7.72 (5.85-9.58) L/h, apparent distribution volume 33.97 (18.41-49.53) L. In conclusion, the method for analysis of GFZ in human plasma showed sensitivity, linearity, precision and accuracy compatible with application in pharmacokinetic studies of multiple oral dose of 600 mg GFZ every 12 h.

Physiologically Based Pharmacokinetic Models for Prediction of Complex CYP2C8 and OATP1B1 (SLCO1B1) Drug-Drug-Gene Interactions: A Modeling Network of Gemfibrozil, Repaglinide, Pioglitazone, Rifampicin, Clarithromycin and Itraconazole.

BACKGROUND: Drug-drug interactions (DDIs) and drug-gene interactions (DGIs) pose a serious health risk that can be avoided by dose adaptation. These interactions are investigated in strictly controlled setups, quantifying the effect of one perpetrator drug or polymorphism at a time, but in real life patients frequently take more than two medications and are very heterogenous regarding their genetic background. OBJECTIVES: The first objective of this study was to provide whole-body physiologically based pharmacokinetic (PBPK) models of important cytochrome P450 (CYP) 2C8 perpetrator and victim drugs, built and evaluated for DDI and DGI studies. The second objective was to apply these models to describe complex interactions with more than two interacting partners. METHODS: PBPK models of the CYP2C8 and organic-anion-transporting polypeptide (OATP) 1B1 perpetrator drug gemfibrozil (parent-metabolite model) and the CYP2C8 victim drugs repaglinide (also an OATP1B1 substrate) and pioglitazone were developed using a total of 103 clinical studies. For evaluation, these models were applied to predict 34 different DDI studies, establishing a CYP2C8 and OATP1B1 PBPK DDI modeling network. RESULTS: The newly developed models show a good performance, accurately describing plasma concentration-time profiles, area under the plasma concentration-time curve (AUC) and maximum plasma concentration (Cmax) values, DDI studies as well as DGI studies. All 34 of the modeled DDI AUC ratios (AUC during DDI/AUC control) and DDI Cmax ratios (Cmax during DDI/Cmax control) are within twofold of the observed values. CONCLUSIONS: Whole-body PBPK models of gemfibrozil, repaglinide, and pioglitazone have been built and qualified for DDI and DGI prediction. PBPK modeling is applicable to investigate complex interactions between multiple drugs and genetic polymorphisms.

Application of a physiologically based pharmacokinetic model for the prediction of mirabegron plasma concentrations in a population with severe renal impairment.

We previously verified a physiologically based pharmacokinetic (PBPK) model for mirabegron in healthy subjects using the Simcyp Simulator by incorporating data on the inhibitory effect on cytochrome P450 (CYP) 2D6 and a multi-elimination pathway mediated by CYP3A4, uridine 5'-diphosphate-glucuronosyltransferase (UGT) 2B7 and butyrylcholinesterase (BChE). The aim of this study was to use this PBPK model to assess the magnitude of drug-drug interactions (DDIs) in an elderly population with severe renal impairment (sRI), which has not been evaluated in clinical trials. We first determined the system parameters, and meta-analyses of literature data suggested that the abundance of UGT2B7 and the BChE activity in an elderly population with sRI was almost equivalent to and 20% lower than that in healthy young subjects, respectively. Other parameters, such as the CYP3A4 abundance, for an sRI population were used according to those built into the Simcyp Simulator. Second, we confirmed that the PBPK model reproduced the plasma concentration-time profile for mirabegron in an sRI population (simulated area under the plasma concentration-time curve (AUC) was within 1.5-times that of the observed value). Finally, we applied the PBPK model to simulate DDIs in an sRI population. The PBPK model predicted that the AUC for mirabegron with itraconazole (a CYP3A4 inhibitor) was 4.12-times that in healthy elderly subjects administered mirabegron alone, and predicted that the proportional change in AUC for desipramine (a CYP2D6 substrate) with mirabegron was greater than that in healthy subjects. In conclusion, the PBPK model was verified for the purpose of DDI assessment in an elderly population with sRI.

Effects and bioaccumulation of gold nanoparticles in the gilthead seabream (Sparus aurata) - Single and combined exposures with gemfibrozil.

Gold nanoparticles (AuNPs) are found in a wide range of applications and therefore expected to present increasing levels in the environment. There is however limited knowledge concerning the potential toxicity of AuNPs as well as their combined effects with other pollutants. Hence, the present study aimed to investigate the effects of AuNPs alone and combined with the pharmaceutical gemfibrozil (GEM) on different biological responses (behaviour, neurotransmission, biotransformation and oxidative stress) in one of the most consumed fish in southern Europe, the seabream Sparus aurata. Fish were exposed for 96 h to waterborne 40 nm AuNPs with two coatings - citrate and polyvinylpyrrolidone (PVP), alone or combined with GEM. Antioxidant defences were induced in liver and gills upon both AuNPs exposure. Decreased swimming performance (1600 µg.L-1) and oxidative damage in gills (4 and 80 µg.L-1) were observed following exposure to polyvinylpyrrolidone coated gold nanoparticles (PVP-AuNPs). Generally, accumulation of gold in fish tissues and deleterious effects in S. aurata were higher for PVP-AuNPs than for cAuNPs exposures. Although AuNPs and GEM combined effects in gills were generally low, in liver, they were higher than the predicted. The accumulation and effects of AuNPs showed to be dependent on the size, coating, surface charge and aggregation/agglomeration state of nanoparticles. Additionally, it was tissue' specific and dependent on the presence of other contaminants. Although, gold intake by humans is expected to not exceed the estimated tolerable daily intake, it is highly recommended to keep it on track due to the increasing use of AuNPs.

Effect of Overencapsulation on the Disintegration and Dissolution of Licensed Formulations for Blinding in Randomized Controlled Trials.

Overencapsulation is a technique used to conceal tablet products for blinding in randomized controlled trials. A tablet is inserted in an opaque capsule shell with backfill excipient to prevent rattling. Regulatory authorities require evidence that such modification does not materially alter drug release to approve their use in trials. The objective of this study was to assess impact of overencapsulation on disintegration and dissolution of 4 immediate-release drug products (penicillin V, gemfibrozil, ciprofloxacin, and furosemide). Each unmodified tablet was compared to 3 overencapsulated tablets with differing backfill excipient (colloidal silica, lactose monohydrate, or microcrystalline cellulose). All 12 overencapsulated tablets met disintegration and dissolution acceptance criteria. Dissolution acceptance was dependent on apparatus as only 4/12 formulations met specifications using the rotating basket compared to 12/12 using the rotating paddle. Significant differences in release were observed at early time points (T5-T15). No correlation was observed between aqueous solubility and release, although dissolution of the lipophilic drug gemfibrozil was least impacted by overencapsulation. There was evidence that type/quantity of backfill delays release at early time points. These findings indicate that under the specified conditions, overencapsulated formulations of 4 drugs, 1 from each class of the Biopharmaceutics Classification System, met compendial requirements for release testing.

Quantitative Analysis of Complex Drug-Drug Interactions between Cerivastatin and Metabolism/Transport Inhibitors Using Physiologically Based Pharmacokinetic Modeling.

Cerivastatin (CER) was withdrawn from the world market because of lethal rhabdomyolysis. Coadministrations of CER and cyclosporine A (CsA) or gemfibrozil (GEM) have been reported to increase the CER blood concentration. CsA is an inhibitor of organic anion transporting polypeptide (OATP)1B1 and CYP3A4, and GEM and its glucuronide (GEM-glu) inhibit OATP1B1 and CYP2C8. The purpose of this study was to describe the transporter-/enzyme-mediated drug-drug interactions (DDIs) of CER with CsA or GEM based on unified physiologically based pharmacokinetic (PBPK) models and to investigate whether the DDIs can be quantitatively analyzed by a bottom-up approach. Initially, the PBPK models for CER and GEM/GEM-glu were constructed based on the previously reported standard protocols. Next, the drug-dependent parameters were optimized by Cluster Newton Method. Thus, described concentration-time profiles for CER and GEM/GEM-glu agreed well with the clinically observed data. The DDIs were then simulated using the established PBPK models with previously obtained in vitro inhibition constants of CsA or GEM/GEM-glu against the OATP1B1 and cytochrome P450s. DDIs with the inhibitors were underestimated compared with observed data using the geometric means of reported values. To search for better described parameters within the range of in vitro values, sensitivity analyses were performed for DDIs of CER. Using the in vitro parameter sets selected by sensitivity analyses, these DDIs were well reproduced, indicating that the present PBPK models were able to describe adequately the clinical DDIs based on a bottom-up approach. The approaches in this study would be applicable to the prediction of other DDIs involving both transporters and metabolic enzymes.

Species-related exposure of phase II metabolite gemfibrozil 1-O-ß-glucuronide between human and mice: A net induction of mouse P450 activity was revealed.

Gemfibrozil is a fibrate drug used widely for dyslipidemia associated with atherosclerosis. Clinically, both gemfibrozil and its phase II metabolite gemfibrozil 1-O-ß-glucuronide (gem-glu) are involved in drug-drug interaction (DDI). But the DDI risk caused by gem-glu between human and mice has not been compared. In this study, six volunteers were recruited and took a therapeutic dose of gemfibrozil for 3 days for examination of the gemfibrozil and gem-glu level in human. Male mice were fed a gemfibrozil diet (0.75%) for 7 days, following which a cocktail-based inhibitory DDI experiment was performed. Plasma samples and liver tissues from mice were collected for determination of gemfibrozil, gem-glu concentration and cytochrome p450 enzyme (P450) induction analysis. In human, the molar ratio of gem-glu/gemfibrozil was 15% and 10% at the trough concentration and the concentration at 1.5 h after the 6th dose. In contrast, this molar ratio at steady state in mice was 91%, demonstrating a 6- to 9-fold difference compared with that in human. Interestingly, a net induction of P450 activity and in vivo inductive DDI potential in mice was revealed. The P450 activity was not inhibited although the gem-glu concentration was high. These data suggested species difference of relative gem-glu exposure between human and mice, as well as a net inductive DDI potential of gemfibrozil in mouse model.

Investigating Transporter-Mediated Drug-Drug Interactions Using a Physiologically Based Pharmacokinetic Model of Rosuvastatin.

Rosuvastatin is a frequently used probe in transporter-mediated drug-drug interaction (DDI) studies. This report describes the development of a physiologically based pharmacokinetic (PBPK) model of rosuvastatin for prediction of pharmacokinetic (PK) DDIs. The rosuvastatin model predicted the observed single (i.v. and oral) and multiple dose PK profiles, as well as the impact of coadministration with transporter inhibitors. The predicted effects of rifampin and cyclosporine (6.58-fold and 5.07-fold increase in rosuvastatin area under the curve (AUC), respectively) were mediated primarily via inhibition of hepatic organic anion-transporting polypeptide (OATP)1B1 (Inhibition constant (Ki ) ∼1.1 and 0.014 µM, respectively) and OATP1B3 (Ki ∼0.3 and 0.007 µM, respectively), with cyclosporine also inhibiting intestinal breast cancer resistance protein (BCRP; Ki ∼0.07 µM). The predicted effects of gemfibrozil and its metabolite were moderate (1.88-fold increase in rosuvastatin AUC) and mediated primarily via inhibition of hepatic OATP1B1 and renal organic cation transporter 3. This model of rosuvastatin will be useful in prospectively predicting transporter-mediated DDIs with novel pharmaceutical agents in development.

Quantitative Prediction of Drug-Drug Interactions Involving Inhibitory Metabolites in Drug Development: How Can Physiologically Based Pharmacokinetic Modeling Help?

This subteam under the Drug Metabolism Leadership Group (Innovation and Quality Consortium) investigated the quantitative role of circulating inhibitory metabolites in drug-drug interactions using physiologically based pharmacokinetic (PBPK) modeling. Three drugs with major circulating inhibitory metabolites (amiodarone, gemfibrozil, and sertraline) were systematically evaluated in addition to the literature review of recent examples. The application of PBPK modeling in drug interactions by inhibitory parent-metabolite pairs is described and guidance on strategic application is provided.

Alteration of the intravenous and oral pharmacokinetics of valsartan via the concurrent use of gemfibrozil in rats.

The present study aimed to examine the potential pharmacokinetic drug interaction between valsartan and gemfibrozil. Compared with the control given valsartan (10 mg/kg) alone, the concurrent use of gemfibrozil (10 mg/kg) significantly (p < 0.05) increased the oral exposure of valsartan in rats. In the presence of gemfibrozil, the Cmax and AUC of oral valsartan increased by 1.7- and 2.5-fold, respectively. Consequently, the oral bioavailability of valsartan was significantly higher (p < 0.05) in the presence of gemfibrozil compared with that of the control group. Furthermore, the intravenous pharmacokinetics of valsartan (1 mg/kg) was also altered by pretreatment with oral gemfibrozil (10 mg/kg). The plasma clearance of valsartan was decreased by two-fold in the presence of gemfibrozil, while the plasma half-life was not altered. In contrast, both the oral and intravenous pharmacokinetics of gemfibrozil were not affected by the concurrent use of valsartan. The cellular uptake of valsartan and gemfibrozil was also investigated by using cells overexpressing OATP1B1 or OATP1B3. Gemfibrozil and gemfibrozil 1-O-ß glucuronide inhibited the cellular uptake of valsartan with IC50 values (µm) of 39.3 and 20.4, respectively, in MDCK/OATP1B1, while they were less interactive with OATP1B3. The cellular uptake of gemfibrozil was not affected by co-incubation with valsartan in both cells. Taken together, the present study suggests the potential drug interaction between valsartan and gemfibrozil, at least in part, via the OATP1B1-mediated transport pathways during hepatic uptake. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Quantitative Rationalization of Gemfibrozil Drug Interactions: Consideration of Transporters-Enzyme Interplay and the Role of Circulating Metabolite Gemfibrozil 1-O-ß-Glucuronide.

Gemfibrozil has been suggested as a sensitive cytochrome P450 2C8 (CYP2C8) inhibitor for clinical investigation by the U.S. Food and Drug Administration and the European Medicines Agency. However, gemfibrozil drug-drug interactions (DDIs) are complex; its major circulating metabolite, gemfibrozil 1-O-ß-glucuronide (Gem-Glu), exhibits time-dependent inhibition of CYP2C8, and both parent and metabolite also behave as moderate inhibitors of organic anion transporting polypeptide 1B1 (OATP1B1) in vitro. Additionally, parent and metabolite also inhibit renal transport mediated by OAT3. Here, in vitro inhibition data for gemfibrozil and Gem-Glu were used to assess their impact on the pharmacokinetics of several victim drugs (including rosiglitazone, pioglitazone, cerivastatin, and repaglinide) by employing both static mechanistic and dynamic physiologically based pharmacokinetic (PBPK) models. Of the 48 cases evaluated using the static models, about 75% and 98% of the DDIs were predicted within 1.5- and 2-fold of the observed values, respectively, when incorporating the interaction potential of both gemfibrozil and its 1-O-ß-glucuronide. Moreover, the PBPK model was able to recover the plasma profiles of rosiglitazone, pioglitazone, cerivastatin, and repaglinide under control and gemfibrozil treatment conditions. Analyses suggest that Gem-Glu is the major contributor to the DDIs, and its exposure needed to bring about complete inactivation of CYP2C8 is only a fraction of that achieved in the clinic after a therapeutic gemfibrozil dose. Overall, the complex interactions of gemfibrozil can be quantitatively rationalized, and the learnings from this analysis can be applied in support of future predictions of gemfibrozil DDIs.

Effect of gemfibrozil, rifampicin, or probenecid on the pharmacokinetics of the SGLT2 inhibitor empagliflozin in healthy volunteers.

BACKGROUND: Empagliflozin is a potent, oral, selective inhibitor of sodium glucose cotransporter 2 in development for the treatment of type 2 diabetes mellitus. OBJECTIVE: The goal of these studies was to investigate potential drug-drug interactions between empagliflozin and gemfibrozil (an organic anion-transporting polypeptide 1B1 [OATP1B1]/1B3 and organic anion transporter 3 [OAT3] inhibitor), rifampicin (an OATP1B1/1B3 inhibitor), or probenecid (an OAT3 and uridine diphosphate glucuronosyltransferase inhibitor). METHODS: Two open-label, randomized, crossover studies were undertaken in healthy subjects. In the first study, 18 subjects received the following in 1 of 2 randomized treatment sequences: a single dose of empagliflozin 25 mg alone and gemfibrozil 600 mg BID for 5 days with a single dose of empagliflozin 25 mg on the third day. In the second study, 18 subjects received a single dose of empagliflozin 10 mg, a single dose of empagliflozin 10 mg coadministered with a single dose of rifampicin 600 mg, and probenecid 500 mg BID for 4 days with a single dose of empagliflozin 10 mg on the second day in 1 of 6 randomized treatment sequences. RESULTS: In the gemfibrozil study, 11 subjects were male, mean age was 35.1 years and mean body mass index (BMI) was 23.47 kg/m(2). In the rifampicin/probenecid study, 10 subjects were male, mean age was 32.7 years and mean BMI was 23.03 kg/m(2). Exposure to empagliflozin was increased by coadministration with gemfibrozil (AUC0-∞: geometric mean ratio [GMR], 158.50% [90% CI, 151.77-165.53]; Cmax: GMR, 115.00% [90% CI, 106.15-124.59]), rifampicin (AUC0-∞: GMR, 135.20% [90% CI, 129.58-141.06]; Cmax: GMR, 175.14% [90% CI, 160.14-191.56]), and probenecid (AUC0-∞: GMR, 153.47% [90% CI, 146.41-160.88]; Cmax: GMR, 125.60% [90% CI, 113.67-138.78]). All treatments were well tolerated. CONCLUSIONS: Increases in empagliflozin exposure were <2-fold, indicating that the inhibition of the OATP1B1/1B3, OAT3 transporter, and uridine diphosphate glucuronosyltransferases did not have a clinically relevant effect on empagliflozin exposure. No dose adjustments of empagliflozin were necessary when it was coadministered with gemfibrozil, rifampicin, or probenecid. ClinicalTrials.gov identifiers: NCT01301742 and NCT01634100.

Mechanistic modeling to predict the transporter- and enzyme-mediated drug-drug interactions of repaglinide.

PURPOSE: Quantitative prediction of complex drug-drug interactions (DDIs) is challenging. Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate of organic anion transporting polypeptide (OATP)1B1. The purpose is to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and DDIs of repaglinide. METHODS: In vitro hepatic transport of repaglinide, gemfibrozil and gemfibrozil 1-O-ß-glucuronide was characterized using sandwich-culture human hepatocytes. A PBPK model, implemented in Simcyp (Sheffield, UK), was developed utilizing in vitro transport and metabolic clearance data. RESULTS: In vitro studies suggested significant active hepatic uptake of repaglinide. Mechanistic model adequately described repaglinide pharmacokinetics, and successfully predicted DDIs with several OATP1B1 and CYP3A4 inhibitors (<10% error). Furthermore, repaglinide-gemfibrozil interaction at therapeutic dose was closely predicted using in vitro fraction metabolism for CYP2C8 (0.71), when primarily considering reversible inhibition of OATP1B1 and mechanism-based inactivation of CYP2C8 by gemfibrozil and gemfibrozil 1-O-ß-glucuronide. CONCLUSIONS: This study demonstrated that hepatic uptake is rate-determining in the systemic clearance of repaglinide. The model quantitatively predicted several repaglinide DDIs, including the complex interactions with gemfibrozil. Both OATP1B1 and CYP2C8 inhibition contribute significantly to repaglinide-gemfibrozil interaction, and need to be considered for quantitative rationalization of DDIs with either drug.

Analysis of the repaglinide concentration increase produced by gemfibrozil and itraconazole based on the inhibition of the hepatic uptake transporter and metabolic enzymes.

The plasma concentration of repaglinide is reported to increase greatly when given after repeated oral administration of itraconazole and gemfibrozil. The present study analyzed this interaction based on a physiologically based pharmacokinetic (PBPK) model incorporating inhibition of the hepatic uptake transporter and metabolic enzymes involved in repaglinide disposition. Firstly, the plasma concentration profiles of inhibitors (itraconazole, gemfibrozil, and gemfibrozil glucuronide) were reproduced by a PBPK model to obtain their pharmacokinetic parameters. The plasma concentration profiles of repaglinide were then analyzed by a PBPK model, together with those of the inhibitors, assuming a competitive inhibition of CYP3A4 by itraconazole, mechanism-based inhibition of CYP2C8 by gemfibrozil glucuronide, and inhibition of organic anion transporting polypeptide (OATP) 1B1 by gemfibrozil and its glucuronide. The plasma concentration profiles of repaglinide were well reproduced by the PBPK model based on the above assumptions, and the optimized values for the inhibition constants (0.0676 nM for itraconazole against CYP3A4; 14.2 µM for gemfibrozil against OATP1B1; and 5.48 µM for gemfibrozil glucuronide against OATP1B1) and the fraction of repaglinide metabolized by CYP2C8 (0.801) were consistent with the reported values. The validity of the obtained parameters was further confirmed by sensitivity analyses and by reproducing the repaglinide concentration increase produced by concomitant gemfibrozil administration at various timings/doses. The present findings suggested that the reported concentration increase of repaglinide, suggestive of synergistic effects of the coadministered inhibitors, can be quantitatively explained by the simultaneous inhibition of the multiple clearance pathways of repaglinide.

CYP2C metabolism of oral antidiabetic drugs--impact on pharmacokinetics, drug interactions and pharmacogenetic aspects.

INTRODUCTION: The cytochrome P4502C enzymes account for the metabolism of approximately 20% of therapeutic drugs including certain oral antidiabetic drugs (OADs). AREAS COVERED: This review focuses on the effect of CYP2C enzymes on metabolism of sulphonylureas (SUs), meglitinides, and thiazolidinediones (TZDs) discussing their impact on pharmacokinetics, drug interactions and toxicological profiles. Pharmacogenetic aspects reflecting individual gene variants and variable drug effects are also considered. EXPERT OPINION: Genetic polymorphisms of CYP2C9 enzymes (*2/*2, *2/*3, *3/*3) influence the glycaemic response to SUs and impair their substrate metabolism. Restricted data from small-sized studies with heterogenous definitions of hypoglycaemia revealed no clear association between CYP2C9 genotypes and the risk of hypoglycaemia. Functional polymorphisms of CYP2C8- and CYP2C9 drug metabolizing genes affect markedly pharmacokinetics of meglitinides. Compared to wild-type carriers, patients treated with TZDs and carrying the common CYP2C8*3 and *4 variants showed a reduced glycaemic control. The strong CYP2C8 and OATP1B1 inhibitor gemfibrozil increases substantially the plasma concentrations of repaglinide and TZDs. Numerous metabolic drug interactions exist between SUs and commonly prescribed drugs, especially anti-infectives. The complex pharmacokinetic and pharmacogenetic properties and the unfavourable short and long term risk profile of glibenclamide and glimepiride raise the question whether their use can be justified any longer.

Physiologically based modeling of pravastatin transporter-mediated hepatobiliary disposition and drug-drug interactions.

PURPOSE: To develop physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and drug-drug interactions (DDI) of pravastatin, using the in vitro transport parameters. METHODS: In vitro hepatic sinusoidal active uptake, passive diffusion and canalicular efflux intrinsic clearance values were determined using sandwich-culture human hepatocytes (SCHH) model. PBPK modeling and simulations were implemented in Simcyp (Sheffield, UK). DDI with OATP1B1 inhibitors, cyclosporine, gemfibrozil and rifampin, was also simulated using inhibition constant (Ki) values. RESULTS: SCHH studies suggested active uptake, passive diffusion and efflux intrinsic clearance values of 1.9, 0.5 and 1.2 µL/min/10(6)cells, respectively, for pravastatin. PBPK model developed, using transport kinetics and scaling factors, adequately described pravastatin oral plasma concentration-time profiles at different doses (within 20% error). Model based prediction of DDIs with gemfibrozil and rifampin was similar to that observed. However, pravastatin-cyclosporine DDI was underpredicted (AUC ratio 4.4 Vs ~10). Static (R-value) model predicted higher magnitude of DDI compared to the AUC ratio predicted by the PBPK modeling. CONCLUSIONS: PBPK model of pravastatin, based on in vitro transport parameters and scaling factors, was developed. The approach described can be used to predict the pharmacokinetics and DDIs associated with hepatic uptake transporters.