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DRUG METABOLISM AND DISPOSITION
Copyright ª 2015 by The American Society for Pharmacology and Experimental Therapeutics
http://dx.doi.org/10.1124/dmd.115.065581
Drug Metab Dispos 44:50–60, January 2016
Evaluation of Normalization Methods To Predict CYP3A4 Induction in
Six Fully Characterized Cryopreserved Human Hepatocyte
Preparations and HepaRG Cells s
Hélène Vermet, Nathalie Raoust, Robert Ngo, Luc Esserméant, Sylvie Klieber, Gérard Fabre,
and Xavier Boulenc
Drug Disposition Domain, Disposition, Safety and Animal Research Scientific Core Platform (H.V., N.R., R.N., S.K., G.F., X.B.);
Biostatistics and Programming, Clinical Sciences & Operations, Scientific Core Platform (L.E.), Sanofi Recherche & Développement,
Montpellier, France
Received May 26, 2015; accepted October 13, 2015
Prediction of drug–drug interactions due to cytochrome P450
isoform 3A4 (CYP3A4) overexpression is important because this
CYP isoform is involved in the metabolism of about 30% of clinically
used drugs from almost all therapeutic categories. Therefore, it is
mandatory to attempt to predict the potential of a new compound to
induce CYP3A4. Among several in vitro–in vivo extrapolation methods recently proposed in the literature, an approach using a scaling
factor, called a d factor, for a given hepatocyte batch to provide
extrapolation between in vitro induction data and clinical outcome
has been adopted by leading health authorities. We challenged the
relevance of the calibration factor determined using a set of 15
well-known clinical CYP3A4 inducers or the potent CYP3A4 inducer
rifampicin only. These investigations were conducted using six
batches of human hepatocytes and an established HepaRG cell line.
Our findings show that use of a calibration factor is preferable for
clinical predictions, as shown previously by other investigators.
Moreover, the present results also suggest that the accuracy of
prediction through calculation of this factor is sufficient when
rifampicin is considered alone, and the use of a larger set of fully
characterized CYP3A4 clinical inducers is not required. For the
established HepaRG cell line, the findings obtained in three experiments using a single batch of cells show a good prediction accuracy
with or without the d factor. Additional investigations with different
batches of HepaRG cell lines are needed to confirm these results.
Introduction
intrinsic metric for investigating CYP induction. Indeed, the mRNA
expression data are in general more sensitive compared with enzymatic
activity for detecting induction in human hepatocytes, and give more
information if the drug is also a P450 inhibitor (Fahmi et al., 2010).
Predictive mathematical models incorporating either induction alone
or induction in combination with inhibition mechanisms have been
applied by a number of authors (Fahmi et al., 2008b; Shou et al., 2008;
Fahmi and Ripp, 2010; Kirby et al., 2011; Templeton et al. 2011).
Dynamic models based on an inducer concentration-time profile to
account for the change in enzyme expression have also been proposed
(Almond et al., 2009; Fahmi et al., 2009).
Some years ago, a calibration factor approach was proposed, which
used a set of clinically well-known CYP3A4 inducers in a mathematical
static model (Fahmi et al., 2008a). In this method, a d factor was
determined for each in vitro human hepatocyte batch used in the assay.
The d parameter represented an empirical calibration factor for the
purpose of in vitro to in vivo induction scaling, and its value was
estimated through correlation and minimization of predicted and
observed area under the curve (AUC) ratios for the set of known
inducers. The method initially proposed by Fahmi et al. (2008a) has
been adopted by the U.S. Food and Drug Administration in its DDI
guidance (CDER 2011).
Over the last 15 years, drug–drug interactions (DDI) have become
one of the emerging topics in clinical drug development process
(Boulenc and Barberan, 2011). In the late 1990s health authorities
issued dedicated guidelines, which have been recently updated, related
to the detection and consequences of DDIs (CDER 2011; CHMP 2012).
The cytochrome P450 3A subfamily enzymes play a major role in the
metabolism of about 30% of clinically used drugs from almost all
therapeutic categories (Zanger and Schwab, 2013). Therefore, CYP3A4
isoform induction has been of particular interest, with several attempts to
predict clinical consequences from in vitro results (Fahmi et al., 2008a,b;
Almond et al., 2009; Fahmi and Ripp, 2010; Einolf et al., 2014).
In the majority of reported cases, the induction mechanism is due to
activation of key transcription factors. Kliewer et al. (1998) first
identified an orphan nuclear receptor, pregnane X receptor (PXR), that
transcriptionally activates the CYP3A gene by interacting with the PXR
response elements in the genes. Even if the final physiologically
relevant effect is the enzyme activity, the mRNA increase is the most
dx.doi.org/10.1124/dmd.115.065581.
s This article has supplemental material available at dmd.aspetjournals.org.
ABBREVIATIONS: AUC, area under the curve; DMSO, dimethylsulfoxide; DDI, drug–drug interaction; Emax, maximal fold-induction; EC50,
concentration resulting in half-maximal induction; fm, fraction metabolized; Fuhep, fraction unbound in hepatocytes; Fup, fraction unbound in plasma;
GMFE, geometric mean fold error; LC-MS/MS, liquid chromatography with tandem mass spectrometry; MAE, mean absolute error; NPE, negative
predictive error; PPE, positive predictive error; PXR, pregnane X receptor; RMSE, root mean squared error; RMSLE, root mean squared logarithmic
error; SAPE, streptavidin-conjugated R-phycoerythrin.
50
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ABSTRACT
51
Normalization Methods To Predict CYP3A4 Induction
TABLE 1
ratios for the set of 15 known inducers. To reach our conclusion in terms
of the recommended method, we also took into account time and
resources needed for each of them.
Cell donor information
Identification
Supplier
Donor Characteristics
CD-Hu4237
GIBCO/Life
Technologies
BD Gentest
Bioreclamation
BD Gentest
GIBCO/Life
Technologies
In Vitro ADMET
Laboratories
GIBCO/Life
Technologies
Female, 57 year old, Caucasian, anoxia
BD-295
IVT-IBG
BD-281
CD-Hu8084
HH1024
HepaRG
Female,
Female,
Female,
Female,
41
67
49
59
year
year
year
year
old,
old,
old,
old,
Caucasian,
Caucasian,
Caucasian,
Caucasian,
anoxia
anoxia
CVA
CVA
Male, 48 year old, Caucasian, anoxia,
CVA
Female, adult, hepatocarcinoma
CVA, cerebrovascular accident.
TABLE 2
Metabolic capacity assessment of human hepatocyte preparations
Hepatocyte Preparation
CD-Hu4237
BD-295
IVT-IBG
BD-281
CD-Hu8084
HH1024
Reference historical data
n
Mean 6 S.D.
ND, not determined.
a
Expressed in nmol/h/106 hepatocytes.
Phenacetin O-Deethylase
(CYP1A2)a
Tolbutamide-Hydroxylase
(CYP2C9)a
Dextromethorphan O-Demethylase
(CYP2D6)a
Midazolam 1ʹ-Hydroxylase
(CYP3A)a
0.169
0.171
0.551
0.894
0.182
1.175
0.005
0.027
0.057
0.066
0.088
0.090
0.233
0.896
2.003
ND
0.286
0.840
0.428
0.536
0.764
1.002
0.167
0.640
82
0.978 6 0.782
83
0.055 6 0.035
100
0.812 6 0.787
85
0.746 6 0.597
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
Human hepatocyte donors used in in vitro induction models show a
substantial interbatch variability due to considerable differences in the
quality and viability of the isolated hepatocytes as well as interdonor
variability in their basal cytochrome P450 levels that consequently
leads to variation in their respective levels of induction by an inducer
compound (Shou et al., 2008). Such interindividual variability is not
uncommon and imposes a degree of uncertainty in predicting the
clinical consequences of induction. Therefore, alternatives to the
use of primary human hepatocyte cultures as models have been
investigated.
Among these alternatives, the human HepaRG cell line is one of the
most suitable human hepatic cell lines due to the retention of key liver
functionality (Kanebratt and Andersson, 2008; Turpeinen et al., 2009;
Templeton et al. 2011). This model is considered useful for the
evaluation of DDIs as most of the common CYP isoform activities
have been measured in this cell line and shown to be both selectively
inhibited and induced by prototypical CYP-selective inhibitors and
inducers at comparable levels to those of primary cultures of human
hepatocytes (Turpeinen et al., 2009). Recently, in vitro HepaRG
CYP3A4 induction data were used to predict a large number of DDIs.
The investigators demonstrated similar predictive accuracy using the
HepaRG cell line compared with the primary hepatocyte culture model
(Grime et al., 2010).
In the current work, d factor values have been determined, for each of
the six cryopreserved human hepatocyte batches as well as for the
HepaRG cell line through the comparative use of both total and
unbound plasma clinical Cmax values for 15 well-known inducers.
Three approaches have been evaluated to establish optimal accuracy: 1)
d not calculated (i.e., d = 1); 2) d value determination based on predicted
and observed effects of rifampicin only; 3) d value estimated through
minimization of the distance between predicted and observed AUC
Materials and Methods
Compounds. Carbamazepine, nifedipine, phenobarbital, phenytoin, pioglitazone, pleconaril, rifampicin, rifapentine, rosiglitazone, troglitazone, and
aprepitant were purchased from Sigma-Aldrich (St. Louis, MO). Four proprietary compounds, obtained from Sanofi Research and Development, called SARA,
SARB, SARC, and SARD were also selected based on the availability of their
clinical and in vitro induction results.
Chemicals. Dimethylsulfoxide (DMSO) and the cytotoxic references diclofenac, 4-hydroxytamoxifen, and menadione were purchased from Sigma-Aldrich
(St. Louis, MO). All other chemicals and reagents used were obtained from usual
commercial sources, and were of the highest commercially available grade.
Cell Media for Cryopreserved Human Hepatocytes. The plating medium
was composed of Ham’s F-12 and Williams’ E medium (50/50, v/v), both
purchased from GIBCO/BRL (Bethesda, MD), supplemented with 10% decomplemented fetal calf serum (GIBCO, Paisley, United Kingdom), 10 mg/l
insulin, 0.8 mg/l glucagon (Sigma-Aldrich, St. Louis, MO), 100 IU penicillin G,
and 100 mg/ml streptomycin (GIBCO).
Culture medium was also composed of Ham’s F-12 and Williams’ E medium
(50/50, v/v) that was devoid of serum but supplemented with 3.6 g/l HEPES,
4 mg/l ethanolamine, 10 mg/l transferring, 1.4 mg/l linoleic acid-albumin,
252 mg/l D-glucose, 44 mg/l sodium pyruvate, 50 mg/l ascorbic acid, 104 mg/l
arginine, and 0.7 g/l L-glutamine (all purchased from Sigma-Aldrich).
Cell Media for HepaRG Cells. The plating medium was composed of
Williams’ E medium with Glutamax (GIBCO/BRL) and supplemented with
HepaRG Thaw, Seed, and General Purpose Supplement (BIOPREDIC International, Rennes, France). For culture, Williams’ E medium with Glutamax was
supplemented with HepaRG Serum-free Induction Supplement (BIOPREDIC
International). Cells were seeded onto 48-well collagen I–coated plates purchased
from BD Biosciences (Bedford, MA).
Human Hepatocytes and HepaRG Cells. Six batches of plateable
cryopreserved human hepatocytes were used. They were obtained from
GIBCO/Life Technologies (Carlsbad, CA) for CD-Hu4237 and CD-Hu8084,
from BD Gentest (Woburn, MA) for BD-281 and BD-295, from Bioreclamation
(Baltimore, MD) for IVT-IBG, and from In Vitro ADMET Laboratories
(Columbia, MA) for HH1024. One single batch of cryopreserved HepaRG cells
(1247818) was obtained from GIBCO/Life Technologies.
Thawing Procedures for Cryopreserved Human Hepatocytes and
HepaRG Cells. Briefly, the vials containing the cryopreserved cells were
removed from liquid nitrogen storage, thawed in a 37C water bath (75–90
seconds), and then quickly poured into prewarmed seeding medium following
the vendor’s protocol. Experiments with the same batch of HepaRG cells were
performed using three independent thawings to investigate the reproducibility of
the effects of the panel of inducers (interstudy variability).
Human Hepatocyte Cell Culture and Treatment. Before seeding, cell
viability was estimated using the Trypan blue dye exclusion test. The human
hepatocyte cell density was adjusted to 0.8 106 viable cells per ml of medium.
52
Vermet et al.
TABLE 3
Metabolic capacity assessment of HepaRG cells
Cell Preparation
Phenacetin
O-Deethylase
(CYP1A2)a
Bupropion-Hydroxylase
(CYP2B6)a
Midazolam
1ʹ-Hydroxylase
(CYP3A)a
HepaRG cells (1247818)
0.300
0.402
2.298
Test compound stability ¼
½Compound2h or 24h
100
½Compound0h
Induction Assay. Quantification of CYP3A4 mRNA induction was
performed using the Quantigene Plex 2.0 technology. The reagents used in the
assay, including bDNA molecules (preamplifier, amplifier, label probe, and
streptavidin-conjugated R-phycoerythrin [SAPE]), were obtained from the
QuantiGene Plex 2.0 assay kit (Affymetrix, Santa Clara, CA). After a 48-hour
incubation period with the test compounds, the cell culture medium was
removed, and the cells were lysed with 100 ml of diluted lysis mixture buffer
to release the RNA. Specific mRNA transcripts for CYP3A4 and b2-microglobulin (b2M, the housekeeping gene) were captured on their respective beads
through a specific probe interaction during an overnight hybridization. Unbound
materials were washed from the beads (complexed with probe set and mRNA)
using a Hydroflex magnetic plate washer (Tecan, Männedorf, Switzerland). The
signal was amplified by a sequential hybridization of DNA probes (2.0
preamplifier, 2.0 amplifier and biotinylated labeled probe, respectively) for 1
hour at 50C. Three washes were performed after each hybridization step. After a
final wash, SAPE was added, and the beads were incubated for 30 minutes at room
temperature. The beads were then washed to remove unbound SAPE, and the samples
were analyzed on a Luminex 200 system (Luminex, Austin, TX) or a Bio-Plex 200
system (Bio-Rad Laboratories, Hercules, CA). The levels of SAPE fluorescence were
proportional to the amounts of mRNA transcripts captured by the beads.
TABLE 4
Clinical trials used in the analyses
Total of 23 trials and 18 victim CYP3A4 substrate/perpetrator inducer compound pairs for the set of 15 test inducer compounds. Fup is
the fraction unbound in plasma and Fuhep is the fraction unbound in the in vitro hepatocyte model of each of the test inducer compounds.
Perpetrator
Victim
No. of Trials
Reference
(Supplemental Data)
AUC Ratio Observed
Fup
Fuhep
Carbamazepine
Nifedipine
Phenytoin
Phenytoin
SARA
SARB
Pioglitazone
Pioglitazone
Rifampicin
Rifampicin
Rifapentine (4 doses)
Phenobarbital
Troglitazone
Rosiglitazone
SARC (3 doses)
SARD
Pleconaril
Aprepitant
Simvastatin
Midazolam
Midazolam
Quetiapine
Midazolam
Midazolam
Midazolam
Simvastatin
Midazolam
Simvastatin
Midazolam
Nifedipine
Midazolam
Nifedipine
Midazolam
Midazolam
Midazolam
Midazolam
1
1
1
1
1
1
1
1
1
1
4
1
1
1
3
1
1
1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
0.26
1
0.06
0.2
0.82
0.73
0.74
0.98
0.08
0.1
0.07; 0.07; 0.07; 0.07
0.39
0.33
1
0.67; 0.57; 0.33
0.2
0.65
0.78
0.25
0.05
0.80
0.80
0.01
0.08
0.01
0.01
0.25
0.25
0.01
0.50
0.01
0.01
0.01
0.01
0.01
0.01
0.52
0.90
0.83
0.83
0.07
0.89
0.80
0.80
0.42
0.42
0.57
1.00
0.22
0.87
0.68
0.94
0.13
0.09
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
The hepatocytes were then seeded onto collagen I–coated 48-well plates at
0.16 106 viable cells per well in 200 ml of medium. Plating efficiency was
evaluated around 4 hours after seeding for the hepatocytes and then daily over the
2 additional days of culture in the presence of CYP inducers. Cells were cultured in
a 37C thermostatically controlled incubator with 5% CO2 and 95% relative humidity.
After the cell attachment period, the plating medium was removed, and the
hepatocytes were treated daily for 2 consecutive days (approximately 48 hours),
with 100 ml per well of fresh culture medium containing either the vehicle control
(DMSO) or the investigated compounds at eight preoptimized concentrations
(based on compounds’ cytotoxicity, solubility, and EC50 [concentration resulting
in half-maximal induction] found in literature) ranging from 0.01 to 30 mM for
rifampicin, rifapentine, aprepitant, and troglitazone, from 0.01 to 60 mM for
SARD, from 0.03 to 100 mM for pioglitazone, SARB, and SARA, from 0.1 to
300 mM for nifedipine, phenytoin, rosiglitazone, SARC, and pleconaril, from 0.3
to 1000 mM for carbamazepine, and from 1 to 3000 mM for phenobarbital. For
each batch of hepatocytes, two separate wells for each concentration of a test
compound were prepared. The final solvent (DMSO) concentration in the incubation medium ranged from 0.1% to 1% (depending on compound solubility). For
incubations in the absence of compound (vehicle control), DMSO, as vehicle, was
added, to incubation medium to provide the same final solvent concentration range
of 0.1% to 1% as that used for the test compounds. Cell donor information is
summarized in Table 1. Basal enzymatic activities for each human hepatocyte
batch are summarized and compared with historical data in Table 2.
HepaRG Cell Culture and Treatment. Before seeding, cell viability was
estimated using the Trypan blue dye exclusion test. The HepaRG cell density was
adjusted to 1.2 106 viable cells/ml of medium. The HepaRG cells were then
seeded onto collagen I–coated 48-well plates at 0.36 106 viable cells per well
in 300 ml of medium. Plating efficiency was evaluated around 6 hours after
seeding and daily over the 2 additional days of culture in the presence of CYP
inducers. Cells were cultured in a 37C thermostatically controlled incubator
with 5% CO2 and 95% relative humidity. After a cell attachment period of 3
days, the plating medium was removed, and the HepaRG cells were treated daily
for 2 consecutive days under the same conditions as described earlier for human
hepatocytes. Basal enzymatic activities are summarized in Table 3.
Assessment of Test Compounds Cytotoxicity. Microscopical examination
of hepatocyte morphology was used to evaluate cytotoxicity during incubation of
each test compound. Moreover, to quantify the potential cytotoxic effects of the
compounds in each experiment, a cytotoxicity assessment was also performed in
parallel to the induction experiments. Specifically, test compound cytotoxicity
was evaluated using an in vitro toxicity kit that measured ATP levels in the cells
after a 48-hour exposure period to the test compound (CellTiter-Glo; Promega,
Madison, WI).
Assessment of Test Compounds Stability. The concentration, in medium,
of each compound was measured at three different time points (0, 2, and 24
hours, in duplicate) during the last day of their respective incubation period to
determine the exposure of human hepatocytes to the incubated compounds.
Liquid chromatography with tandem mass spectrometry (LC-MS/MS) analyses were performed using an Acquity UPLC System I-Class, equipped with a
Waters Acquity UPLC BEH C18 column (2.1 mm i.d. 100 mm length,
1.7 mm particle size) coupled to a Xevo TQS mass spectrometer (all from
Waters, Milford, MA).
The percentage of remaining compound at 2 or 24 hours was calculated as
follows:
53
Normalization Methods To Predict CYP3A4 Induction
Two duplicate assays (n = 2) were performed for all the described experimental samples. All multiplex data were derived from measuring median
reporter fluorescence from 50 beads per gene per well assayed, and were
presented as median fluorescence intensity. All data were corrected for background signals determined in the absence of target mRNAs. The gene of interest
and the housekeeping gene (b2-microglobulin, b2M) levels (median fluorescence intensity) were both determined in two different tubes of the same sample,
and the mean of the two values was determined. Thereafter, the measured amount
of the gene of interest was normalized to the levels of the housekeeping gene in
the same sample.
All results were expressed as the expression level of the investigated gene in the
treated-hepatocytes, relative to control conditions (calibrator).The calibrator used
was “untreated hepatocytes” (i.e., hepatocytes treated over the same period of time
with DMSO alone). The fold-induction for each investigated compound relative to
the level of vehicle control mRNA expression was calculated as follows:
Fold-induction relative to vehicle control ¼ Ecompound Evehicle control
with Evehicle control for mRNA expression equal to 1:
AUCi
1
¼
AUC dEmax ½Inducer
1 þ EC50 þ½Inducer fm þ ð1 2 fmÞ
ð1Þ
where fm is the fraction of the substrate probe drug metabolized by CYP3A4
(e.g., 0.91 for midazolam), [Inducer] is the unbound or total plasma concentration of the perpetrator inducer (i.e., Cmax), and d factor, EC50, and Emax are as
previously defined.
Data Set and Analysis. Three approaches were evaluated: 1) d not calculated
(d = 1); 2) d value determination based on the predicted (with eq. 1) and observed
effects of rifampicin alone; and 3) d value estimated through minimization of the
distance between the predicted (calculated with eq. 1) and observed AUC ratios
for the set of the 15 well-known inducers, using the Brent’s method in “optim”
function of R software version 3.0 (www.r-project.org).
The retained distances were GMFE (geometric mean fold error), RMSE (root
mean squared error), RMSLE (root mean squared logarithmic error), and MAE
(mean absolute error), which are defined as the following:
+
Predicted AUC ratio Log Observed
AUC ratio
n
GMFE ¼ 10
vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
2
u u
t Predicted AUC ratio-Observed AUC ratio
RMSE ¼ +
n
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
ðLogðPredicted AUC ratioÞ-LogðObserved AUC ratioÞÞ2
RMSLE ¼ +
n
jPredicted AUC ratio-Observed AUC ratioj
MAE ¼ +
n
In each case, the scaling factor d was estimated per batch using all
perpetrator compounds except one to simulate real conditions (when
inducer potency of a new chemical entity is investigated). The AUC ratio
of the remaining perpetrator was then predicted using the optimal d. This
Fig. 1. Schematic presentation of the statistical investigations workflow when all inducers
(23 clinical trials in total, called method 3 in
Materials and Methods) are used, with methods
comparison.
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
Fold-induction was calculated for each concentration of test compound and for
each individual hepatocyte preparation. The maximal fold-induction (Emax) and
the concentration resulting in half-maximal induction (EC50) of CYP3A4 for
each compound were determined after fitting of the fold-induction values to a
sigmoidal curve, using biost@t-speed (internal software).
In Vitro–In Vivo Prediction of CYP Induction: Determination of the
d Value. The d parameter in eq. 1 represents an empirical calibration factor for
the purpose of in vitro–in vivo induction scaling. A unique value was determined
for each human hepatocyte batch and for each HepaRG experiment. This value
was determined through comparison of the predicted and observed exposure
ratio [AUCi/AUC, i.e., clinically observed ratio of area under the curve plasma
concentration/time of the relevant administered CYP3A4 probe substrate, in the
presence (AUCi) and absence of the inducer compound (AUC)] for different
CYP3A4 probe substrates such as midazolam, nifedipine, or simvastatin. This
equation only considers the potential induction effect of a compound on
CYP3A4 expressed in the liver. The plasma concentration, C max, of the
perpetrator (inducer compound) in the corresponding clinical trials was either
expressed as its unbound concentration, with Fup incorporated into the equation
or total concentration (without Fup in the equation). When unbound Cmax was
used, the in vitro EC50 was also corrected for the unbound fraction of test
compound in the hepatocyte assay (i.e., Fuhep), which was calculated using a
quantitative structure-activity relationship (QSAR) model as previously described elsewhere (Kilford et al., 2008). Fup and Fuhep values for each test
compound are reported in Table 4.
54
Vermet et al.
approach avoids an optimistic estimation of the error, as estimation of d and
prediction of the AUC ratio were not performed on the same set of data (see Fig. 1).
The predictions were classified as true positives or true negatives with
respect to the potential induction effect of the test compound if both the
predicted and observed AUC ratios were #0.8-fold (20% decrease in AUC)
or .0.8-fold, respectively. Predictions were classified as false positives or false
negatives with respect to the potential induction effect if the observed AUC ratios
were not predicted appropriately within the 0.8-fold cutoff criteria.
To compare the relative predictability of the different methods, the positive
predictive error (PPE) and the negative predictive error (NPE) values were
calculated using the following equations:
FP
100%
FP þ TP
FN
100%
NPE ¼
FN þ TN
PPE ¼
The PPE is defined as the proportion of in vitro studies that predicted a risk but
for which no clinical DDI was observed. The NPE is the proportion of studies
that were predicted as providing no risk of induction but actually demonstrated a
DDI risk. The lowest PPE, NPE, GMFE, and RMSE values obtained indicated
the best prediction outcomes.
Methods were compared through use of the predicted to observed AUC
ratios for the victim substrate probe by considering the number of predictions
within a 2-fold error (0.5 # predicted/observed AUC ratio # 2.0). Among the
methods employed to investigate the four minimization processes, only the best
one, based on quality criteria described earlier, was selected for this last comparison. Statistical investigations and method comparison are summarized in Fig. 1.
Results
Viability and Morphology of the Cultured Hepatocytes. Hepatocyte cultures were evaluated daily by phase-contrast microscopy, and
were considered to exhibit normal hepatocyte morphology for initiating
experiments when the confluence ranged between 80% and 100%.
Daily morphologic observations indicated that human hepatocytes
treated with vehicle (0.1% to 1% DMSO) exhibited normal hepatocyte
morphology. These observations, supported by the ATP content measurements performed on the last day of incubation (after 48 hours),
CYP3A4 mRNA Expression
Test Drug
CD-Hu4237
Carbamazepine
EC50 (mM)
Emax (FI)
Nifedipine
EC50 (mM)
Emax (FI)
Phenytoin
EC50 (mM)
Emax (FI)
SARA
EC50 (mM)
Emax (FI)
SARB
EC50 (mM)
Emax (FI)
Pioglitazone
EC50 (mM)
Emax (FI)
Rifampicin
EC50 (mM)
Emax (FI)
Rifapentine
EC50 (mM)
Emax (FI)
Phenobarbital
EC50 (mM)
Emax (FI)
Troglitazone
EC50 (mM)
Emax (FI)
Rosiglitazone
EC50 (mM)
Emax (FI)
SARC
EC50 (mM)
Emax (FI)
SARD
EC50 (mM)
Emax (FI)
Pleconaril
EC50 (mM)
Emax (FI)
Aprepitant
EC50 (mM)
Emax (FI)
BD-295
IVT-IBG
BD-281
CD-Hu8084
HH1024
Mean
S.D.
35
19
59
15
36
9.3
98
13
95
19
29
21
59
16
31
4.4
12
14
13
41
13
9.1
66
9.1
23
15
14
30
23
20
21
13
13
15
12
8.7
32
9.1
38
7.3
41
6.8
10
10
24
9.5
14
3.0
1.7
15
3.2
8.9
2.4
2.6
7.5
5.8
ND
ND
ND
ND
3.7
8.0
2.6
5.1
4.3
14
3.3
15
4.2
5.3
7.6
3.2
11
5.7
3.1
10
5.6
8.9
3.1
4.9
13
4.3
11
7.9
12
4.3
29
12
21
10
10
4.3
16
7.2
7.5
3.5
0.32
30
0.94
141
0.62
24
1.1
30
2.8
50
0.40
65
1.0
57
0.91
44
0.42
25
2.1
122
0.89
15
2.6
23
1.4
22
0.61
55
1.3
44
0.86
41
261
26
240
89
239
14
338
19
480
21
300
36
310
34
92
28
2.9
26
1.6
68
4.1
21
3.9
22
4.4
35
2.4
55
3.2
38
14
12
11
5.8
16
7.3
16
14
17
19
13
19
14
13
2.0
5.7
5.4
25
2.8
37
5.9
14
9.3
18
2.8
31
6.0
24
5.4
25
2.4
8.6
3.8
14
6.7
13
12
4.7
5.3
28
ND
ND
6.4
14
6.8
15
3.0
8.3
13
5.9
11
12
23
2.8
ND
ND
ND
ND
ND
ND
16
7.0
6.7
4.8
ND
ND
ND
ND
ND
ND
3.5
10
3.1
7.6
3.0
8.1
0.61
2.0
FI, fold induction; ND, not determined.
2.3
6.5
1.1
19
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
TABLE 5
Summary of in vitro induction parameters from test compound concentration/fold change in CYP3A4 mRNA curves
obtained with the six human cryopreserved hepatocyte batches
55
Normalization Methods To Predict CYP3A4 Induction
showed that most of the test compounds did not exhibit any cytotoxic
effects when used at concentrations up to 1000 mM. Cytotoxic concentrations of test drugs for each hepatocyte preparation and HepaRG
experiment are summarized in the Supplemental Data.
Stability of Compounds. The remaining concentration of each
parent test compound in culture medium was determined by LC-MS/MS
at various time points (0, 2, and 24 hours, in duplicate) during the second
day of incubation to check that cells were well exposed to test compound.
These analyses demonstrated that human hepatocytes and HepaRG cells
were well exposed to unchanged drug for the majority of the tested
compounds, at least at the highest noncytotoxic concentrations. For the
lowest concentrations of nifedipine, pioglitazone, rosiglitazone, troglitazone, SARA, and SARB (i.e., the worst case), hepatocytes were well
exposed after 2 hours of incubation while at least 80% of each respective
parent compound had been metabolized at the last 24-hour sampling time
point for at least one batch. Compounds concentrations and percentages
remaining at 24 hours are presented in the Supplemental Data.
Effect of Test Compound Treatment on the CYP3A4 mRNA
Expression in Human Hepatocytes and HepaRG Cells. The clinical
trials (n = 23) used in this analysis are referenced in Table 4. The 15
compounds were each tested in three to six different batches of
cryopreserved human hepatocytes and three thawings of HepaRG
cells, using CYP3A4 mRNA fold-induction as an end-point measurement. Dose–response data were fitted using a sigmoidal Emax model,
and EC50 and Emax values were determined (Tables 5 and 6, Fig. 3).
Representative dose–response curves, obtained with rifampicin in the
different human hepatocyte preparations and HepaRG cells, are
illustrated in Fig. 2. Only dose–response curves that fitted the following
acceptance criteria were used. The dose-response curve had at least six
data points. Though more than six concentrations were typically tested,
some dose–response curves were bell-shaped due to compound
cytotoxicity, solubility limitations, or other factors, and in these cases,
data points at higher concentrations were excluded for EC50 and Emax
calculations. A sigmoidal model fitted the dose-response data with less
CYP3A4 mRNA Expression
Test Drug
Carbamazepine
EC50 (mM)
Emax (FI)
Nifedipine
EC50 (mM)
Emax (FI)
Phenytoin
EC50 (mM)
Emax (FI)
SARA
EC50 (mM)
Emax (FI)
SARB
EC50 (mM)
Emax (FI)
Pioglitazone
EC50 (mM)
Emax (FI)
Rifampicin
EC50 (mM)
Emax (FI)
Rifapentine
EC50 (mM)
Emax (FI)
Phenobarbital
EC50 (mM)
Emax (FI)
Troglitazone
EC50 (mM)
Emax (FI)
Rosiglitazone
EC50 (mM)
Emax (FI)
SARC
EC50 (mM)
Emax (FI)
SARD
EC50 (mM)
Emax (FI)
Pleconaril
EC50 (mM)
Emax (FI)
Aprepitant
EC50 (mM)
Emax (FI)
FI, fold induction.
HepaRG
(Replicate 1)
HepaRG
(Replicate 2)
HepaRG
(Replicate 3)
Mean HepaRG
S.D. HepaRG
59
7.1
40
7.1
27
4.3
42
6.2
16
1.6
16
5.5
9.3
6.9
14
3.6
13
5.3
3.5
1.7
31
6.9
46
7.3
37
4.9
38
6.4
7.3
1.3
4.1
9.9
2.7
9.7
2.5
6.2
3.1
8.6
0.87
2.1
12
8.4
3.9
5.9
11
7.2
8.9
7.1
4.4
1.3
25
4.4
25
3.8
16
2.7
22
3.6
5.2
0.85
2.2
17
3.2
17
1.8
16
2.4
17
0.77
0.33
0.66
12
1.0
12
1.8
14
1.2
12
0.57
1.1
309
9.6
322
9.8
343
8.1
325
9.2
17
0.90
7.6
2.2
12
3.0
4.1
2.4
7.8
2.5
3.8
0.41
9.8
3.9
8.9
4.3
9.7
4.2
9.5
4.1
0.49
0.24
7.7
8.5
6.3
7.9
8.5
6.0
7.5
7.4
1.1
1.3
4.3
6.7
5.2
6.7
4.0
4.4
4.5
5.9
0.64
1.3
23
2.1
31
3.3
43
4.2
32
3.2
10
1.0
1.4
3.1
1.7
4.7
4.0
2.8
2.4
3.6
1.4
1.0
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
TABLE 6
Summary of in vitro induction parameters from test compound concentration/fold change in CYP3A4 mRNA curves
obtained with HepaRG cells (three experiments)
56
Vermet et al.
Fig. 2. Representative concentration–response
curves for rifampicin obtained with biost@t-speed
software. Shown are (A) six cryopreserved hepatocyte batches and (B) results for three independent thawing periods used for single batch of
HepaRG cells.
ranging from 2.5 6 0.41-fold for troglitazone to 17 6 0.33-fold for
rifampicin.
Determination of the d Value for the Human Hepatocyte
Batches. For each human hepatocyte batch, the scaling parameter d was
determined using the three approaches described in the Materials and
Methods section: 1) d value = 1; 2) d value determination based on
predicted and observed effects of rifampicin alone; and 3) d value
estimated through minimization of the distance between predicted and
observed AUC ratios for the set of 15 well-known inducers with four
retained distances (GMFE, RMSE, RMSLE, and MAE). The three
methods were evaluated using different values for the hepatic inducer
plasma concentration: unbound (with Fup) or total (without Fup) Cmax.
To compare the relative predictability of the different methods, GMFE
and RMSE were calculated as quality prediction criteria. Considering
the overall total six batches, predicted versus observed AUC ratios, in
Fig. 3. In vitro induction parameters EC50 (A, B) and Emax (C, D) obtained with six human cryopreserved hepatocyte batches (left) and HepaRG cells (three independent
thawing periods) (right), derived from the test compound concentration–fold change in CYP3A4 mRNA curves.
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
than 20% EC50 coefficient of variation. The responses of the human
hepatocytes and HepaRG cells in the presence of the positive control
(i.e., rifampicin) were within the normal ranges reported in the literature:
CYP3A4 gene expression was potently increased, with mean Emax at
57-fold 6 44 and 17-fold 6 0.33, and mean EC50 at 1.0 6 0.91 mM and
2.4 6 0.77 mM, respectively.
The 15 tested compounds (references and proprietary sanofi
compounds) induced CYP3A4 gene expression in all the human
hepatocyte donors, with mean EC50 values ranging from 1.0 6
0.91 mM for rifampicin to 310 6 92 mM for phenobarbital, and mean
Emax values ranging from 7.0 6 4.8-fold for pleconaril to 57 6 44-fold
for rifampicin.
The tested compounds also induced CYP3A4 gene expression in
HepaRG cells, with mean EC50 values ranging from 1.2 6 0.57 mM for
rifapentine to 325 6 17 mM for phenobarbital, and mean Emax values
Normalization Methods To Predict CYP3A4 Induction
each test condition, are presented in Fig. 4. As shown in Table 7, similar
results were obtained with all four methods of minimization, GMFE,
RMSE, RMSLE, or MAE. Therefore, only GMFE was selected for
57
comparison with the other methods in Fig. 4. As shown in this figure
and in Table 7, the NPE percentage is 20%–100% higher, whatever the
method evaluated, when unbound concentrations (EC50 and Cmax) are
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
Fig. 4. Comparison of predicted and observed AUC ratios for each batch of human hepatocyte cultures and each independent thawing period of the HepaRG batch. Predicted AUC
ratios are calculated using three different methods: (A) d equal unity, (B) d determined with rifampicin alone as calibrator, and (C) d factor obtained through GMFE error function for
human hepatocytes in primary culture (left) or HepaRG cell line (right). The dotted lines represent the 2-fold error (i.e., 2-fold boundary), and the solid line represents the line of unity.
58
Vermet et al.
TABLE 7
Summary of the DDI predictions of tested approaches for induction-based DDI of 129 predicted AUC ratios
Six cryopreserved human hepatocyte batches, 20 to 22 trials per batch. One trial is one observed AUC ratio compared with the corresponding predicted value. See Materials and Methods for
calculation of PPE, NPE, RMSE, and GMFE.
Inducer Plasma Cmax
Concentration
Total
Unbound
Approaches
Percentage of Trials Included
in the 2-Fold Error
FN (n)a
FP (n)a
TN (n)a
TP (n)a
NPE (%)
59
46
1
20
2
106
33
96
74
5
12
10
102
96
93
96
97
74
72
74
75
5
6
6
7
12
13
12
12
10
9
10
10
92
71
22
2
83
64
38
100
89
98
92
78
69
76
71
22
18
24
19
RMSEb
GMFEa
16
0.31
2.5
33
11
0.23
1.6
102
101
101
100
33
40
38
41
11
11
11
11
0.23
0.24
0.23
0.24
1.7
1.8
1.7
1.7
20
85
52
2.3
0.25
1.8
1
21
69
64
1.4
0.32
1.9
2
4
1
4
20
18
21
18
85
89
83
88
52
50
53
51
2.3
4.3
1.2
4.3
0.24
0.24
0.26
0.24
1.6
2.0
1.7
1.9
PPE (%)
d, induction scalar; 2-fold envelope, number of trials included in the 2-error, as also presented in Figure 4; GMFE, geometric mean fold error; inducer concentration, total or unbound plasma
concentration in clinic (Cmax), and in vitro (incubated inducer concentration); MAE, mean absolute error; NPE, negative predictive error; PPE, positive predictive error; RMSLE, root mean squared
logarithmic error; RMSE, root mean square error; trial, one trial is one observed AUC ratio compared with the corresponding predicted value.
a
Total number of clinical trials that were predicted as false negative (FN), false positive (FP), true negative (TN), or true positive (TP) with respect to induction based on the 0.8-fold cutoff criterion.
b
RMSE and GMFE used as quality criteria.
c
GMFE, RMSE, RMSLE, MAE retained distances used for d calculation through a minimization process as described in Material and Methods.
incorporated, but it has a tendency to lead to higher values of PPE
(Table 7). Allocating the scaling parameter d to a value of 1 provides the
lowest accuracy in comparison with using a calculated scaling value
[GMFE = 2.5, 46% within 2-fold (Table 7)]. Moreover, there was a
trend for more-biased predictions toward overprediction of induction
when d = 1, with the higher PPE value (16%) (Table 7 and Fig. 4).
Hence, the determination of a d factor calculated for each hepatocyte
batch is the method of choice.
The method using the full set of 15 compounds to calculate d values
did not increase the quality criteria compared with the method using
rifampicin alone. As shown in Table 7, the quality criteria RMSE, GMFE,
NPE and PPE were similar, with both methods reflecting no improvement in the prediction when the set of compounds are used, when total
Cmax is considered. In addition, comparison of both methods indicates
that the d values are equivalent for a given tested human hepatocyte batch,
despite having clearly different d values (range: 0.10–0.56) in the two
TABLE 8
Summary of the DDI predictions of tested approaches for induction-based DDI of 69 predicted AUC ratios
Three experiments with one batch of HepaRG cell line, 23 trials per experiment. One trial is one observed AUC ratio compared with the corresponding predicted value. See Materials and Methods
for calculation of PPE, NPE, RMSE, and GMFE.
Inducer Plasma Cmax
Concentration
Total
Unbound
Approaches
1
d=1
2
dRif
3
GMFEc
RMSEc
RMSLEc
MAEc
1
d=1
2
dRif
3
GMFEc
RMSEc
RMSLEc
MAEc
n Trials Included
in the 2-Fold Error
Percentage of Trials Included
in the 2-Fold Error
FN (n)a
FP (n)a
TN (n)a
TP (n)a
NPE (%)
53
77
0
10
2
57
0
54
78
0
10
2
57
53
55
52
53
77
80
75
77
0
2
0
0
10
8
9
10
2
4
3
2
44
64
21
3
46
67
21
50
44
49
26
73
64
71
38
18
14
18
16
RMSEb
GMFEb
15
0.23
1.6
0
15
0.23
1.6
57
55
57
57
0
33
0
0
15
13
14
15
0.24
0.24
0.24
0.24
1.6
1.7
1.6
1.6
9
36
70
7.7
0.33
1.9
3
9
36
70
7.7
0.33
1.9
3
3
3
3
9
9
9
9
39
43
39
41
67
61
67
64
7.1
6.5
7.1
6.8
0.29
0.31
0.30
0.32
1.7
2.2
1.7
2.7
PPE (%)
d, induction scalar; 2-fold envelope, number of trials included in the 2-fold error, as also presented in Figure 4; GMFE, geometric mean fold error; inducer concentration, total or unbound plasma
concentration in clinic (Cmax) and in vitro (incubated inducer concentration); NPE, negative predictive error; PPE, positive predictive error; RMSE, root mean square error, RMSLE, root mean squared
logarithmic error; MAE, mean absolute error.
a
Total number of clinical trials that were predicted as false negative (FN), false positive (FP), true negative (TN), or true positive (TP) with respect to induction based on the 0.8-fold cutoff criterion.
b
RMSE and GMFE used as quality criteria.
c
GMFE, RMSE, RMSLE, and MAE retained distances used for d calculation through a minimization process as described in Material and Methods.
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
1
d=1
2
dRif
3
GMFEc
RMSEc
RMSLEc
MAEc
1
d=1
2
dRif
3
GMFEc
RMSEc
RMSLEc
MAEc
n Trials Included
in the 2-Fold Error
59
Normalization Methods To Predict CYP3A4 Induction
TABLE 9
Values for d determined by two methods and total Cmax inducer concentrations: 1)
d factor obtained through GMFE error function and 2) d determined with rifampicin
alone as calibrator for six human hepatocyte preparations in primary culture
The d factor value calculated with GMFE method is the average of the d values determined for
each batch (see Materials and Methods and Figure 1 for details).
Method
HH1024
CD-Hu8084
BD-281
IVT-IBG
BD-295
CD-Hu4237
d GMFE
d Rifampicin
0.23
0.20
0.32
0.32
0.46
0.46
0.56
0.56
0.11
0.10
0.40
0.43
Discussion
In the current study, six different batches of human cryopreserved
hepatocytes and one batch of HepaRG cells, analyzed after three independent thawing periods, were treated with 15 compounds at concentrations ranging from 0.01 to 3000 mM. For each investigated batch, an
empirical calibration factor for the purpose of in vitro–in vivo scaling,
called the d factor, was determined (eq. 1). Gene expression, as a measure
of the in vitro induction potential of these compounds, was evaluated at
concentrations up to their respective maximal noncytotoxic concentration.
The metabolic stability of the test compounds in human hepatocytes and
HepaRG cells was also investigated, as recommended by regulatory
guidelines.
TABLE 10
Values for d determined by two methods and total Cmax inducer concentrations: 1)
d factor obtained through GMFE error function and 2) d determined with rifampicin
alone as calibrator for three experiments with the HepaRG cell line
The d factor value calculated with GMFE method is the average of the d values determined for
each experiment (see Materials and Methods and Figure 1 for details).
Method
HepaRG
Replicate 1
HepaRG
Replicate 2
HepaRG
Replicate 3
d GMFE
d Rifampicin
1.1
0.93
1.1
0.99
0.96
0.92
Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
methods for each hepatocyte batch reflecting the interbatch variability
response (Table 9).
Determination of the d Value for the HepaRG Cell Line. For
each thawing of one batch of HepaRG cell line, the scaling parameter
(i.e., d) was determined using the three approaches outlined earlier with
the inducer plasma Cmax concentration expressed as either unbound
(with F up ) or total (without F up ). As described earlier for human
hepatocyte preparations, the relative predictability of each approach
was compared by calculating the GMFE, RMSE, NPE, and PPE as
quality prediction criteria.
Taking the three experiments together, the predicted versus observed
AUC ratios in each condition are presented in Fig. 4. Similarly to the
human hepatocyte preparations, the use of the d factor calculated
without Fup was the best method to avoid underestimation, and similar
results were obtained with all methods of minimization, GMFE, RMSE,
RMSLE, or MAE (Table 8). Therefore, only GMFE was selected for
comparison with the other methods in Fig. 4. As shown in this figure
and in Table 8, the NPE percentage is 0 in most of cases, when total
Cmax concentrations are incorporated, whatever the test method applied.
As observed with the human hepatocyte preparations, the third
approach, which used the set of 15 compounds to calculate the d values,
did not increase the quality criteria (RMSE, GMFE, PPE, and NPE)
compared with the second approach that used rifampicin alone.
Allocation of the scaling parameter d to a value of 1 provides the same
level of accuracy as that observed for a calculated scaling value [GMFE =
1.6, 77% within 2-fold (Table 8)]. Moreover, using the d value
determination based on the predicted and observed effects of rifampicin
alone and incorporating its total Cmax inducer concentration, the
d values were close to 1 [range: 0.92 to 0.99 (Table 10)], indicating
that calculation of a d value is unnecessary when a test compound is
incubated with HepaRG cells.
To summarize the results obtained with the HepaRG cell line (Fig. 4),
the preferred approach for both optimal prediction of potential induction and ease of use is the first method incorporating a d factor value
equal to 1 (i.e., no d factor) and total Cmax compound concentration
(without Fu).
Quantification of test compounds by LC-MS/MS during day 2, the
final day of incubation, demonstrated that human hepatocytes and
HepaRG cells were well exposed to unchanged compound at least for
the highest concentrations. However, 6 of 15 compounds exhibited a
non-negligible metabolism after 24 hours incubation at the lowest concentrations for at least one batch. This suggests the effective concentration for induction process was less than those considered to derive
EC50 and Emax. There is no obvious way to address this problem because induction mechanism and metabolic depletion of parent compound occur simultaneously. To address this potential issue, some
authors have proposed considering the time weighted average concentration but have showed no improvement regarding quality criteria
(Zhang et al., 2014).
The Emax values determined in vitro were found to be highly variable
from one batch of human hepatocytes to another, and limited interexperimental variability was demonstrated for the HepaRG cells (n = 3) with
both rifampicin alone (Fig. 2) and for all test compounds (Fig. 3). This
variability in Emax values between different donors reflects the different
magnitude of response in the donors and justifies the use of the d factor.
Variability in hepatocyte plating efficiency and cell-viability during the 2day duration of the experiment may also contribute to this observed
variability. Typically, there was relatively little interindividual variability
in the EC50 values in our study (Fig. 3). Of note, comparison of EC50
values for human hepatocytes and HepaRG show that the EC50 is similar
for all of the test inducers (Fig. 3, Table 5, 6).
For each human hepatocyte batch and HepaRG cell line, the scaling
parameter d was determined using the three approaches described in the
Materials and Methods section using the unbound or total hepatic
inducer plasma concentration.
For human hepatocyte batches, the use of in vitro and in vivo unbound
concentrations tended to increase false negatives, even though in terms of
2-fold error the methods considering unbound concentration were slightly
more accurate (Table 7). However, the use of the d factor calculated without
Fup (i.e., Cmax total used) was the best method to avoid underestimation of
clinical outcome (the lowest NPE percentage) (Table 7). This statement
was specifically true with HepaRG in vitro model, which also showed a
better accuracy in terms of 2-fold error (Table 8).
Despite these findings showing that unbound input concentrations
(both in vitro and in vivo) yielded more accurate predictions of clinical
induction magnitude, we currently recommend using the total concentration values when predicting positive/negative outcomes in clinical
induction studies as this will not yield false negatives. This is consistent
with the previous claims of others (Einolf et al. 2014). However it must be
acknowledged that our dataset had only four clinical noninducers; thus, to
thoroughly test free versus total concentrations as the relevant input
values for prediction, a larger dataset that is enriched with drugs that show
an induction response in vitro but not in vivo, as well as being highly
protein bound (e.g., fup , 0.1), would be needed.
For experiments with human hepatocyte batches, comparison of the
three methods (i.e., d equal to unity, d determined with rifampicin
alone, and d determined with the set of compounds) showed that
60
Vermet et al.
Acknowledgments
The authors thank Dr. Magalie Pardon, Sophie Vivier, Dr. François Donat,
Dr. Terence Appelqvist, Dr. Roger Botham, and Dr. Jean-Marie Martinez for
reviewing the manuscript and for their helpful suggestions.
Authorship Contributions
Participated in research design: Vermet, Klieber, Fabre, Boulenc.
Conducted experiments: Vermet, Raoust, Ngo.
Contributed new reagents or analytic tools: Vermet, Ngo.
Performed data analysis: Vermet, Esserméant, Boulenc.
Wrote or contributed to the writing of the manuscript: Vermet, Esserméant,
Klieber, Fabre, Boulenc.
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Downloaded from dmd.aspetjournals.org at ASPET Journals on May 15, 2017
incorporation of the d factor provided the best prediction. Omitting the
calibration factor led to a clear overestimation of the clinical effects of
the test inducer. Moreover, our data provided no strong rational to
suggest that a more accurate prediction was obtained when the set of
15 known test inducers were evaluated. Indeed, the d factor determined
with rifampicin alone appeared to be sufficiently robust because it
provided similar predictive accuracy to that obtained with the full set of
test compounds (see Table 7 and Fig. 4).
In conclusion, the current investigation with the human hepatocyte in
vitro model has demonstrated that the optimal determination of the
calibration factor d, in terms of both the predictive accuracy of clinical
outcome and level of resources required, is the method using the known
CYP3A4 inducer rifampicin alone. Because rifampicin is classically
used as a prototypical positive control inducer in each in vitro experiment, this option provides a method to incorporate the d calibrator
in each experiment to reduce the impact of interexperimental variability
for any human hepatocyte batch. In addition, rifampicin is metabolically stable in vitro (Supplemental Data) and thereby provides robust
EC50 and Emax determination.
The HepaRG cell line has been previously proposed as an in vitro
model to investigate induction processes (Grime et al., 2010). In our
experiments with this cell line, using the set of 15 known inducers
resulted in in vitro Emax values that tended to be lower than those
obtained when human hepatocyte batches were used as the in vitro
model (Fig. 3). Because HepaRG cell line exhibits a higher basal
activity of CYP3A4 compared with the various cryopreserved human
hepatocyte batches (Table 2, 3), the lower Emax values obtained in the
HepaRG cell line may be partly explained by a lower induction
potential. In view of the low Emax values (Fig. 3 and Table 8), the
calibration factor did not appear to improve the accuracy of the
prediction obtained with HepaRG cells in contrast to the results
obtained with the batches of human hepatocytes.
As previously stated in the literature, since similar predictive
accuracy has been obtained with HepaRG cell line and human
hepatocytes, data from both in vitro models can be used interchangeably within the same laboratory to predict in vivo clinical
outcome for CYP3A4 induction (McGinnity et al., 2009). In terms of
the accuracy in prediction of clinical outcome as shown by 2-fold
error (%), our data also suggest comparable reliability of the two
models (Tables 7 and 8).
To sum up, our findings show that application of the calibration
factor d to in vitro values obtained from experiments to evaluate
potential inducers in human hepatocytes is preferable for prediction of
clinical outcome. However they also suggest that the calculation of
this factor d does not require the use of a complete set of 15 known
CYP3A4 inducers. The use of rifampicin alone, which is already
systematically incorporated as a prototypical positive CYP3A4 control in each in vitro experiment, should be sufficient to predict clinical
outcome. When the HepaRG established cell line is used as the in vitro
model, the findings obtained in three experiments, using a single batch
of cells, show a good prediction accuracy with or without d factor.
However, this finding is derived from values obtained with one single
batch of HepaRG cells (three independent thawing periods). Additional
studies using different batches of HepaRG cells will be required to
provide definitive data that could confirm these results.