in vitro evaluation of hepatic transporter-mediated clinical drug … · 2012. 3. 1. · ms/ms...

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In vitro evaluation of hepatic transporter-mediated clinical

drug-drug interactions: hepatocyte model optimization and

retrospective investigation

Yi-an Bi, Emi Kimoto, Samantha Sevidal, Hannah M. Jones, Hugh A. Barton, Sarah

Kempshall, Kevin M. Whalen, Hui Zhang, Chengjie Ji, Katherine S Fenner, Ayman F. El-

Kattan, and Yurong Lai

Pharmacokinetics, Dynamics & Metabolism, World Wide Research & Development,

Pfizer, Inc. Groton Laboratories, CT 06340 (Y.B, E.K, H.A.B, K.M.W, H.Z, C.J, A.F.E,

and Y. L); La Jolla Laboratories, CA 92121 (S.S); Sandwich Laboratories, Kent, UK

(H.M.J, S.K, K.S.F)

DMD Fast Forward. Published on March 1, 2012 as doi:10.1124/dmd.111.043489

Copyright 2012 by the American Society for Pharmacology and Experimental Therapeutics.

This article has not been copyedited and formatted. The final version may differ from this version.DMD Fast Forward. Published on March 1, 2012 as DOI: 10.1124/dmd.111.043489

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Running title page

Running title: In vitro evaluation of OATP-mediated DDI

Corresponding Author:

Yurong Lai, PhD

Department of Pharmacokinetics, Dynamics, and Metabolism, MS 8220-2475,

Pfizer World Wide Research and Development, Pfizer Inc., Groton, CT 06340;

Phone: 860-715-6448; Fax: 860-686-5364; Email: [email protected];

Number of text pages:

Number of tables: 4

Number of Figures: 3

Number of references: 53

Number of words in Abstract: 206

Number of words in Introduction: 743

Number of words in Discussion: 1563

Abbreviation: SCHH: Sandwich cultured human hepatocyte; OAT, organic

anion transporter; OATP, organic anion transporting polypeptide; OCT, organic

cation transporter; NTCP, sodium taurocholate cotransporting polypeptide. DDI,

drug-drug interaction


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Abstract:

To assess the feasibility of using sandwich cultured human hepatocytes (SCHH)

as a model for characterizing transport kinetics for in vivo pharmacokinetic prediction,

the expression of OATP proteins in SCHH, along with biliary efflux transporters (Li et al.,

2009), were quantitatively confirmed by LC-MS/MS. Rifamycin SV (Rif SV), which was

shown to completely block the function of OATP transporters, was selected as an

inhibitor for assessing the initial rates of active uptake. The optimized SCHH model was

applied in a retrospective investigation of compounds with known clinically significant

OATP-mediated uptake and was further applied to explore drug-drug interactions (DDIs).

Greater than 50% inhibition of active uptake by Rif SV was found to be associated with

clinically significant OATP-mediated DDIs. We propose that the in vitro active uptake

value could therefore serve as a cutoff for class 3 and 4 compounds of biopharmaceutics

drug disposition classification system (BDDCS), which could be integrated into the

International Transporter Consortium (ITC) decision tree recommendations (Giacomini et

al., 2010) to trigger clinical evaluations for potential DDI risks. Furthermore, kinetics of

in vitro hepatobiliary transport obtained from SCHH, along with protein expression

scaling factors, offer an opportunity to predict complex in vivo processes using

mathematical models, such as physiologically-based pharmacokinetics models (PBPK).


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Introduction

Hepatobiliary elimination are primary elimination routes for many endogenous

and exogenous xenobiotics. Hepatic uptake and efflux transporters respectively located

on sinusoidal or canalicular membranes, contribute to the vectorial transport of drugs and

their metabolites from systemic circulation to bile (Meier et al., 1997; Kullak-Ublick et

al., 2000). Two classes of hepatic uptake transporters, sodium-dependent and sodium-

independent transporters, co-exist on the sinusoidal membrane of hepatocytes with

overlapping substrate specificities. For example, the sodium-dependent transporter,

sodium-taurocholate co-transporting polypeptide (NTCP), is shown to transport the

organic anion transporting polypeptide (OATP) substrates atorvastatin and rosuvastatin

(Ho et al., 2006; Choi et al., 2011). OATP1B1/1B3, organic anion transporter 2 (OAT2)

and organic cation transporter 1 (OCT1) are specifically expressed in the liver and

transport structurally diverse substrates in a sodium-independent manner. In the last

decade, significant advances toward the prediction of in vivo NME clearance using in

vitro models have been well-documented. Indeed, in vitro human liver microsomes and

isolated hepatocytes were shown to be important tools in drug discovery and

development to confidently predict in vivo human drug metabolism for compounds


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predominately eliminated by cytochrome P-450 (Obach, 1999; McGinnity et al., 2004).

However, human PK prediction remains very challenging for compounds where drug

transporters are involved in the clearance mechanism. In 2010, the International

Transporter Consortium (ITC) recommended decision trees using in vitro systems to

assess the risk of in vivo transporter mediated drug-drug interactions (DDIs) (Giacomini

et al., 2010). For OATP transporters, the investigation cascade is initiated by the criteria

of active hepatic uptake if hepatic clearance is an important route of elimination, e.g >0.3

of total clearance (Giacomini et al., 2010). However, the models and the extent of active

hepatic uptake that would trigger the investigation cascade remain undetermined and

suitable in vitro tools to assess the active/passive hepatic uptake need to be further

validated. We hypothesized that clinically relevant OATP mediated DDI is associated

with significant active uptake in vitro.

Recently, a physiologically-based pharmacokinetic (PBPK) model, in which

physiological compartments representing organs/tissues are connected with blood flow,

was developed to predict in vivo clearance and time profiles of drug elimination using in

vitro models such as suspension hepatocytes and canalicular membrane vesicles

(Watanabe et al., 2009). The approach is generally accepted as a useful tool to predict


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tissue concentration, drug-drug interaction, and the effects of enzyme/transporter genetic

polymorphisms on drug exposure. Practically, parameters for distinct clearance processes

including passive diffusion, transporter-mediated hepatic uptake (sinusoidal), metabolism,

and transporter-mediated efflux (canalicular) into the bile could be determined in vitro

and used to predict in vivo human.

The sandwich cultured hepatocyte model (SCH) built by culturing hepatocytes

between two layers of gelled matrix in a sandwich configuration, forms a bile canalicular

network and provides the three-dimensional orientation and proper localization of

hepatobiliary transporters that mimic in vivo conditions and allow the vectorial transport

of xenobiotics (Bi et al., 2006). In 2006, Turncliff et al. evaluated the hepatobiliary

disposition of metabolites of terfenadine generated in sandwich cultured rat hepatocytes

(SCRH) (Turncliff et al., 2006). The advancement of in vitro models for the clearance

prediction in human has further reflected an increase in the mechanistic understanding of

the hepatic vectorial elimination process (Kotani et al., 2011). For example, by using LC-

MS/MS quantification methods, the expression of biliary efflux transporters in sandwich

cultured rat hepatocytes (SCRH) were determined and used to improve the extrapolation

from in vitro to in vivo for the compounds excreted from bile (Li et al., 2009; Li et al.,

2010). Meanwhile, a decrease in functional uptake in SCRH was observed raising


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concerns for its suitability as a model for active hepatic uptake evaluations (Li et al.,

2010; Kotani et al., 2011). However, unlike SCRH, based on our in house unpublished

results and the recently published data (Kotani et al., 2011), active uptake functions in

sandwich cultured human hepatocytes (SCHH) are well-maintained and the system

appears promising as a single in vitro model for evaluation of candidate drug uptake and

biliary excretion. The objectives of this research are three folds; first, confirm the

maintenance of hepatic-specific uptake transporter function and expression in SCHH;

second, optimize the experimental conditions needed to define the active hepatic uptake

and biliary excretion to obtain in vitro parameters that could be used as inputs for

mathematical PBPK model for in vivo prediction (Jones et al., 2012); and third, obtain an

in vitro cutoff values for active uptake in SCHH that would be appropriate to trigger the

clinical investigations recommended by the ITC.

Materials and Methods

Reagent and hepatocytes

HPLC grade acetonitrile, water and methanol were purchased from Burdick &

Jackson (Muskegon, MI) and EMD Chemicals, Inc (Gibbstown, NJ), respectively. Hanks


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balanced salt solution (HBSS) was purchased from Invitrogen (Carlsbad, CA).

Rosuvastatin, atorvastatin, pitavastatin valsartan, fluvastatin, pravastatin, cerivastatin,

buprenorphine, and midazolam were obtained from Sequoia Research Products Ltd.

(Oxford, UK). Rifamycin SV (Rif SV) was purchased from Sigma-Aldrich (St. Louis,

MO). Ammonium acetate was obtained from Mallinckrodt (Phillipsburg, NJ).

[3H]Taurocholate (TC, 4.6 Ci/mmol) was purchased from PerkinElmer Life Sciences

(Boston, MA). The BCA kit was purchased from Pierce Biotechnology (Rockford, IL).

The ProteoExtract® native membrane protein extraction kit was purchased from

Calbiochem (Temecula, CA). Trypsin was purchased from Promega (Madison, WI).

MatrigelTM (phenol red free) and collagen coated 24 well plates were obtained from BD

Biosciences (Franklin Lakes, NJ). In Vitro GRO-HT, In Vitro GRO-CP and In Vitro

GRO-HI hepatocytes media were purchased from Celsis In Vitro Technologies

Inc.(Baltimore, MD). Cryopreserved human hepatocyte (lot Hu4165) was purchased from

CellzDirect (Pittsboro, NC).

Sandwich cultured human hepatocytes (SCHH)

Cryopreserved hepatocytes were thawed and plated as described previously (Bi et

al., 2006). In brief, hepatocytes were thawed in a water bath at 37°C, and then

immediately poured into 50 mL in pre-warmed In Vitro GRO-HT medium in a conical


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tube. The cells were then centrifuged at 50 × g for 3 minutes and resuspended 0.85 × 106

cells/mL in In Vitro GRO-CP medium. Cell viability was determined by trypan blue

exclusion. On day 1, hepatocyte suspensions were seeded in BioCoat 24-well plates in a

volume of 0.5 mL/well. After incubation overnight at 37ºC, the hepatocytes were overlaid

with 0.5 mL IN VITRO GRO-HI medium with MatrigelTM (0.25 mg/mL). The IN VITRO

GRO-HI media were refreshed every 24 hr.

Extraction and digestion of membrane protein

At day 5 post culture, SCHH were detached from cell culture plates and washed

with HBSS. Along with suspension hepatocytes, the membrane protein fraction of

hepatocytes was extracted as described previously (Li et al., 2008) using the

ProteoExtract® native membrane protein extraction kit (Calbiochem). Briefly, hepatocyte

pellets were homogenized in extraction buffer I of the kit containing a protease inhibitor

cocktail followed by incubation at 4 oC for 10 minutes with gently rocking. The

homogenate was centrifuged at 16,000 x g for 15 minutes at 4 oC. The supernatant

containing cytosolic proteins was discarded and the pellets were re-suspended in

extraction buffer II of the kit containing a protease inhibitor cocktail. After 60 minutes of

incubation at 4 oC with gentle rocking, the suspension was centrifuged at 16,000 x g for


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15 minutes at 4 oC. The protein concentration in the membrane fractions was determined

using the BCA protein assay kit (Pierce Biotechnology, Inc. Rockford, IL).

LC-MS/MS quantitative measurement of OATP1B1, 1B3 and 2B1 transporters

Proteotypic peptides and stable isotope label (SIL) peptides of OATP1B1, 1B3,

and 2B1 were selected (Table 1) and synthesized as surrogate analytes for the

corresponding protein quantification by LC-MS/MS (Li et al., 2008). LC-MS

quantification for human OATP proteins and two of six peptides identified

(NVTGFFQSFK and SSPAVEQQLLVSGPGK) were also reported by Ji et al (Ji et al.,

2012) . The digestion condition were optimized by our previous report (Balogh et al.,

2012). Briefly, 80 μg of membrane fraction protein was reduced with 6 mM dithiothreitol

and alkylated with iodoacetamide in 25 mM ammonium bicarbonate digestion buffer

containing 10% sodium deoxycholate monohydrate (DOC), and then digested by trypsin

(the final concentration of DOC during digestion was 1%). At the end of digestion,

samples were acidified with an equal amount of 0.2% formic acid in water with SIL

internal standards, and centrifuged at 14,000 x g for 5 minutes. The supernatants were

transferred to a new plate and dried down. The samples were reconstituted with 0.1%

formic acid in water and analyzed by LC-MS/MS.


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The calibration curve was prepared using the synthetic proteotypic peptide with a

fixed concentration of each SIL peptide as the internal standard. Sample quantification

was conducted by coupling a triple quadrupole mass spectrometer (TQ-MS, API4000,

Applied Biosystem, Foster City, CA) to a Shimadzu High-performance liquid

chromatography (LC) system (SLC-10A, WoolDale, IL) and HTS PAL Leap autosampler

(Carrboro, NC). A Phenomenex Kinetex 2.6 µm C18 100A column (3.0 × 100 mm) was

used for peptide chromatography. A linear gradient elution program was conducted to

achieve chromatographic separation with mobile phase A (0.1% formic acid in HPLC

Grade Water), and mobile phase B (0.1% formic acid in acetonitrile). A sample volume

of 10 μl was injected onto the LC column at a flow rate of 0.5 mL/min. The parent-to-

product transitions for the proteotypic peptide generally represent the doubly charged

parent ion to the single charged product y ions for each peptide (Table 1). Data were

processed by integrating the appropriate peak areas for the analyte peptides and the SIL

internal standard peptides in Analyst 1.4.2 (Applied Biosystems, Foster City, CA).

Determination of hepatic uptake in SCHH

SCHH were rinsed twice with 0.5 ml of 37°C regular HBSS buffer or Ca2+/Mg2+-

free HBSS containing 1 mM EGTA, and then replaced with fresh regular HBSS buffer or

Ca2+/Mg2+-free HBSS containing 1 mM EGTA. The disruption of the bile canalicular


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network was achieved by pre-incubation with Ca2+/Mg2+-free HBSS containing 1 mM

EGTA buffer for 10 minutes. For determination of the effects of various inhibitors on

rosuvastatin uptake in SCHH, parallel incubations were conducted in the presence of the

uptake transporter inhibitors, Rif SV (100 μΜ), Cyclosporin A (CsA, 10 μΜ), and

gemfibrozil (30 μΜ). SCHH uptake was initiated by the addition of 500 µL containing

substrate at a concentration indicated in the figure legends, with or without inhibitors.

Reactions were terminated at designated time points by quickly washing the hepatocytes

three times with ice-cold HBSS buffer. The cells were either lysed with 0.5% Triton-100

(radiolabeled compounds) or 100% methanol containing internal standard (non-

radiolabeled compounds). Samples were analyzed either by LC-MS/MS, respectively.

LC-MS/MS Analysis of Probe Substrates

LC-MS/MS analysis of probe substrates was conducted with an API 4000 triple

quadruple mass spectrometer (PE Sciex, Ontario, ON, Canada) coupled with a turbo ion

spray interface in positive ion mode, and connected with a Shimadzu LC (SLC-10A)

system (WoolDale, IL) and Gilson 215 autosampler. The mass spectrometer was

controlled by Analyst 1.4.2 software (Applied Biosystems). The Gilson autosampler was

independently controlled by Gilson 735 software and synchronized to Analyst via contact

closure. The HPLC method consisted of a step gradient with 25 uL samples loaded onto


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a 1.5 x 5 mm Showadenko (Tokyo, Japan) ODP 13 µm particle size column using 95%

2mM ammonium acetate/5% 50/50 methanol/acetonitrile. Incubation samples and

standard curve samples were eluted with 10% 2mM ammonium acetate in 50/50 of

methanol/acetonitrile. Peak area counts of analyte compound and internal standard (IS)

were integrated using DiscoveryQuant Analyze as an add-on to Analyst 1.4.2. The

obtained values underwent data analysis by averaging the analyte area divided by the

internal standard analyte for each concentration.

Data Analysis

The apparent in vitro biliary clearance (CLbile) (Liu et al., 1999) and percent active

uptake were determined by equations 1 and 2, respectively. The hepatic uptake of test

compounds was estimated from the initial uptake phase (0.5 to 1 min) while biliary

excretion was assessed at 10 minutes. The data represent the results from a single study

run in triplicate or duplicate and a minimum of two experiments were performed. The

standard deviations or coefficient variation (CV%) was listed in the legends of figure or

table.

)(

),2/2(),(

*_ medium

FreeMgCaHBSSStd

ionconcentrattimeIncubation

onAccumulationAccumulatiCLbile

++−= Eq1

% active uptake = 100-(slope+Rif SV)/(slope-Rif SV) Eq 2


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Results

Protein expression of OATP1B1, 1B3, and 2B1 in suspension hepatocytes and SCHH

As functional active uptake has been shown previously in SCHH both in house

and in the literature (Kotani et al., 2011), in the present study, the protein expression of

OATP1B1, 1B3, and 2B1 in SCHH was measured by LC-MS/MS and compared with that

in suspension hepatocytes. Peptides proteolytically released from the target OATP

proteins were quantified using external synthetic peptide calibration curves. The peptide

fragments were monitored using multiple reactions monitoring (MRM) (Table 1). Sample

preparation, digestion, and detection limits of OATP protein quantification were

previously evaluated (Balogh et al., 2012). As shown in Table 2, while OATP1B3 and

2B1 expression levels were reduced to approximately half of that in suspension

hepatocytes, OATP1B1 expression in SCHH was slightly higher (1.5 fold) than that

found in suspension hepatocytes. The results provide support for OATP-mediated active

hepatic uptake in SCHH, which indicates that SCHH could be a suitable tool for the

assessment of active OATP uptake. In addition, the protein expression obtained by LC-

MS/MS measurement could be integrated into a mathematical model as a component of

scaling factors for in vivo extrapolation from in vitro.


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Inhibition of active uptake in SCHH

The active component of hepatic uptake can be determined by the total hepatic

uptake (PSuptake) minus the passive diffusion (PSpassive) in an in vitro hepatocyte model.

Generally, passive diffusion in hepatocytes can be obtained by either co-incubation with

an OATP inhibitor or by conducting the uptake experiment at low temperature, e. g at 4ºC.

We previously reported that the lack of uptake might be an artificial effect of a rigid cell

membrane at 4ºC and the uptake in the hepatocyte model determined at 37ºC and 4ºC

might not truly reflect the functional active uptake (Kimoto et al., 2011). To select a

suitable inhibitor blocking carrier-mediated active hepatic uptake in SCHH, time-

dependent accumulation of rosuvastatin, a known substrate of OATP proteins, was

investigated in the presence or absence of known OATP inhibitors, rifamycin SV (Rif SV,

100 μM), cyclosporin A (CsA, 10 μM) and gemfibrozil (30 μM). As depicted in Figure 1,

rosuvastatin was actively transported into SCHH and the uptake was linear up to 1.5

minutes. It is worthwhile to note that a positive Y-intercept was obtained by extending the

trendline of rosuvastatin uptake. Non-specific binding on hepatocyte surface has been

proposed to contribute the intercept and was not included here for the calculation of

initial uptake rate. The initial uptake rates of rosuvastatin estimated from 0.5 to 1 minute

were inhibited by all three OATP inhibitors, Rif SV, CsA and gemfibrozil, by 95, 80, and


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78%, respectively. The active uptake of rosuvastatin was almost completely inhibited in

the presence of Rif SV at 100 μΜ.

Hepatic uptake and biliary excretion for compounds that are the substrates of phase

I/II metabolizing enzymes or hepatic uptake transporters in SCHH

As mentioned above, rosuvastatin uptake in SCHH was nearly abolished by co-

incubation with 100 μΜ Rif SV. The results agree with previous reports that Rif SV (100

μM) totally blocks OATP functions in OATP transfected cell lines (Vavricka et al., 2002).

To determine if Rif SV also affects metabolizing enzymes, biliary excretion, and active

hepatic uptake by transporters other than OATPs, initial uptake and biliary excretion of

various compounds were further tested in SCHH. Buprenorphine and midazolam, which

are metabolized by UGT1A1 and CYP3A4, respectively, were used as compounds that

penetrate the hepatocytes via passive diffusion. TC were selected as probe substrates of

NTCP transporters. Rosuvastatin as a known OATP substrate was again tested in SCHH

for characterizing the initial uptake and biliary excretion kinetics. In addition,

rosuvastatin and taurocholate (TC) are excreted from bile through biliary efflux

transporters such as multidrug resistant protein 2 (MRP2), breast cancer resistant protein

(BCRP) or bile salt exporting pump (BSEP) (Ito et al., 2010). The uptake (PSuptake and

PSpassive) and biliary excretion (CLbile) in SCHH of the compounds are shown in Figure 2


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and Table 3. As expected, Rif SV (100 μΜ) inhibited approximately 93% and 83% of the

uptake rate of rosuvastatin and TC in SCHH, respectively. Following a decrease of uptake

into SCHH caused by the inhibition of Rif SV, biliary excretion of rosuvastatin and TC

were also substantially decreased (Table 3). Although significant increases in the

intracellular concentration of buprenorphine or midazolam in SCHH were detected in the

presence of Rif SV (Figure 2), the initial uptake rates of the compounds were not

significantly altered. The intracellular accumulation of buprenorphine or midazolam by

Rif SV might be due to the inhibition of CYP3A4 and UGT1A1 activities in SCHH.

Since no biliary excretion was detected for burperenophine and midazolam (Table 3) both

in the absence and presence of Rif SV, the results revealed that Rif SV did not change the

elimination profile by switching elimination pathways between metabolizing enzyme-

mediated clearance and transporter-mediated biliary excretion.

Hepatic uptake in SCHH for the compounds that undergo clinically significant DDIs

with OATP inhibitors

As noted above, SCHH has been characterized as a suitable model to assess in

vitro hepatic uptake (active and passive) and biliary excretion. To evaluate the risk of in

vivo OATP-mediated DDIs from the in vitro SCHH model, a literature review was


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conducted to compile the OATP substrates that undergo significant DDIs in the clinic (>2

fold increase in AUC) when co-administered with OATP inhibitors. The substrates are

listed in Table 4 and we conducted uptake and biliary excretion assays in SCHH to

determine the in vitro active uptake (PSactive) and CLbile. To avoid potential saturation of

active uptake transporters, the substrate concentrations selected either were below the

OATP Km known from literature reports or lack of saturation was confirmed by our

preliminary experiments. As indicated in Table 4, initial uptake rates into SCHH for the

compounds ranged from 2 to 45 uL/min/mg protein. Rif SV inhibitable active hepatic

uptake ranged from 55% to 84% in SCHH for the compounds reported to undergo OATP-

mediated DDIs. Although the Rif SV inhibitable active uptake (%) did not correlate with

the AUC changes that are observed in clinic (Figure 3A), these compounds were actively

uptaken into hepatocyte to the extent of greater than 50% (Figure 3A). On the other hand,

an increase of passive diffusion into hepatocytes tended to diminish the fold increase in

AUC change caused by OATP inhibitors (Figure 3B), suggesting OATP mediated DDI

risk could be low for high permeable compounds.

Discussion

Adverse clinically significant DDIs represent major challenges in drug discovery

and development. In the last two decades, preclinical in vitro /in vivo models were used to


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effectively predict human pharmacokinetics. However, the predictions were successful

for the compounds that are mainly eliminated renally or via cytochrome P-450

metabolizing enzymes (Obach, 2009). Predicting hepatic transporter mediated clearance

continues to be challenging due to large interspecies differences in hepatic transporter

homology or expression, and lack of validated in vitro tools (Lai, 2009). Hepatic drug

elimination is generally composed of a series of processes that include: entrance into

hepatocyte via passive diffusion and active uptake mediated by hepatic transporters;

metabolic elimination through phase I and/or phase II enzymes; and excretion to bile

and/or back to systemic circulation by the efflux transporters. To assess processes

involved in hepatic uptake and biliary excretion for in vivo prediction, the development of

an in vitro model that mimics the complexity of the hepatic transport system has become

imperative.

Human hepatocyte in vitro models are widely accepted as a valuable tool for

investigating drug metabolic liability and gene induction and toxicity, as well as serving

as effective screening tools for NMEs. The cellular polarity that allows vectorial transport

in vivo is disrupted rapidly when cells are isolated from the intact organ. Therefore, the

restoration of the bile canalicular network in the cultured hepatocyte model is desired for

investigating the vectorial transport of drug candidates. SCHH has been generally


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accepted as a good model to aid in predicting biliary clearance in humans (Bi et al., 2006).

Following the previous efforts to understand the expression of hepatobiliary efflux

transporters in SCHH (Li et al., 2009), in the present study, we report, for the first time,

the maintenance in SCHH of uptake hepatic transporters, OATP1B1, 1B3 and 2B1 as

measured by LC-MS/MS. This provides molecular evidence to support SCHH as a

model for obtaining functional hepatic uptake parameters for in vivo prediction.

Moreover, to better define the uptake clearance in SCHH, ideally an inhibitor that can

block all known hepatic uptake transporters with minimum effect on passive diffusion

and biliary excretion is needed. To meet these criteria, we measured rosuvastatin uptake

in SCHH co-incubated with several known OATP transporter inhibitors. Under the

concentrations applied, these inhibitors can completely block OATP1B1 or 1B3 activity

in OATP gene overexpressing systems (Vavricka et al., 2002; Yamazaki et al., 2005;

Letschert et al., 2006). As a result, Rif SV (100 μΜ) was shown to completely knock

down rosuvastatin uptake in SCHH. The inhibitor selected provided the ability in

assessing the sum of active hepatic uptakes contributed by OATP transporters expressed

in hepatocytes. In contrast, Rif SV (100 μΜ) had no effect on the passive diffusion of

midazolam and buprenorphine into hepatocytes. Rif SV also increased the intracellular

accumulation of burprenorphine and midazolam through the inhibition of metabolizing


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enzymes, such as UGT1A1 and CYP3A4. These inhibitory effects were minimized

through optimization of experimental conditions by calculating the initial uptake rate to

avoid the artificial effect on hepatic uptake caused by the inhibitory effects of Rif SV on

metabolizing enzymes. Moreover, the reduced biliary excretion is observed followed the

decreases of hepatic uptake. Since the intracellular accumulation of the compounds was

not observed (Table 3, 4 and Figure 2) with or without Ca2+, we speculate that the

reduced biliary excretion was caused by the inhibitory effects on hepatic uptake.

However, direct inhibitory effects on hepatobiliary efflux transporters still remain to be

further investigated as Rif SV appears as an inhibitor of efflux transporters including bile

salt export pump (BSEP) (Wang et al., 2003).

Three isoforms (OATP1B1, OATP1B3 and OATP2B1) are considered to play a

pivotal role in the hepatic uptake of xenobiotics and endogenous compounds on the

sinusoidal membrane of hepatocytes (Giacomini et al., 2010). The OATPs transport drugs

from a wide range of therapeutic classes including the 3-hydroxymethylglutaryl-CoA

reductase inhibitors (statins), angiotensin II receptor antagonists (e.,g., olmesartan and

valsartan), angiotensin-coverting enzyme inhibitors (enalapril and temocaprilat), the H1-

receptor antagonist fexofenadine, and the endothelin receptor antagonist, bosentan

(Giacomini et al., 2010). As the OATP proteins are poorly conserved evolutionarily as


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evidenced by the lack of human orthologues in rodents, extrapolation of in vivo human

from rodent models remains limited. The ITC recommends that the clinical investigation

cascade should be initiated when active hepatic transport is involved in the liver

clearance pathway and outlines decision trees for in vitro evaluation of hepatic uptake

using a hepatocyte model to predict the potential risk of clinical DDIs. The investigation

cascades are considered to be similar to the in vitro studies of drug metabolism and

interaction (Giacomini et al., 2010). As a result, developing in vitro models that can

predict OATP mediated DDIs is an efficient and inexpensive approach that could reduce

or eliminate the need for further clinical investigation. However, the extent of in vitro

active hepatic uptake necessary to trigger the clinical assessment of DDI was not

provided (Giacomini et al., 2010). In addition, the performance of the in vitro hepatocyte

models should be evaluated to increase confidence in obtaining outcomes through

retrospective analysis. With this in mind, a literature review was conducted and the

compounds with reported OATP-mediated clinical DDI were tested in our optimized

SCHH model. As expected, active hepatic uptake of the compounds with clinically

significant OATP DDIs was observed. The contribution of the active portion to overall

hepatic uptake was high, being 55 to 84% of the total uptake rate. As hepatocyte lot

differences in transporter expression exist, it is important that we confirmed the OATP


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expression in SCHH, and compared the active hepatic uptake in multiple hepatocyte lots

(Supplemental Table 1).These results suggest that 50% active hepatic uptake in SCHH

could be the in vitro cutoff to trigger the clinical risk assessment of hepatic transporter-

mediated DDIs.

The relationship among solubility, passive permeability, and the effects of drug

transporter and metabolizing enzymes on drug disposition has been well addressed by the

biopharmaceutics drug disposition classification system (BDDCS) (Wu and Benet, 2005).

As depicted in Figure 3B, the fold increase of AUC tended to decrease as the PSpassive

in SCHH increased. The results suggest that low permeability drugs that rely primarily on

transporter uptake for entry are prone to clinical DDIs mediated by OATP transporters.

When applying the classification system, transporter effects are predicted to be minimal

for high permeability/high solubility Class 1 compounds (Wu and Benet, 2005). In the

gastrointestinal space, good solubility is essential for saturation of efflux transporters to

obtain good absorption. Once the compounds are absorbed (into the systemic space), high

permeability/low solubility Class 2 compounds could behave similarly to Class 1

compounds, in that the high permeability can overcome the transporter effects, and

therefore reduce the risk of transporter mediated DDIs by competing drug entering into

hepatocytes. This simple categorization under BDDCS suggests that the high vs low


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permeability designation reflects the differences in freedom of access to phase I and/or

phase II metabolizing enzymes within hepatocytes. In addition to the factors described

here, hepatic blood flow needs to be considered as under flow limited conditions the

impacts of inhibition of uptake transport could be reduced.

It is interesting to note that atorvastatin is categorized as class 2 in the previous

report (Wu and Benet, 2005). However, atorvastatin was shown to be have limited

diffusion into SCHH in present study, and could be categorized as a class 4 compound

(9.3 uL/min/mg of atorvastatin vs. 91 ul/min/mg of propranolol, data not shown). In this

regard, additional investigations are proposed to better understand the passive diffusion

cutoff using cellular uptake model, e.g SCHH. Some exceptions were also found in the

relationship between passive permeability and AUC increase observed in clinic. While

cerivastatin was a high permeable compound in SCHH (15 μL/min/mg), a significant

AUC increase (4.8 and 5.6 fold) was reported when cerivastatin was co-administered

with the OATP inhibitors, CsA and gemfibrozil, respectively (Figure 3B, circle marked).

Cerivastatin interacted with OATP proteins and is also extensively metabolized by

CYP2C8 and CYP3A4 in liver via demethylation of the benzylic methyl ether moiety

(Muck, 2000). CsA and Gemfibrozil are potent inhibitors of OATP transporters, as well

as inhibiting CYP metabolizing enzymes. These clinical observations could be explained


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by the inhibition of multi-clearance pathways resulting in a sum of effects on overall

hepatic clearance. Due to lack of exposure data, it is also worthwhile to note that outliers

were anticipated with co-administration of CsA, as the inhibition of OATP transporters

may have been insufficient in vivo (Figure 3 below the dotline). Collectively, caution

should be raised in that the interplay between transporters and metabolizing enzymes

could generate a multi-level complexity in predicting clinical DDI from an in vitro

system.

In conclusion, SCHH maintains hepatic transporter expression and functional

activity, and appears to be a well-characterized in vitro model for prediction of in vivo

human PK. Rif SV inhibited the active uptake of OATP transporters, demonstrating it was

an OATP inhibitor useful to estimate the extents of active and passive uptake in SCHH.

The optimization of the experimental design minimized the impacts of inhibitory effects

on metabolizing enzymes. Retrospective analysis for the compounds that undergo

clinically significant hepatic transporter-mediated DDIs suggested that 50% or greater

active hepatic uptake in SCHH with low passive permeability would have a potential risk

of clinical DDIs and this value could serve as a cutoff to trigger the clinical investigation

cascade for DDI risk assessment.


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Acknowledgements:

We would like to acknowledge Dr. Larissa M Balogh for the help on OATP protein

quantification and the editing of manuscript. We also thank Andrea Clouser-Roche for

bioanalytical support and Drs Theodore E. Liston, Larry M. Tremaine, Bo Feng,

Manthena V. Varma, John Litchfield, and Hendrik Neubert for their helpful scientific

comments and suggestions.


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Authorship contributions

Participated in research design: Y.B., E.K., H.A.B., H.M.J., Y.L

Conducted experiments: Y.B., E.K., S.S., S.K., K.M.W., H.Z

Contributed new reagents or analytic tools: Y.B., E.K.

Performed data analysis: Y.B., E.K., S.S., H.M. J., H.A.B., S.K., K.M.W., H.Z., C.J., K.S.F.,

A.F.E., Y.L

Wrote or contributed to the writing of the manuscript: Y.B., E.K., S.S., H.M J., H.A.B.,

S.K., K.M.W., H.Z., C.J., K.S.F., A.F.E., Y.L


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Footnotes:

The authors were all employees of Pfizer during this research and declare no conflicts of

interest. YB and EK are equal contributors.


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Figure Legends

Figure 1. Inhibitory effect of CsA , gemfibrozil and Rif SV on rosuvastatin uptake in

SCHH. The uptake of rosuvastatin (1µM) was measured at 37 ºC in the presence and

absence of CsA (10 µM), gemfibrozil (30 µM) and rif SV (100 µM). Data are presented

as mean ± SD.

Figure 2. Hepatic uptake and biliary excretion of several compounds in SCHH. The

hepatic uptake was investigated at 37 ºC in the presence and absence of Rif SV (100 µM)

or in the buffer with/without Ca2+/Mg2+. A: midazolam (1µM), B: buprenorphine (0.2µM),

C: TC (1µM) and D: rosuvastatin (1µM). Data are presented from single studies run in

duplicate or triplicate. A minimum of two experiments were performed on different day

to verify coefficient of variation (CV%)

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TABLES

Table 1. Target peptides and MRM transitions monitored for human OATP proteins

m/z

Protein Peptide Q1 Q3

OATP1B1 NVTGFFQSFK 587.8 961.4, 860.4, 656.3

NVTGFFQSFK* 591.8 969.4, 868.4, 664.3

OATP1B3 NVTGFFQSLK 570.8 927.4, 826.4, 622.3

NVTGFFQSL*K 574.3 934.4, 833.5, 629.3

OATP2B1 SSPAVEQQLLVSGPGK 798.9 711.9, 445.2, 1155.6

SSPAVEQQLLVSGPGK* 802.9 715.9, 453.2, 1163.6

m/z: mass to charge ratio of the ion. *, stable isotope labeled amino acid.


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Table 2. Quantification of OATP1B1, 1B3 and 2B1 in suspension hepatocytes and SCHH

of lot Hu4165. The protein expression of OATP1B1, 1B3, and 2B1 in SCHH was

measured by LC-MS/MS and compared with that in suspension hepatocytes. * P

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Table 3. Comparison of initial rate of hepatocyte uptake in absence or presence of Rif SV.

Substrates were incubated in the presence and absence of the inhibitor Rif SV (100 µM)

for passive and active uptake, or in the buffer with/without Ca2+ for in vitro biliary

clearance (CLbile). Data are presented from single studies run in duplicate or triplicate. A

minimum of two experiments were performed on different day to verify coefficient of

variation (CV%)

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Table 4. OATP related drug-drug interactions and hepatic active uptake in SCHH.

Clinical substrates were incubated in the presence and absence of the inhibitor Rif SV

(100 µM) for passive and active uptake, or in the buffer with/without Ca2+ for in vitro

biliary clearance (CLbile). Data are presented as the mean of duplicates or as the mean

(SD) of 3~5 experiments.

Inhibitors Substrates

Control Rif SV (100 μΜ) Active uptake (%)

AUC changes (Fold)

Cmax changes (Fold)

Reference Substrate concentrat

ion (μM)

PSuptake CLbil

e PSpassive CLbile

uL/min/mg protein

CsA

Atorvastatin

1 22(5.9) 1.4 9.3(1.3) ~0 58 (6)

14.3 12.6 (Lemahieu et al., 2005)

Atorvastatin 7.7 9.65 (Hermann et al., 2004)

Atorvastatin 6.44 5.59 (Asberg et al., 2001)

Bosentan 1 45 1.9 8 ~0 82 0.97 0.67 (Binet et al., 2000)

Cerivastatin 1 31.8(5.0) 0.2 15(1.7) ~0 55 (3) 3.75 5.0 (Muck et al., 1999)

Fluvastatin

1 31(8.4) 3.3 11(7.5) ~0 72(7.1)

2.10 5.0 (Park et al., 2001)

Fluvastatin 2.55 3.11 (Park et al., 2001)

Fluvastatin 0.94 0.3 (Goldberg and Roth,

1996)

Fluvastatin 0.89 1.65 (Holdaas et al., 2006)

Pitavastatin 1 36.5(4.2) 0.4 11.9(0.7) 67(5.6) 3.6 5.6 (LIVALO)

pravastatin 1 2.4 (0.91) 0.4 0.5 (0.35) 0.1 79.1(18)

12.2 7.4 (Park et al., 2002)

pravastatin 8.93 6.78 (Hedman et al., 2004) Pravastatin 21.8 6.9 (Regazzi et al., 1993)

Rosuvastatin 1 8.3 (1.5) 2.6 1.5(1.0) 0.5 84(14) 6.08 9.6 (Simonson et al., 2004)

Repaglinide 0.2 61(38) 0.2 24(6.4) 0.4 55(17.7) 1.44 0.75 (Kajosaari et al., 2005)

Erythromycin Pitavastatin 1 36.5(4.2) 0.4 11.9(0.7) 67(5.6) 1.8 2.6 (LIVALO)

Gemfibrozil

Cerivastatin 1 31.8(5.0) 0.2 15(1.7) ~0 55 (3) 4.59 2.07 (Backman et al., 2002)

Pravastatin 1 2.4 (0.91) 0.4 0.5 (0.35) 0.1 79.1(18) 1.02 0.81 (Kyrklund et al., 2003)

Rosuvastatin 1 8.3 (1.5) 2.6 1.5(1.0) 0.5 84(14) 0.88 1.21 (Schneck et al., 2004)

lopinavir and ritonavir

Atorvastatin 1 22(5.9) 1.4 9.3(1.3) ~0 58 (6) 6.82 (2.4) 11.7 (7.6) (Lau et al., 2007)

Bosentan 1 45 1.9 8 ~0 82 (16) 4.22 5.12 (Dingemanse et al., 2010)

Rifampin

Atorvastatin 1 22(5.9) 1.4 9.3(1.3) ~0 58 (6) 7.52 13.85 (He et al., 2009)

Pravastatin 1 2.4 (0.91) 0.5 (0.35) 79.1(18) 1.33 1.73 (Deng et al., 2009)

Atorvastatin 1 22(5.9) 1.4 9.3(1.3) ~0 58 (6) 8.36 7.61 (Pham et al., 2009)

tipranavir and ritonavir

Rosuvastatin 1 8.3 (1.5) 2.6 1.5(1.0) 0.5 84(14)

0.37 1.33 (Pham et al., 2009)

atazanavir and ritonavir

Rosuvastatin 1.13 5.00 (Busti et al., 2008)


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