Renal Excretion of Dabigatran: The Potential Role of Multidrug and

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Brief Article

Renal Excretion of Dabigatran: The Potential Role of Multidrug and Toxin Extrusion (MATE) Proteins Hong Shen, Ming Yao, Michael Sinz, Punit Marathe, A. David Rodrigues, and Mingshe Zhu Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.9b00472 • Publication Date (Web): 23 Jul 2019 Downloaded from pubs.acs.org on July 24, 2019

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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Molecular Pharmaceutics

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Renal Excretion of Dabigatran: The Potential Role of Multidrug and Toxin Extrusion (MATE) Proteins

Hong Shen†,*, Ming Yao†, Michael Sinz†, Punit Marathe†, A. David Rodrigues†, and Mingshe Zhu†

Department of Metabolism and Pharmacokinetics, Bristol-Myers Squibb Research and Development, Princeton, NJ

*Address correspondence to: Dr. Hong Shen Department of Metabolism and Pharmacokinetics, Bristol-Myers Squibb Company Room F1.3802K, Mail Stop F13-09, Route 206 & Province Line Road Princeton, NJ 08543 Office Phone: (609)-252-4509; Fax : (609)-252-6802 ; Email: [email protected]

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TABLE OF CONTENTS GRAPHIC

OCT2

-

URINE

Dabigatran


BCRP

MATE2K

MATE1

P-gp

OAT4

-

-

-

-

RPTC

-

OAT3

-

OAT1

OAT2

BLOOD

Passive diffusion (?)

-

Dabigatran

OAT2 (?)

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mp-2019-00472w ABSTRACT Following oral administration, dabigatran etexilate (DABE) is rapidly hydrolyzed to its active form dabigatran. DABE but not dabigatran presents as a P-glycoprotein (P-gp) substrate and has increasingly been used as a probe drug. Therefore, although dosed as DABE, a Pgp drug-drug interaction (DDI) is reported as a dabigatran plasma concentration ratio (perpetrator versus placebo). Because the majority of a DABE dose (80 to 85%) is recovered in urine as unchanged dabigatran (renal active secretion ~25% of total clearance), dabigatran was evaluated in vitro as a substrate of various human renal transporters. Active (pyrimethamine-sensitive) dabigatran uptake was observed with human embryonic kidney (HEK) 293 cells expressing multidrug and toxin extrusion protein 1 (MATE1) and 2K (MATE2K); Michaelis-Menten constant (Km) values of 4.0 and 8.0 µM, respectively. By comparison, no uptake of 2 μM dabigatran (versus mock transfected HEK293 cells) was evident with HEK293 cells transfected with organic cation transporters (OCT2) and organic anion transporters (OAT1, 2, 3 and 4). The efflux ratios of dabigatran across P-gp- and BCRP (breast cancer resistance protein)-MDCK (Madin-Darby canine kidney) cell monolayers were 1.5 and 2.0 (versus mock-MDCK cell monolayers), suggesting dabigatran is a relatively poor P-gp and BCRP substrate. Three of five drugs (verapamil, ketoconazole and quinidine) known to interact clinically with dabigatran, as P-gp inhibitors, presented as MATE inhibitors in vitro (IC50 1.0 to 25.2 µM). Taken together, although no basolateral transporter was identified for dabigatran, the results suggest that apical MATE1 and MATE2K could play an important role in its renal clearance. MATE-mediated renal secretion of dabigatran needs to be considered when interpreting the results of P-gp DDI studies following DABE administration.


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KEYWORDS: Dabigatran etexilate, dabigatran, multidrug and toxin extrusion proteins, Pglycoprotein, and drug-drug interaction

ABBREVIATIONS: A-to-B, apical-to-basolateral; AUC, area under plasma concentration-time curve; BCRP, breast cancer resistance protein; B-to-A, basolateral-to-apical; Cgut, gut inhibitor concentration following a proposed oral dose in 250 mL; Cmax, maximum plasma concentration; CL, clearance;

CLR, renal clearance; P450, cytochrome P450; DDI, drug-drug interaction;

DMEM, Dulbecco’s modified Eagle medium; ER, efflux ratio; FDA, Food and Drug Administration; fu, fraction of unbound drug; HBSS, Hank’s balanced salt solution; HEK293: human embryonic kidney 293 cells; HEPES, N-2-hydroxyethylpiperazine-N'-2-ethanesulfonic acid; GFR, glomerular filtration rate; IC50, half maximal inhibitory concentration; ITC, International Transporter Consortium; Km, Michaelis-Menten constant that corresponds to the substrate concentration at which the uptake rate is half of maximum transport rate; LC-MS/MS, liquid chromatography-tandem mass spectrometry; MATE, multidrug and toxin extrusion protein; MDCK, Madin-Darby canine kidney cells; MPP+, 1-methyl-4-phenylpyridinium; OAT, organic anion transporter; OCT, organic cation transporter; Papp, apparent permeability; P-gp, Pglycoprotein; PYR, pyrimethamine; RE-LY, randomized evaluation of long-term anticoagulation therapy; SNP, single nucleotide polymorphism; SLC, solute carrier; TEER, trans epithelial electrical resistance; Vmax, maximum transport rate; dabigatran etexilate, DABE.

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INTRODUCTION Dabigatran etexilate (DABE) [ethyl 3-{[(2-{[(4-{N'-hexyloxycarbonyl carbamimidoyl}13

phenyl)amino]methyl}-1-methyl-1H-benzimidazol-5-yl)carbonyl]

(pyridin-2-yl-amino)

propanoate], is an inactive oral prodrug that is rapidly and extensively hydrolyzed by esterases to yield dabigatran, a reversible non-peptide direct thrombin inhibitor. The drug has been approved by the FDA for reducing the risk of stroke and serious blood clots in patients with non-valvular atrial fibrillation. DABE gained instant attention as the first novel antithrombotic agent available in the United States since the introduction of warfarin4-5 with anticoagulant efficacy superior to that of warfarin although some degree of bleeding risk with DABE was reported.6 Therefore, DABE has narrow therapeutic index. After oral administration, DABE is rapidly and completely hydrolyzed by esterases to the active form, dabigatran, with a resulting absolute bioavailability of approximately 3 to 7 %. As a result, the prodrug and its intermediates are barely detectable in human plasma.7-9 Once formed, dabigatran is largely excreted unchanged in urine; 80 to 85% of a DABE dose is recovered as unchanged dabigatran in urine after IV administration.7 The total and renal clearance (CL and CLR) of dabigatran following an intravenous infusion of [14C]dabigatran, was determined to be 155 and 119 mL/min, in healthy male volunteers, respectively. Given the unbound fraction (fu) and glomerular filtration rate (GFR) are 0.65 and 120 mL/min, respectively, the renal extraction ratio [renal extraction ratio = CLR/(fu•GFR)] of dabigatran is 1.5, suggesting significant renal tubular secretion. In addition, dabigatran exposure is higher in subjects aged > 65 years (~2.0-fold versus young) because of the age-dependent reduction in renal function.9 Renal impairment impacts the pharmacokinetics of dabigatran, as reflected in an increase in the area under plasma concentrationtime curve (AUC) of dabigatran in subjects with mild (1.5-fold increase), moderate (3.2-fold

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mp-2019-00472w increase) and severe (6.3-fold increase) renal impairment versus normal renal function. The mean terminal elimination half-life is doubled in subjects with severe renal impairment (14 hours vs. 28 hours), as is the prolongation of the pharmacodynamic effect.10 It has been reported that the interindividual dabigatran pharmacokinetics variability is high with a coefficient of variation for AUC ranging from 30 to 60%.11 Taken together, these results suggest that renal secretion is a major elimination pathway of dabigatran. However, the mechanism(s) responsible for the tubular secretion of dabigatran are unknown. For any new molecular entity, the assessment of potential drug-drug interactions (DDIs) is of importance during drug development. In this regard, DABE has been recently recommended as a probe for intestinal P-gp inhibition, due to its high selectivity, by the International Transporter Consortium, EMA, and FDA (EMA9,

60-61

. A concentration-dependent efflux of DABE was

observed in the Caco-2 cells with Km value of approximately 1 to 3 µM, and verapamil and cyclosporine A, two strong inhibitors of P-gp, decreased DABE efflux in the cells. 12-13 Of note, it is dabigatran but not DABE itself that is measured in plasma as a DDI index. For example, Kishimoto et al. reported that DABE was a suitable P-gp probe because of the good in vitro to in vivo extrapolation between the in vitro IC50 values determined using DABE and the plasma AUC ratios of dabigatran in human subjects.14 In addition, DDI studies between DABE and a set of potential P-gp transporter inhibitors (e.g., amiodarone, verapamil, clarithromycin, ketoconazole, quinidine, dronedarone, ritonavir, cobicistat, bosutinib, and itraconazole) have been investigated.15-19 However, compared with digoxin, in vitro and in vivo data using DABE as a Pgp probe are still limited. Therefore, additional studies are needed to verify the in vitro and in vivo translation of DABE and the transporter selectivity of dabigatran.

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mp-2019-00472w In the present study, an attempt was made to assess dabigatran as a substrate of various basolateral (organic cation transporter 1 and 2 [OCT1 and OCT2], organic anion transporter 1, 2 and 3 [OAT1, OAT2, and OAT3]) and apical (multidrug and toxin extrusion protein 1 [MATE1], MATE2K, OAT2, OAT4, P-gp, and breast cancer resistance protein [BCRP]) human renal transporters in vitro. In addition, clinically evaluated perpetrator drugs (amiodarone, verapamil, clarithromycin, ketoconazole, and quinidine) were assessed as inhibitors of dabigatran transport in vitro. To our knowledge, dabigatran is described for the first time as a MATE1 and MATE2K substrate.

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EXPERIMENTAL SECTION Compounds. Dabigatran, dabigatran-d3, amiodarone, verapamil, clarithromycin, ketoconazole, quinidine, pyrimethamine (PYR), and elacridar were purchased from Toronto Research Chemicals Inc. (North York, Ontario). Cyclosporin A, imipramine, Ko143, paminohippuric acid, estrone-3-sulfate, indomethacin, and metformin were purchased from SigmaAldrich (St. Louis, MO). [3H]p-aminohippuric acid (3.6 Ci/mmol), [3H]estrone-3-sulfate ammonium salt (45.6 Ci/mmol), [3H]digoxin (40 Ci/mmol), and [14C]mannitol (56 mCi/mmol) were obtained from PerkinElmer Life and Analytical Sciences (Boston, MA). [14C]Metformin (92.7 mCi/mmol) was purchased from American Radiolabeled Chemicals (St. Louis, MO). [3H]Penciclovir (1.5 Ci/mmol) and [3H]Cladribine (16.2 Ci/mmol) were obtained from Moravek Biochemicals, Inc. (Brea, CA). All other reagents were obtained from commercial sources. Cell Lines and Culture Conditions. Human embryonic kidney (HEK) 293 cells [American Type Culture Collection (ATCC)] that were transfected (individually) with human OCT1, OCT2, MATE1, MATE2K, OAT1, OAT2, OAT3 or OAT4 were prepared as described previously 20-21. All cells (transporter-transfected HEK cells and mock cells) were grown in 75cm2 culture flasks using Dulbecco’s modified Eagle medium (DMEM) with 10% fetal bovine serum, 1% L-glutamine, hygromycin B (100 µg/mL), penicillin (100 units/mL), and streptomycin (100 µg/mL) at 37°C in 5% CO2 atmosphere. Cells were split (ratio of 1:40) once a week at 80 to 95% confluence after one wash with phosphate-buffered saline containing 0.25% trypsin/EDTA. Two to three days prior to performing the transport experiments, cells were seeded in poly-Dlysine coated 24-well plates (BD Biosciences; San Jose, CA) at a density of 500,000 cells per well. All cell culture media and reagents were obtained from Mediatech, Inc (Manassas, VA) or Invitrogen (Carlsbad, CA). Passage numbers 10 to 40 were used throughout the study.

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mp-2019-00472w The Madin-Darby canine kidney (MDCK) II epithelial cells transfected with human P-gp (ABCB1) or breast cancer resistance protein (BCRP; ABCG2) were obtained from the Netherlands Cancer Institute (Amsterdam, The Netherlands). MDCK cells were cultured in DMEM supplemented with 10% fetal bovine serum, penicillin (100 units/mL), and streptomycin (100 µg/mL). Cells were grown at 37˚C, 95% relative humidity, and 5% CO2, and were passaged (ratio of 1:100) twice a week at 80 to 95% confluence using trypsin-EDTA solution, and then seeded on polycarbonate membrane filters (HTS-Transwell® inserts, surface area: 0.33 cm2, 24 well; Costar, Cambridge, MA) at a density of approximately 500,000 cells/cm2. MDCK cells, 4 to 6 days after seeding, were used for studies. All MDCK cells were used within 20 passages or less after thawing from liquid nitrogen.

Uptake and Inhibition Studies Using Transporter-Expressing HEK293 Cells. The transport experiments were performed in stably transporter transfected cells as previously described 21, and experiments were performed at least three times in triplicate. Briefly, the cells were seeded in poly-D-lysine-coated 24-well plates. After two to three days of incubation, the cells were rinsed twice with 1.5 mL pre-warmed Hanks' balanced salt solution (HBSS). Substrate uptake was initiated by the addition of 0.2 mL of pre-warmed buffer (HBSS with 10 mM HEPES, pH 7.4 for OAT1-, OAT2-, OAT3-, OAT4-, OCT1, OCT2, and vector-transfected cells as well as pH 8.4 for MATE1-, MATE2K-, and vector-transfected cells) containing dabigatran (2 µM) or radiolabeled compounds ([3H]p-aminohippuric acid, 1 µM;

[3H]estrone-3-sulfate, 1 µM;

[3H]Penciclovir, 1 µM; or [14C]metformin, 1 µM). The substrate concentration of 2 μM was selected in this study by weighing the balance between sensitivity of bioanalytical method and range of Cmax. The maximum Cmax of dabigatran was approximately 1,100 μg/L (1.8 μM) in the clinical DDI study between DBAE and clarithromycin.22 In addition, the mean steady-state Cmax

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mp-2019-00472w was 1.1 μM following 400 mg once daily DABE administration,8 and a P-gp inhibitor might increase Cmax by 2-fold.23 MATE1- and MATE2K-mediated transport were demonstrated to be stimulated by an oppositely directed proton gradient previously.24 The uptake of 1 μM [14C]metformin into the human and monkey transporter-expressing cells was measured in the presence of different extracellular pH conditions (5.0, 6.0, 7.0, 7.4, 8.0, 9.0, 10.0, and 11.0). The human MATE1- and MATE2K-mediated transport of metformin demonstrated pH dependence under these experiment conditions. At low extracellular pH (equal to and less than 6.0), the metformin uptake were negligible, whereas the uptake increased significantly when pH was raised from pH 6.0 with maximum uptake at pH 9.0 and pH10.0 for MATE1- and MATE2K-mediated uptake, respectively.24 The final concentration of organic solvents in the incubation solution were not exceed 0.5% (v/v). For the assessment of inhibition, substrate and inhibitor were both added to the buffer. After a suitable period of incubation at 37 °C, transport was terminated by the removal of the buffer, followed by washing the cells with ice-cold HBSS three times. Subsequently, the cells were solubilized in 0.1% Triton X-100. The levels of dabigatran in cell lysates were determined using the highly sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay described below. For the radiolabeled substrates, substrate level in the cell lysates was determined by liquid scintillation counting employing a LS 6500 multipurpose scintillation counter (Beckman Coulter, Fullerton, CA).

Cellular uptake was

normalized to the protein content determined using bicinchoninic acid (BCA) kit (Pierce Chemical, Rockford, IL).

Trans-Epithelial Transport Studies Using Transporter-Expressing MDCK Cells. All experiments were performed at least three times in triplicate. The trans-epithelial transport of dabigatran was evaluated using P-gp-, BCRP-, and mock-MDCK parental cells. Dabigatran (1

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mp-2019-00472w µM) or radiolabeled compounds ([3H]digoxin, 1 µM or [3H]Cladribine, 1 µM) was prepared in HBSS buffer containing 10 mM HEPES (pH 7.4) with and without Cyclosporine A (20 µM), Elacridar (50 µM), or Ko143 (10 µM). They are potent inhibitors of both P-gp and BCRP at the tested concentrations. The final concentration of organic solvents in the incubation solution will not exceed 0.5% (v/v). Substrate solution was added to either the apical (A; 200 µL) or the basolateral (B; 600 µL) compartment of the culture plate, and 600 or 200 µL of buffer was added to the compartment opposite to that containing the substrate. After incubation for 2 h at 37 °C, 50µL aliquots were removed from both sides and subjected to LC-MS/MS analysis as described below.

LC-MS/MS Analysis of Dabigatran. Analyses employed a Shimadzu SCL 30AD Nexera liquid chromatography system, comprising two LC-30AD pumps and a Shimadzu SIL-30AC autosampler, coupled with a Qtrap 6500 mass spectrometer (SCIEX, Framingham, MA, USA). Both dabigatran and dabigatran-d3 (internal standard) were quantitated. Chromatography was carried out with a Waters Acquity HSS T3 column (50 mm× 2.1 mm, 1.8 μm particle size) (Waters, Santa Clara, CA, USA) employing mobile phase A (0.1% formic acid in water) and mobile phase B, (acetonitrile) at a flow rate of 0.6 mL/min. The gradient program was set as follows: mobile phase B set at 5% (0 min to 0.5 min), increased linearly from 5% to 40% (0.5 min to 1.5 min), increased linearly a second time from 40% to 95% (1.5 min to 2.5 min), maintained at 95% (2.5 to 2.6 min), then decrease from 95% to 5%. Finally, the column was equilibrated (0.9 min) at 5% mobile phase B, prior to the next injection. Dabigatran and dabigatran-d3 retention times were 1.74 min (total run time of 3.5 min). The mass spectrometer was operated with positive electrospray ionization and multiple reaction monitoring (MRM) using the transitions of the protonated forms of dabigatran (m/z 472.2 → m/z 289.1) and dabigatran-d3 (m/z 475.1 → m/z 292.1). Optimized

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mp-2019-00472w parameters were as follows: curtain gas, gas 1 and gas 2 (nitrogen) 35, 60 and 75 units, respectively; dwell time 100 ms; source temperature 500 ºC; IonSpray voltage 3500 V. Declustering potential (DP) and collision energy (CE) were 100 V and 37 eV for both dabigatran and dabigatran-d3. Detailed procedures and results of the LC/MS method development and validation will be published separately.

Data Analysis. The initial rate for MATE1- and MATE2K-mediated dabigatran uptake was obtained by subtracting the uptake velocity in mock-transfected HEK293 cells from that of MATE1- and MATE2K-expressing HEK293 cells, and the kinetic parameters were obtained by fitting the data (nonlinear regression) to equation 1 (WinNonlin, Pharsight Inc.; Mountain View, CA).

v0 =

Vmax x S Kt + S

(1)

where v0 represents the initial uptake rate of dabigatran (picomoles per minute per mg protein, S is the substrate concentration (µM), Vmax is the maximum rate of (saturable) uptake, and Km is the Michaelis-Menten constant that corresponds to the substrate concentration at which the transport rate is half of Vmax. The half maximal inhibitory concentration (IC50) values for inhibition of MATE1- and MATE2K-mediated dabigatran uptake were determined by fitting the data (nonlinear regression) to equation 2 (WinNonlin, Pharsight Inc.; Mountain View, CA).   I  v0 = Vmax x 1 −     I + IC50 

(2)

where γ is the Hill factor that describes the steepness of the curve and I is the inhibitor concentration, v0 is the initial uptake rate measured at the given inhibitor concentration.

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mp-2019-00472w The apparent permeability (Papp) of dabigatran across the MDCK epithelial cell monolayer was calculated using equation 3:

Papp =

1  dQ  x  S x C 0  dt 

(3)

Where S represents membrane surface area, C0 is substrate (donor compartment) concentration at time zero, and dQ/dt is amount of substrate transported per unit of time. Data are represented as the average Papp (nanometers per second) for apical-to-basolateral (A-to-B) and basolateral-toapical (B-to-A) transport.

The efflux ratio (ER) of test compounds after incubation with P-gp-MDCK (ERMDCK-P-gp), BCRP-MDCK (ERMDCK-BCRP), and mock MDCK (ERMDCK) cells was calculated according to equation 4:

ER =

Papp,B−to−A Papp,A−to−B

(4).

The net ER of test compounds for P-gp-MDCK and BCRP-MDCK cells was calculated using equations 5 and 6, respectively. Net ERP −gp =

ERMDCK −P −gp

Net ERBCRP =

ERMDCK−BCRP ERMDCK

(5)

ERMDCK

and

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(6)


mp-2019-00472w All data are reported as mean ± SD, unless otherwise indicated. To test for statistically significance among multiple treatments for a given parameter, one-way analysis of variance (ANOVA) was performed. When the F ratio showed that there were significant differences among treatments, the Dunnett method of multiple comparisons was used to determine which treatments differ from control. Student’s t test was also used to compare the uptake rates of substrate uptake between transporter transfected and mock cells. A p-value of less than 0.05 was considered statistically significant. All statistical analyses were performed using GraphPad Prism 7.03 (GraphPad Software, Inc.; San Diego, CA).

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RESULTS Transport of Dabigatran by OCT1, OCT2, OAT1, OAT2, OAT3, and OAT4. Dabigatran was first assessed as a substrate of OCT1 and OCT2 that are expressed in renal proximal tubule cells

25

. The differential uptake of [14C]metformin into OCT1- and OCT2-

HEK293 cells versus mock-HEK cells was demonstrated (Supplemental Figure 2). Furthermore, the uptake of metformin was also significantly inhibited (> 90%) by PYR (50 μM), a known OCT1 and OCT2 inhibitor 26-27. In contrast to metformin, differential uptake of dabigatran (2 µM) into OCT2-HEK293 cells was not observed and PYR (50 µM) and imipramine (200 μM) had no effect. Therefore, under the conditions of the study, dabigatran did not behave as an OCT1 and OCT2 substrate at the tested concentration (Figure 1). Similar experiments were conducted with HEK293 cells expressing human OAT1, OAT2, OAT3 and OAT4. In this instance, dabigatran (2 µM) uptake was minimal versus mocktransfected cells (Figures 1 and 2). In contrast, the uptake of p-aminohippuric acid, penciclovir and estrone-3-sulfate, reported substrates of OAT1, OAT3, OAT2 and OAT4 21, 28-29, was significantly higher in OAT1-, OAT3-, OAT2-, and OAT4-HEK293 cells versus mock controls, respectively (Supplemental Figures 2 and 3). The OAT1-, OAT2-, OAT3-, and OAT4-mediated uptake of probe substrates are significantly decreased by the known transporter inhibitors. These results indicated that dabigatran was not a substrate of OAT1, OAT2, OAT3, and OAT4 under the assay conditions chosen. Transport of Dabigatran by MATE1 and MATE2K. In the absence of measurable OCT and OAT uptake, attention turned to HEK293 cells stably transfected with human MATE1 or MATE2K (Figures 2 and 3). As shown in Figure 2B, uptake of dabigatran (2 µM) in the presence of MATE1 transfected HEK293 cells was significantly higher than that observed with mock cells.

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mp-2019-00472w In addition, the uptake was reduced by MATE1 inhibitors (PYR and imipramine). The uptake of dabigatran into HEK-293 cells expressing MATE1 is linear over a period of 2 min (Figure 3A). As a result, the dabigatran transport kinetics and inhibition experiments were determined over 1.5 min. Dabigatran (0.14 to 300 μM) uptake was saturable and described by a Km of 4.0 ± 0.9 μM (Vmax 12.1 ± 0.9 pmol/mg/1.5 min; Figure 3B). Similarly, the uptake of dabigatran (2 µM) into MATE2K-HEK293 cells was timedependent and significantly higher than in mock cells (Figure 3A). The uptake of dabigatran into MATE2K-HEK293 cells was also significantly inhibited by PYR and imipramine, inhibitors of both MATE forms27, 30 (Figure 2C). The uptake window for MATE2K-mediated transport of dabigatran was ~30-fold versus mock cells (13.45 ± 0.36 versus 0.45 ± 0.28 pmol/mg protein at 5 min). Based on the linear conditions established (i.e., the uptake of dabigatran into HEK-293 cells expressing MATE2K is linear over a period of 2 min), the dabigatran transport kinetics and inhibition experiments were determined over 1.5 min. Kinetic analysis showed that MATE2Kmediated dabigatran uptake was also saturable and described by a Km of 8.0 ± 0.8 μM (Vmax 84.3 ± 5.4 pmol/mg/1.5 min) (Figure 3C). Collectively, the results indicated that dabigatran was a substrate of both human MATE1 and MATE2K. Dabigatran as a P-gp and BCRP Substrate. To evaluate whether dabigatran (1 µM) is a P-gp or BCRP substrate, additional studies were conducted with monolayers of P-gp-, BCRP-, and mock-MDCK cells. In mock-MDCK cell monolayers, the dabigatran basolateral-to-apical (B-A) and apical-to-basolateral (A-B) ER was close to unity (1.2; Figure 4A), and the compound exhibited poor passive diffusion rates after incubation for 2 hours (Papp, B-A and Papp, A-B of 0.16 and 0.14 ×10-6 m/s, respectively). In the presence of both P-gp-MDCK (Figure 4B) and BCRPMDCK (Figure 4C) monolayers, dabigatran exhibited comparable or slightly greater vectorial B-

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mp-2019-00472w A transport versus A-B transport, yielding a B-A/A-B ER of 1.8 and 2.3 for P-gp- and BCRPMDCK cells, respectively. The efflux ratios were reduced by Cyclosporine A, Ko143, and Elacridar that are dual inhibitors of P-gp and BCRP.31-33 These data indicate that dabigatran behaves as a poor P-gp and BCRP substrate in vitro. It is worth noting that the inhibitor concentrations used in this study (i.e., 10 µM for Ko143, 50 µM for Elacridar, and 20 µM for Cyclosporine A) are relatively high, and thus the inhibition of endogenous canine transporters expressed in the MDCK cells might occur. However, MDCK wild-type cells were used as control in this study. No significant difference in dabigatran permeability, between the two directions (AB and B-A), in MDCK wild-type cells in the absence and presence of inhibitor confirmed that the potential inhibition of endogenous canine transporters likely did not confound the findings (Figure 4). These data indicate that dabigatran behaves as a poor P-gp and BCRP substrate in vitro. The bidirectional permeability of digoxin (1 µM) was determined in monolayers of MDCK and P-gp-transfected MDCK (MDCK-P-gp) cells also. Digoxin exhibited greater B-to-A (25.4 ± 4.4 ×10-6 m/s) than A- to-B (0.5 ± 0.1 ×10-6 m/s) permeability in MDCK-P-gp cells, resulting in a higher ER compared with MDCK cells (49.7 versus 3.5). In addition, the ER was reduced to 2.3 by 50 μM elacridar, a known P-gp inhibitor 34-35 (Supplemental Figure 4A). Similarly, cladribine exhibited higher B-to-A (21.5 ± 4.6 ×10-6 cm/s) than A-to-B (9.8 ± 2.3 ×10-6 cm/s) permeability in MDCK-BCRP cells (ER of 2.2). As expected, the permeability was sensitive to Ko143 (a BCRP inhibitor)

36

(Supplemental Figure 4B). Therefore, these results indicated that MDCK-P-gp and

MDCK-BCRP cells used in the study were functional with respect to the transcellular transport of model substrates. In Vitro Inhibition of MATE-Mediated Dabigatran Uptake by Five Drugs Known to Impact the Pharmacokinetics of Dabigatran. The impact of five known P-gp inhibitors

17



mp-2019-00472w (amiodarone,

verapamil,

clarithromycin,

ketoconazole, and quinidine) on dabigatran

pharmacokinetics has been assessed clinically (US-FDA, 2010). Four of them have been shown to impact dabigatran systemic exposure (Table 1). In the absence of appreciable P-gp or BCRP dabigatran transport, an effort was made to evaluate all five as MATE1 and MATE2K inhibitors. The final dabigatran concentration was 2 μM (A variants enhance the glucose-lowering effect of metformin via delaying its excretion in Chinese type 2 diabetes patients. Diabetes Res Clin Pract 2015, 109 (1), 57-63. 2. Christensen, M. M.; Pedersen, R. S.; Stage, T. B.; Brasch-Andersen, C.; Nielsen, F.; Damkier, P.; Beck-Nielsen, H.; Brosen, K., A gene-gene interaction between polymorphisms in the OCT2 and MATE1 genes influences the renal clearance of metformin. Pharmacogenet Genomics 2013, 23 (10), 526-34. 3. Tkac, I.; Klimcakova, L.; Javorsky, M.; Fabianova, M.; Schroner, Z.; Hermanova, H.; Babjakova, E.; Tkacova, R., Pharmacogenomic association between a variant in SLC47A1 gene and therapeutic response to metformin in type 2 diabetes. Diabetes Obes Metab 2013, 15 (2), 18991. 4. Connolly, S. J., Atrial fibrillation in 2010: advances in treatment and management. Nat Rev Cardiol 2011, 8 (2), 67-8. 5. Paikin, J. S.; Haroun, M. J.; Eikelboom, J. W., Dabigatran for stroke prevention in atrial fibrillation: the RE-LY trial. Expert Rev Cardiovasc Ther 2011, 9 (3), 279-86. 6. Southworth, M. R.; Reichman, M. E.; Unger, E. F., Dabigatran and postmarketing reports of bleeding. The New England journal of medicine 2013, 368 (14), 1272-4. 7. Blech, S.; Ebner, T.; Ludwig-Schwellinger, E.; Stangier, J.; Roth, W., The metabolism and disposition of the oral direct thrombin inhibitor, dabigatran, in humans. Drug metabolism and disposition: the biological fate of chemicals 2008, 36 (2), 386-99. 8. Stangier, J.; Rathgen, K.; Stahle, H.; Gansser, D.; Roth, W., The pharmacokinetics, pharmacodynamics and tolerability of dabigatran etexilate, a new oral direct thrombin inhibitor, in healthy male subjects. British journal of clinical pharmacology 2007, 64 (3), 292-303. 9. Stangier, J.; Stahle, H.; Rathgen, K.; Fuhr, R., Pharmacokinetics and pharmacodynamics of the direct oral thrombin inhibitor dabigatran in healthy elderly subjects. Clinical pharmacokinetics 2008, 47 (1), 47-59. 10. Stangier, J.; Rathgen, K.; Stahle, H.; Mazur, D., Influence of renal impairment on the pharmacokinetics and pharmacodynamics of oral dabigatran etexilate: an open-label, parallelgroup, single-centre study. Clinical pharmacokinetics 2010, 49 (4), 259-68. 11. Ollier, E.; Hodin, S.; Basset, T.; Accassat, S.; Bertoletti, L.; Mismetti, P.; Delavenne, X., In vitro and in vivo evaluation of drug-drug interaction between dabigatran and proton pump inhibitors. Fundam Clin Pharmacol 2015, 29 (6), 604-14. 12. Hodin, S.; Basset, T.; Jacqueroux, E.; Delezay, O.; Clotagatide, A.; Perek, N.; Mismetti, P.; Delavenne, X., In Vitro Comparison of the Role of P-Glycoprotein and Breast Cancer Resistance Protein on Direct Oral Anticoagulants Disposition. Eur J Drug Metab Pharmacokinet 2018, 43 (2), 183-191. 13. Ishiguro, N.; Kishimoto, W.; Volz, A.; Ludwig-Schwellinger, E.; Ebner, T.; Schaefer, O., Impact of endogenous esterase activity on in vitro p-glycoprotein profiling of dabigatran etexilate in Caco-2 monolayers. Drug metabolism and disposition: the biological fate of chemicals 2014, 42 (2), 250-6. 14. Kishimoto, W.; Ishiguro, N.; Ludwig-Schwellinger, E.; Ebner, T.; Schaefer, O., In vitro predictability of drug-drug interaction likelihood of P-glycoprotein-mediated efflux of dabigatran etexilate based on [I]2/IC50 threshold. Drug metabolism and disposition: the biological fate of chemicals 2014, 42 (2), 257-63. 26


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mp-2019-00472w 15. Hartter, S.; Sennewald, R.; Nehmiz, G.; Reilly, P., Oral bioavailability of dabigatran etexilate (Pradaxa((R)) ) after co-medication with verapamil in healthy subjects. British journal of clinical pharmacology 2013, 75 (4), 1053-62. 16. Hsyu, P. H.; Pignataro, D. S.; Matschke, K., Effect of bosutinib on the absorption of dabigatran etexilate mesylate, a P-glycoprotein substrate, in healthy subjects. European journal of clinical pharmacology 2017, 73 (1), 57-63. 17. Gouin-Thibault, I.; Delavenne, X.; Blanchard, A.; Siguret, V.; Salem, J. E.; Narjoz, C.; Gaussem, P.; Beaune, P.; Funck-Brentano, C.; Azizi, M.; Mismetti, P.; Loriot, M. A., Interindividual variability in dabigatran and rivaroxaban exposure: contribution of ABCB1 genetic polymorphisms and interaction with clarithromycin. J Thromb Haemost 2017, 15 (2), 273-283. 18. Prueksaritanont, T.; Tatosian, D. A.; Chu, X.; Railkar, R.; Evers, R.; Chavez-Eng, C.; Lutz, R.; Zeng, W.; Yabut, J.; Chan, G. H.; Cai, X.; Latham, A. H.; Hehman, J.; Stypinski, D.; Brejda, J.; Zhou, C.; Thornton, B.; Bateman, K. P.; Fraser, I.; Stoch, S. A., Validation of a microdose probe drug cocktail for clinical drug interaction assessments for drug transporters and CYP3A. Clinical pharmacology and therapeutics 2017, 101 (4), 519-530. 19. Kumar, P.; Gordon, L. A.; Brooks, K. M.; George, J. M.; Kellogg, A.; McManus, M.; Alfaro, R. M.; Nghiem, K.; Lozier, J.; Hadigan, C.; Penzak, S. R., Differential Influence of the Antiretroviral Pharmacokinetic Enhancers Ritonavir and Cobicistat on Intestinal P-Glycoprotein Transport and the Pharmacokinetic/Pharmacodynamic Disposition of Dabigatran. Antimicrobial agents and chemotherapy 2017, 61 (11). 20. Shen, H.; Yang, Z.; Zhao, W.; Zhang, Y.; Rodrigues, A. D., Assessment of vandetanib as an inhibitor of various human renal transporters: inhibition of multidrug and toxin extrusion as a possible mechanism leading to decreased cisplatin and creatinine clearance. Drug metabolism and disposition: the biological fate of chemicals 2013, 41 (12), 2095-103. 21. Shen, H.; Liu, T.; Morse, B. L.; Zhao, Y.; Zhang, Y.; Qiu, X.; Chen, C.; Lewin, A. C.; Wang, X. T.; Liu, G.; Christopher, L. J.; Marathe, P.; Lai, Y., Characterization of Organic Anion Transporter 2 (SLC22A7): A Highly Efficient Transporter for Creatinine and Species-Dependent Renal Tubular Expression. Drug metabolism and disposition: the biological fate of chemicals 2015, 43 (7), 984-93. 22. Delavenne, X.; Ollier, E.; Basset, T.; Bertoletti, L.; Accassat, S.; Garcin, A.; Laporte, S.; Zufferey, P.; Mismetti, P., A semi-mechanistic absorption model to evaluate drug-drug interaction with dabigatran: application with clarithromycin. British journal of clinical pharmacology 2013, 76 (1), 107-13. 23. Chu, X.; Galetin, A.; Zamek-Gliszczynski, M. J.; Zhang, L.; Tweedie, D. J.; International Transporter, C., Dabigatran Etexilate and Digoxin: Comparison as Clinical Probe Substrates for Evaluation of P-gp Inhibition. Clinical pharmacology and therapeutics 2018, 104 (5), 788-792. 24. Shen, H.; Liu, T.; Jiang, H.; Titsch, C.; Taylor, K.; Kandoussi, H.; Qiu, X.; Chen, C.; Sukrutharaj, S.; Kuit, K.; Mintier, G.; Krishnamurthy, P.; Fancher, R. M.; Zeng, J.; Rodrigues, A. D.; Marathe, P.; Lai, Y., Cynomolgus Monkey as a Clinically Relevant Model to Study Transport Involving Renal Organic Cation Transporters: In Vitro and In Vivo Evaluation. Drug metabolism and disposition: the biological fate of chemicals 2016, 44 (2), 238-49. 25. Jonker, J. W.; Schinkel, A. H., Pharmacological and physiological functions of the polyspecific organic cation transporters: OCT1, 2, and 3 (SLC22A1-3). The Journal of pharmacology and experimental therapeutics 2004, 308 (1), 2-9. 26. Ito, S.; Kusuhara, H.; Kuroiwa, Y.; Wu, C.; Moriyama, Y.; Inoue, K.; Kondo, T.; Yuasa, H.; Nakayama, H.; Horita, S.; Sugiyama, Y., Potent and specific inhibition of mMate1-mediated

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mp-2019-00472w efflux of type I organic cations in the liver and kidney by pyrimethamine. The Journal of pharmacology and experimental therapeutics 2010, 333 (1), 341-50. 27. Kusuhara, H.; Ito, S.; Kumagai, Y.; Jiang, M.; Shiroshita, T.; Moriyama, Y.; Inoue, K.; Yuasa, H.; Sugiyama, Y., Effects of a MATE protein inhibitor, pyrimethamine, on the renal elimination of metformin at oral microdose and at therapeutic dose in healthy subjects. Clinical pharmacology and therapeutics 2011, 89 (6), 837-44. 28. Lu, R.; Chan, B. S.; Schuster, V. L., Cloning of the human kidney PAH transporter: narrow substrate specificity and regulation by protein kinase C. Am J Physiol 1999, 276 (2 Pt 2), F295303. 29. Takeda, M.; Hosoyamada, M.; Cha, S. H.; Sekine, T.; Endou, H., Hydrogen peroxide downregulates human organic anion transporters in the basolateral membrane of the proximal tubule. Life Sci 2000, 68 (6), 679-87. 30. Tsuda, M.; Terada, T.; Ueba, M.; Sato, T.; Masuda, S.; Katsura, T.; Inui, K., Involvement of human multidrug and toxin extrusion 1 in the drug interaction between cimetidine and metformin in renal epithelial cells. The Journal of pharmacology and experimental therapeutics 2009, 329 (1), 185-91. 31. Song, Y. K.; Park, J. E.; Oh, Y.; Hyung, S.; Jeong, Y. S.; Kim, M. S.; Lee, W.; Chung, S. J., Suppression of Canine ATP Binding Cassette ABCB1 in Madin-Darby Canine Kidney Type II Cells Unmasks Human ABCG2-Mediated Efflux of Olaparib. The Journal of pharmacology and experimental therapeutics 2019, 368 (1), 79-87. 32. Pedersen, J. M.; Khan, E. K.; Bergstrom, C. A. S.; Palm, J.; Hoogstraate, J.; Artursson, P., Substrate and method dependent inhibition of three ABC-transporters (MDR1, BCRP, and MRP2). European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences 2017, 103, 70-76. 33. Weidner, L. D.; Zoghbi, S. S.; Lu, S.; Shukla, S.; Ambudkar, S. V.; Pike, V. W.; Mulder, J.; Gottesman, M. M.; Innis, R. B.; Hall, M. D., The Inhibitor Ko143 Is Not Specific for ABCG2. The Journal of pharmacology and experimental therapeutics 2015, 354 (3), 384-93. 34. Tang, F.; Horie, K.; Borchardt, R. T., Are MDCK cells transfected with the human MDR1 gene a good model of the human intestinal mucosa? Pharmaceutical research 2002, 19 (6), 76572. 35. Keogh, J. P.; Kunta, J. R., Development, validation and utility of an in vitro technique for assessment of potential clinical drug-drug interactions involving P-glycoprotein. European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences 2006, 27 (5), 543-54. 36. Weiss, J.; Rose, J.; Storch, C. H.; Ketabi-Kiyanvash, N.; Sauer, A.; Haefeli, W. E.; Efferth, T., Modulation of human BCRP (ABCG2) activity by anti-HIV drugs. J Antimicrob Chemother 2007, 59 (2), 238-45. 37. Cho, S. K.; Chung, J. Y., The MATE1 rs2289669 polymorphism affects the renal clearance of metformin following ranitidine treatment. Int J Clin Pharmacol Ther 2016, 54 (4), 253-62. 38. Mousavi, S.; Kohan, L.; Yavarian, M.; Habib, A., Pharmacogenetic variation of SLC47A1 gene and metformin response in type2 diabetes patients. Mol Biol Res Commun 2017, 6 (2), 9194. 39. Nies, A. T.; Koepsell, H.; Damme, K.; Schwab, M., Organic cation transporters (OCTs, MATEs), in vitro and in vivo evidence for the importance in drug therapy. Handbook of experimental pharmacology 2011, (201), 105-67.

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mp-2019-00472w 40. Motohashi, H.; Inui, K., Organic cation transporter OCTs (SLC22) and MATEs (SLC47) in the human kidney. AAPS J 2013, 15 (2), 581-8. 41. Burckhardt, B. C.; Brai, S.; Wallis, S.; Krick, W.; Wolff, N. A.; Burckhardt, G., Transport of cimetidine by flounder and human renal organic anion transporter 1. American journal of physiology. Renal physiology 2003, 284 (3), F503-9. 42. Ahn, S. Y.; Eraly, S. A.; Tsigelny, I.; Nigam, S. K., Interaction of organic cations with organic anion transporters. The Journal of biological chemistry 2009, 284 (45), 31422-30. 43. Tsuruya, Y.; Nakanishi, T.; Komori, H.; Wang, X.; Ishiguro, N.; Kito, T.; Ikukawa, K.; Kishimoto, W.; Ito, S.; Schaefer, O.; Ebner, T.; Yamamura, N.; Kusuhara, H.; Tamai, I., Different Involvement of OAT in Renal Disposition of Oral Anticoagulants Rivaroxaban, Dabigatran, and Apixaban. Journal of pharmaceutical sciences 2017, 106 (9), 2524-2534. 44. International Transporter, C.; Giacomini, K. M.; Huang, S. M.; Tweedie, D. J.; Benet, L. Z.; Brouwer, K. L.; Chu, X.; Dahlin, A.; Evers, R.; Fischer, V.; Hillgren, K. M.; Hoffmaster, K. A.; Ishikawa, T.; Keppler, D.; Kim, R. B.; Lee, C. A.; Niemi, M.; Polli, J. W.; Sugiyama, Y.; Swaan, P. W.; Ware, J. A.; Wright, S. H.; Yee, S. W.; Zamek-Gliszczynski, M. J.; Zhang, L., Membrane transporters in drug development. Nature reviews. Drug discovery 2010, 9 (3), 215-36. 45. Muller, F.; Konig, J.; Glaeser, H.; Schmidt, I.; Zolk, O.; Fromm, M. F.; Maas, R., Molecular mechanism of renal tubular secretion of the antimalarial drug chloroquine. Antimicrobial agents and chemotherapy 2011, 55 (7), 3091-8. 46. Reznicek, J.; Ceckova, M.; Cerveny, L.; Muller, F.; Staud, F., Emtricitabine is a substrate of MATE1 but not of OCT1, OCT2, P-gp, BCRP or MRP2 transporters. Xenobiotica; the fate of foreign compounds in biological systems 2017, 47 (1), 77-85. 47. Muller, F.; Weitz, D.; Derdau, V.; Sandvoss, M.; Mertsch, K.; Konig, J.; Fromm, M. F., Contribution of MATE1 to Renal Secretion of the NMDA Receptor Antagonist Memantine. Mol Pharm 2017, 14 (9), 2991-2998. 48. Astorga, B.; Ekins, S.; Morales, M.; Wright, S. H., Molecular determinants of ligand selectivity for the human multidrug and toxin extruder proteins MATE1 and MATE2-K. The Journal of pharmacology and experimental therapeutics 2012, 341 (3), 743-55. 49. Tanihara, Y.; Masuda, S.; Sato, T.; Katsura, T.; Ogawa, O.; Inui, K., Substrate specificity of MATE1 and MATE2-K, human multidrug and toxin extrusions/H(+)-organic cation antiporters. Biochemical pharmacology 2007, 74 (2), 359-71. 50. Wittwer, M. B.; Zur, A. A.; Khuri, N.; Kido, Y.; Kosaka, A.; Zhang, X.; Morrissey, K. M.; Sali, A.; Huang, Y.; Giacomini, K. M., Discovery of potent, selective multidrug and toxin extrusion transporter 1 (MATE1, SLC47A1) inhibitors through prescription drug profiling and computational modeling. J Med Chem 2013, 56 (3), 781-95. 51. Somogyi, A.; Stockley, C.; Keal, J.; Rolan, P.; Bochner, F., Reduction of metformin renal tubular secretion by cimetidine in man. British journal of clinical pharmacology 1987, 23 (5), 54551. 52. Muller, F.; Pontones, C. A.; Renner, B.; Mieth, M.; Hoier, E.; Auge, D.; Maas, R.; Zolk, O.; Fromm, M. F., N(1)-methylnicotinamide as an endogenous probe for drug interactions by renal cation transporters: studies on the metformin-trimethoprim interaction. European journal of clinical pharmacology 2015, 71 (1), 85-94. 53. Lepist, E. I.; Phan, T. K.; Roy, A.; Tong, L.; Maclennan, K.; Murray, B.; Ray, A. S., Cobicistat boosts the intestinal absorption of transport substrates, including HIV protease inhibitors and GS-7340, in vitro. Antimicrobial agents and chemotherapy 2012, 56 (10), 5409-13.

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mp-2019-00472w 54. Mathialagan, S.; Rodrigues, A. D.; Feng, B., Evaluation of Renal Transporter Inhibition Using Creatinine as a Substrate In Vitro to Assess the Clinical Risk of Elevated Serum Creatinine. Journal of pharmaceutical sciences 2017, 106 (9), 2535-2541. 55. Lepist, E. I.; Zhang, X.; Hao, J.; Huang, J.; Kosaka, A.; Birkus, G.; Murray, B. P.; Bannister, R.; Cihlar, T.; Huang, Y.; Ray, A. S., Contribution of the organic anion transporter OAT2 to the renal active tubular secretion of creatinine and mechanism for serum creatinine elevations caused by cobicistat. Kidney international 2014, 86 (2), 350-7. 56. Vermeer, L. M.; Isringhausen, C. D.; Ogilvie, B. W.; Buckley, D. B., Evaluation of Ketoconazole and Its Alternative Clinical CYP3A4/5 Inhibitors as Inhibitors of Drug Transporters: The In Vitro Effects of Ketoconazole, Ritonavir, Clarithromycin, and Itraconazole on 13 Clinically-Relevant Drug Transporters. Drug metabolism and disposition: the biological fate of chemicals 2016, 44 (3), 453-9. 57. Grover, A.; Benet, L. Z., Effects of drug transporters on volume of distribution. AAPS J 2009, 11 (2), 250-61. 58. Liesenfeld, K. H.; Lehr, T.; Dansirikul, C.; Reilly, P. A.; Connolly, S. J.; Ezekowitz, M. D.; Yusuf, S.; Wallentin, L.; Haertter, S.; Staab, A., Population pharmacokinetic analysis of the oral thrombin inhibitor dabigatran etexilate in patients with non-valvular atrial fibrillation from the RE-LY trial. J Thromb Haemost 2011, 9 (11), 2168-75. 59. Meyer zu Schwabedissen, H. E.; Verstuyft, C.; Kroemer, H. K.; Becquemont, L.; Kim, R. B., Human multidrug and toxin extrusion 1 (MATE1/SLC47A1) transporter: functional characterization, interaction with OCT2 (SLC22A2), and single nucleotide polymorphisms. American journal of physiology. Renal physiology 2010, 298 (4), F997-F1005. 60. European Medicines Adency Guideline on the Investigation of Drug Interactions. 2012 (https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-investigation-druginteractions_en.pdf). 61. U.S. Department of Health and Human Services Food and Drug Administrration Draft Guidance for Industry on In Vitro Metabolism- and Transporter-Mediated Drug-Drug Interaction Studie. 2017 (https://www.fda.gov/downloads/Drugs/Guidances/UCM581965.pdf).

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mp-2019-00472w

FIGURE CAPTIONS Figure 1. Profiling of the transport of dabigatran by major drug transporters expressed at the basolateral membrane of RPTC. Uptake in the HEK cells stably transfected with the control vector, OAT1 (A), OAT3 (B), OAT2 (C), OCT2 (D), or OCT1 (E) was measured after a 5-min incubation at 37°C with 2 µM dabigatran. Incubations were conducted in the absence and presence of 100 μM probenecid (OAT1 and OAT3), 1,000 μM probenecid (OAT2), 50 µM sulfobromophthalein (OAT1, OAT3, and OAT2), 50 µM pyrimethamine (OCT1 and OCT1), or 200 μM imipramine (OCT1 and OCT2) to evaluate the effects of these inhibitors on dabigatran uptake. Values shown are mean ± S.D. (n = 3). ***p < 0.001 and †††p < 0.001 compared with HEK and OCT2 transfected HEK cell values, respectively. *p < 0.05, **p < 0.01 and ***p < 0.001 statistically significantly different from uptake in HEKMock cells, and †p < 0.05, ††p < 0.01 and

†††p

< 0.001 statistically significantly different from

uptake in the absence of an inhibitor.

Figure 2. Profiling of the transport of dabigatran by major drug transporters expressed at the apical membrane of RPTC. Uptake in the HEK cells stably transfected with the control vector, OAT4 (A), MATE1 (B), or MATE2K (C) OCT2 (D) was measured after a 5-min incubation at 37°C with 2 µM dabigatran. Incubations were conducted in the absence and presence of 1,000 μM probenecid (OAT4), 50 µM sulfobromophthalein (OAT4), 50 µM pyrimethamine (MATE1 and MATE2K), or 200 μM imipramine (MATE1 and MATE2K) to evaluate the effects of these inhibitors on dabigatran uptake. Values shown are mean ± S.D. (n = 3). ***p < 0.001 and †††p < 0.001 compared with HEK and OCT2 transfected HEK cell values, respectively. *p < 0.05, **p < 0.01 and ***p < 0.001

31



Page 32 of 41

mp-2019-00472w statistically significantly different from uptake in HEK-Mock cells, and †p < 0.05, ††p < 0.01 and †††p

< 0.001 statistically significantly different from uptake in the absence of an inhibitor.

Figure 3. Time- (A) and concentration-dependent uptake of dabigatran by human MATE1 (B) and MATE2K (C). Time-dependent uptake in the HEK cells stably transfected with the control vector (open triangles), MATE1 (closed squares), or MATE2K (closed circles) was measured over 8 min incubation at 37°C with 2 µM dabigatran. For concentration-dependent uptake, cells were incubated with dabigatran (0.13 to 300 µM) for 1.5 min (linear range). The net MATE1- (closed squares) or MATE2K-mediated uptake (closed circles) was calculated by subtracting that in mock cells from that in HEK-MATE1 or HEK-MATE2K cells. The curves represent the best fit of the MichaelisMenten equation. Values shown are mean ± S.D. (n = 3).

Figure 4. Transport of dabigatran across MDCK wild-type (A), MDCK-P-gp (B) and MDCK-BCRP cell monolayers (C). Apical-to-basolateral (A-B, white bar) and basolateral-to-apical (B-A, black bar) permeability of 1 µM dabigatran in the absence and presence of cyclosporine A (20 µM), Ko143 (10 µM), or elacridar (50 µM) were measured. Values shown are mean ± S.D. (n = 3). Γp < 0.05 and

ΓΓΓp

Renal Excretion of Dabigatran: The Potential Role of Multidrug and

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