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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.
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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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Schneck DW, Birmingham BK, Zalikowski JA, Mitchell PD, Wang Y,
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Lasseter KC, Brown CD, Windass AS and Raza A (2004) The effect
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Schneck DW (2004) Rosuvastatin pharmacokinetics in heart
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(2002) Interactions of
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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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