Accepted Article

Article Type: Clinical Trial

Assessment of Multi-Ion Channel Block in a Phase-1 Randomized Study Design:
Results of the CiPA Phase 1 ECG Biomarker Validation Study

Jose Vicente1, Robbert Zusterzeel2, Lars Johannesen1, Roberto Ochoa-Jimenez2, Jay W Mason3,4,
Carlos Sanabria4, Sarah Kemp4, Philip T. Sager5, Vikram Patel2, Murali K Matta2, Jiang Liu2, Jeffry
Florian1, Christine Garnett1, Norman Stockbridge1, David G Strauss2

1

Office of New Drugs, Center for Drug Evaluation and Research, United States Food and Drug Administration,

Silver Spring, MD, USA
2

Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research,

United States Food and Drug Administration, Silver Spring, MD, USA
3

Department of Medicine, Division of Cardiology, University of Utah, Salt Lake City, UT

4Spaulding Clinical Research, West Bend, WI, USA

5

Stanford University, Palo Alto, CA, USA

Disclaimer
This article reflects the views of the authors and should not be construed to represent FDA’s views or policies.
The mention of commercial products, their sources, or their use in connection with material reported herein is
not to be construed as either an actual or implied endorsement of such products by the FDA.

Conflicts of Interest
PT Sager has consulting agreements with Biomedical Systems, Charles River, and iCardiac. The other authors
report no conflicts of interest.

Funding
This study was internally funded by the FDA/CDER Safety Research Interest Group

This article has been accepted for publication and undergone full peer review but has notbeen through the copyediting, typesetting, pagination and proofreading process, which maylead to differences between this version and the Version of Record. Please cite this article as
doi: 10.1002/cpt.1303
This article is protected by copyright. All rights reserved.

Corresponding authors:

Accepted Article

Jose Vicente, PhD
U.S. Food and Drug Administration
10903 New Hampshire Avenue,
WO22-4167 Silver Spring, MD, 20993, USA
E-mail: jose.vicenteruiz@fda.hhs.gov
Telephone: 301-796-8442
Fax: 301-796-9838

David G. Strauss, MD, PhD
U.S. Food and Drug Administration
10903 New Hampshire Avenue,
WO64-2072 Silver Spring, MD, 20993, USA
E-mail: david.strauss@fda.hhs.gov
Telephone: 301-796-6323
Fax: 301-796-9927

Key words: drug-induced QT prolongation, torsade de pointes, multichannel block

Abstract
Balanced multi-ion channel-blocking drugs have low torsade risk because they block inward currents.
The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative proposes to use an in-silico
cardiomyocyte model to determine the presence of balanced block, and absence of J-Tpeakc
prolongation would be expected for balanced blockers. This study included 3 balanced blockers in a
10-subject per drug parallel-design; lopinavir/ritonavir and verapamil met the primary endpoint of
ΔΔJ-Tpeakc upper bound <10 ms, while ranolazine did not (upper bounds of 8.8, 6.1, and 12.0 ms,
respectively). A predominant hERG blocker (chloroquine) prolonged ΔΔQTc and ΔΔJ-Tpeakc by ≥10
ms. In a separate crossover design, diltiazem (calcium block) did not shorten dofetilide-induced ΔQTc
prolongation, but shortened ΔJ-Tpeakc and prolonged ΔTpeak-Tend. Absence of J-Tpeakc
prolongation appears consistent with balanced block, however, small sample size (10 subjects) may
be insufficient to characterize concentration-response in some cases.

Introduction
Current regulatory guidelines from the International Council on Harmonisation (ICH) describe nonclinical (ICH S7B1) and clinical strategies (ICH E142) to assess the potential of a drug to prolong
cardiac repolarization as well as its clinical proarrhythmic potential. No drugs with unexpected QT
prolongation or torsade de pointes (torsade) risk have reached the market after the adoption of ICH
S7B and E14 guidelines. However, there are drugs that block the potassium channel encoded by thehuman ether-à-go-go related gene (hERG) and prolong the heart rate corrected QT (QTc) interval but
have low torsade risk (e.g., ranolazine, verapamil, amiodarone) because they block other inward
currents (i.e., late sodium and/or L-type calcium currents). Block of these inward currents isantiarrhythmic by preventing early afterdepolarizations.3-9 ICH S7B and E14 discuss the importanceof the drug’s effects on other ion channels in addition to hERG and encourage interested parties todevelop models for directly assessing drug-induced proarrhythmia of QTc prolonging drugs.1, 2 In linewith this, the goal of the Comprehensive in vitro Proarrhythmia Assay (CiPA) is to perform amechanistic assessment of a drug’s torsade risk.10

Under CiPA, the torsade risk of a drug will be determined by an in silico model that integrates the
drug’s effects on multiple ion channel currents of the human ventricular myocyte. CiPA’s in silico
model outputs a Torsade Metric Score called qNet,11 which reflects the balance of inward andThis article is protected by copyright. All rights reserved.

Accepted Article

outward currents throughout the action potential. Multichannel blocking drugs, that is, drugs thatblock hERG as well as late sodium and/or L-type calcium currents, will be considered balanced ionchannel blockers (referred to as “balanced blockers”) if qNet predicts the drug to be low risk, and“predominant hERG blockers” otherwise (i.e., drugs that only block hERG or multichannel blockers
predicted to be intermediate or high risk). For a balanced blocker, the CiPA initiative proposes to use
electrocardiogram (ECG) analysis in early phase 1 clinical trials to determine if there is evidence of
unexpected ion channel effects in humans compared to the preclinical data.12 As described in areview of the CiPA initiative that included the rationale and design of this clinical study,13 prior work
identified that the heart rate corrected J-Tpeak (J-Tpeakc) interval could be used to differentiate
predominant hERG blockers from balanced blockers. Specifically, predominant hERG blockers
prolong QTc and J-Tpeakc, while balanced blockers prolong QTc with no J-Tpeakc prolongation.14-18
This study was designed in 2 parts with separate objectives.13 The primary objective of part 1 was toassess whether balanced ion channel-blocking drugs (ranolazine, verapamil and lopinavir/ritonavir)
do not cause J-Tpeakc prolongation in a small sample size (10 subjects per drug and placebo) phase1 type parallel study design. One predominant hERG-blocking drug (chloroquine) was included as acontrol. Balanced block was determined based on ion channel data available during study design,13,
19
and not based on qNet. Thus, drug categories may be different if based on data acquired withcurrent CiPA protocols20 and qNet. Prolongation of J-Tpeakc and QTc was defined using a
concentration-response model as an upper bound of the predicted effect at maximum drug plasma
concentration ≥10 ms. The primary objective of part 2 (crossover study) was to test the hypothesisthat diltiazem (calcium channel block) can reduce the QTc prolongation by dofetilide (predominanthERG block) by shortening J-Tpeakc. Sample size and J-Tpeakc threshold were determined based on
analyses from prior clinical studies.14, 15, 17, 18 and by resampling the data using similar methodology of
Ferber et al.21(see online supplement in Vicente et al.13 for details).

Results
Sixty healthy subjects (22 women) with a mean ± SD age of 31.7 ± 8.7 years and body mass index of
25.8 ± 2.7 kg/m2 were randomized with 50 subjects assigned to part 1 (parallel study) and 10
subjects assigned to part 2 (crossover study). No serious or unexpected treatment-related adverse
events were observed. Two subjects were discontinued after receiving the second dose of diltiazemin part 2 and one subject withdrew consent prior to the second day of treatment in part 1. All othersubjects completed the study. The online supplement includes full baseline characteristics, adverse
events frequencies by treatment, CONSORT flow diagram as well as detailed results for multiple ECG
biomarkers as described in the statistical analysis plan.13 The clinical data and raw annotated ECG
waveforms are publicly available at PhysioNet's22 website(https://physionet.org/physiobank/database/ecgcipa/).

This article is protected by copyright. All rights reserved.

Part 1: parallel study

Accepted Article

Administered drugs, their dosing times and their pharmacokinetic (PK) time profiles are shown in
Figure 1. The observed geometric mean maximum drug plasma concentrations (Cmax) after firstdose on days 1 and 3 are shown in Table 1. As planned, subjects were exposed to a lower drugconcentration on Day 1 and a higher drug concentration on Day 3.
Figure 2 shows time profiles of placebo corrected changes from baseline (ΔΔ) for ΔΔQTc and ΔΔJTpeakc for each treatment and time-point (see online supplement for ΔΔTpeak-Tend plots). Table 1
shows predictions for all ECG biomarkers at low and high concentrations on days 1 and 3,
respectively, from concentration-response models with proper fit (i.e., linear relationship supported
by observed data). Goodness of fit concentration-response plots are shown in Figure 3 and online
supplement.

Ranolazine, lopinavir/ritonavir and verapamil
The pre-specified primary endpoint for the balanced ion channel-blocking drugs was that they would
not prolong J-Tpeakc defined by an upper bound of the two-sided 90% confidence interval of ΔΔJTpeakc < 10 ms at Cmax on day 3. While not included in the primary endpoint, QTc prolongation(i.e., upper bound of ΔΔQTc ≥ 10 ms at Cmax on day 3) was also expected because these drugs are
known to block hERG.
The three balanced blockers had flat or negative mean ΔΔJ-Tpeakc slope and mean ΔΔJ-Tpeakc
effects < 5 ms (Figure 3). The prespecified criterion was met with verapamil (mean [90% confidence
interval] of -2.6 [-11.4 to 6.1] ms) and lopinavir/ritonavir (−2.9 [-14.6 to 8.8] ms), however thecriterion was not met for ranolazine (1.2 [-9.5 to 12.0] ms).
Ranolazine prolonged QTc by 14.1 [7.5 to 20.8] ms on day 1 and 28.2 [18.3 to 38.2] ms on day 3,
while verapamil prolonged QTc by 8.6 [4.4 to 12.9] ms on day 1 and 13.9 [10.0 to 17.8] ms on day 3(Figure 3 and Table 1). Lopinavir/ritonavir prolonged QTc by >20 ms on day 3, but exhibited nonlinear concentration-dependent QTc prolongation.

Chloroquine
Chloroquine was included as a non-balanced (predominant hERG) blocker drug. The pre-specified
primary endpoint was that it would prolong ΔΔQTc defined by an upper bound of the two-sided 90%
confidence interval of ΔΔQTc ≥ 10 ms at Cmax on day 1. While not included in the primary endpoint,
chloroquine was expected to prolong ΔΔJ-Tpeakc.
Chloroquine met the prespecified criterion prolonging ΔΔQTc by 30.7 [22.6 to 38.9] ms at Cmax on
day 1 (Figure 3). ΔΔJ-Tpeakc was prolonged as defined by it being ≥ 10 ms throughout theconcentration range in the study (Figure 3), however the goodness of fit plot showed a poor fit of
the concentration-J-Tpeakc linear model with a large positive intercept (8.6 ms) and flat slope.

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Part 2: crossover part - Dofetilide vs. dofetilide + diltiazem

Accepted Article

The hypothesis for this part of the study was that diltiazem (L-type calcium channel block) canshorten the QTc prolongation caused by dofetilide (predominant hERG block) by shortening the JTpeakc interval. This was assessed in a crossover study design by subjects receiving dofetilide alone
in one period, while in a second period having subjects receive diltiazem alone on days 1 and 2 andthen diltiazem combined with dofetilide on day 3. Dosing schedule and pharmacokinetic results areshown in Figure 4. Diltiazem observed Cmax on day 3 was 385.2 ng/mL. Dofetilide Cmax
concentrations on day 3 were 1.5 and 1.2 ng/mL for dofetilide alone and diltiazem + dofetilide
treatment periods, respectively. When dofetilide was administered alone (Figure 5), it prolonged
ΔQTc by prolonging both ΔJ-Tpeakc and ΔTpeak-Tend. When diltiazem was co-administered with
dofetilide, diltiazem did not shorten ΔQTc (Figure 5.A and Figure 5.D), thus not meeting the primary
endpoint. In the subsequent exploratory analysis, diltiazem shortened ΔJ-Tpeakc by 11.5 [2.2 to20.7] ms (Figure 5.B and Figure 5.E) and increased ΔTpeak-Tend by 16.3 [4.8 to 27.7] ms (Figure 5.C
and Figure 5.F).

PR and QRS effects for all study drugs
Chloroquine, verapamil, lopinavir/ritonavir and diltiazem prolonged ΔΔPR in a concentrationdependent fashion (Table 1). Goodness of fit plots supported a linear concentration-ΔΔPR
relationship for chloroquine, which caused 14.8 [4.7 to 24.9] ms prolongation at Cmax on day 3.
With verapamil, lopinavir/ritonavir and diltiazem, concentration-dependent ΔΔPR prolongation was
linear at lower concentrations, but goodness of fit plots (see online supplement) suggested that it
plateaued around 30 ms, which was the effect seen at Cmax on day 3. Ranolazine and dofetilide did
not prolong PR.
Chloroquine prolonged QRS in a concentration dependent fashion, with ΔΔQRS of 9.9 [6.1 to 13.6]
ms at Cmax on day 3 (Table 1). No QRS prolongation was observed with other drugs.

Discussion
Drug-induced torsade develops when there is an imbalance of inward and outward repolarization
currents that triggers early afterdepolarizations. The CiPA initiative proposes to assess the effects ofdrugs on multiple ion channel currents (e.g., hERG, L-type calcium and late sodium) and integratethem in a mechanistic, in silico model of the human ventricular cardiomyocyte to predict torsade
risk. The torsade risk metric (qNet) from the in silico model reflects the balance of inward andoutward currents (i.e., how close a drug is to generating an early afterdepolarization, the trigger for
torsade).11 CiPA proposes to assess ECG data from early phase 1 clinical studies to determine if there
are unexpected ion channel effects in humans compared to the results from the in vitro assays that
inform the in silico model. For a balanced ion channel blocking drug (i.e., multichannel blocker thathas a low torsade risk qNet), a lack of QTc prolongation would confirm that there are no unexpected
ion channel effects. Moreover, if the balanced blocker causes QTc prolongation, a lack of J-Tpeakc
prolongation could confirm presence of balanced ion channel effects. Thus, presence of J-Tpeakc
prolongation would not be expected for balanced blockers.

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Part 1

Accepted Article

Drug categories were assigned based on ion channel data available during study design, and not on
the qNet score from the in silico model.13, 19 The prespecified criterion to test the hypothesis for thebalanced ion channel drugs in this study was that the upper bound of the two-sided 90% confidence
interval of the predicted ΔΔJ-Tpeakc using a concentration-response model would be <10 ms at
Cmax on day 3. All three balanced ion channel drugs had flat or negative concentration-response
relationships for ΔΔJ-Tpeakc and the primary endpoint was met for verapamil (upper bound 6.1 ms)
and for lopinavir/ritonavir (8.8 ms); however, it was missed for ranolazine (12.0 ms). Of note, withranolazine this occurred when the QTc was prolonged by ~30 ms, whereas on day 1 the mean ΔΔQTc
was ~14 ms and ΔΔJ-Tpeakc upper bound was <10 ms (2.2 [-4.3 to 8.7] ms). One predominant hERGblocking drug (chloroquine) that is associated with torsade23, 24 was included in the parallel part ofthe study as control. As hypothesized, chloroquine prolonged ΔΔQTc in a concentration-dependent
fashion, meeting the primary endpoint with ΔΔQTc upper bound at Cmax on day 1 ≥ 10 ms.
Chloroquine also prolonged ΔΔJ-Tpeakc throughout the 3 days of the study as defined by an upperbound ≥10 ms, but the prolongation was not linearly related to concentration.

Concentration-Response Model Observations and Limitations
In the parallel (Part 1) of the study, concentration-response models for the primary endpoints hadflat or negative J-Tpeakc slopes for ranolazine, verapamil and lopinavir/ritonavir, and a positive QTcslope for chloroquine, as expected. For the non-primary endpoints, it was observed that thelopinavir-ΔΔQTc relationship was non-linear and the chloroquine-ΔΔJ-Tpeakc model had a positive
intercept with a flat slope (Figure 3). With lopinavir, lower concentrations showed no QTc changes
followed by a sharp increase of ~20 ms in mean ΔΔQTc at the higher concentrations on Day 3. This
non-linear pattern was also present for ΔΔTpeak-Tend (online supplement), and both are consistent
with the time profile (Figure 2).
The positive intercept with a flat slope for the chloroquine-ΔΔJ-Tpeakc linear model may have been
due to not having enough data to characterize ΔΔJ-Tpeakc response at low chloroquine
concentrations (Figure 3). Positive intercepts have been reported before with small sample sizes (seeTable 3 in Darpo et al.25), and were observed in some other concentration-ECG relationships in thisstudy (e.g., ranolazine-QTc, online supplement). In addition, multi-ion channel effects may play amore substantial role at higher chloroquine concentrations leading to a plateau of ΔΔJ-Tpeakc
prolongation. This hypothesis is supported by PR and QRS prolongation caused by chloroquine in thisstudy (Table 1 and online supplement), which is consistent with prior observations.26, 27 In addition,
chloroquine is known to accumulate in heart tissue, so the tissue concentration may have been
substantially higher than the plasma concentration (e.g., up to ~150 fold),28 leading to additional ion
channel block. Lastly, QRS prolongation may be also explained by block of the inward rectifierpotassium current (IK1) by chloroquine.19, 29, 30 Overall, the ECG findings for chloroquine may warrant
further investigation.
Lastly, the variability of ΔΔJ-Tpeakc measures observed at high ranolazine concentrations was dueto heart-rate increase in two timepoints in two subjects. The observed variability could have been an
artifact due to the use of previously developed population based heart-rate correction.14

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Part 2

Accepted Article

A prior study demonstrated that lidocaine and mexiletine (late sodium current blockers) shorten QTc
prolongation by dofetilide by shortening J-Tpeakc.17 We hypothesized that diltiazem (L-type calcium
channel blocker) would exert a similar effect. Diltiazem did not affect the slope of the dofetilideconcentration-ΔQTc relationship (28.4 [21.9 to 34.9] ms per ng/mL with diltiazem and 29.2 [22.3 to36.0] ms per ng/mL without), which were similar to those reported in our two prior studies (30.2[26.9 to 33.5] ms per ng/mL and 27.9 [24.9 to 30.9] ms per ng/mL).15, 17 The reason for the lack of
QTc shortening with diltiazem is not clear. Multiple nonclinical studies clearly demonstrate that Ltype calcium channel block shortens action potential duration.31-33 However, prior clinical studies
combining diltiazem with quinidine and diltiazem with moxifloxacin also demonstrated a lack of QTc
shortening by diltiazem.17, 34 This could be something specific to diltiazem, including potential
secondary effects due to an autonomic response from diltiazem’s effect on blood pressure orchanges in ventricular loading from atrio-ventricular delay with mechanoelectrical feedback fromstretch-activated ion channels.35-38
Diltiazem did shorten J-Tpeakc, but also increased Tpeak-Tend; which differs from what wasobserved for late sodium current block combined with predominant hERG block.17 Nevertheless,these findings were considered an exploratory analysis according to the statistical analysis plan.39 Of
note, verapamil and lopinavir/ritonavir, which block hERG and L-type calcium,19 did prolong QTc
without prolonging J-Tpeakc, as expected (Figure 3). Thus, these specific drugs with a combination of
L-type calcium and hERG block exhibited QTc prolongation without J-Tpeakc prolongation.

Summary of QTc and JTpeakc Effects with Comparison to Prior Studies
Figure 6 shows ΔΔQTc and ΔΔJ-Tpeakc changes predicted from the linear-mixed effects models forbalanced ion channel blockers (ranolazine and verapamil in this study along with ranolazine in a priorstudy) in comparison to predominant hERG blockers (dofetilide in two studies, quinidine andmoxifloxacin). Concentration has been normalized in the X axis to facilitate comparison.15, 17
Chloroquine and lopinavir/ritonavir are not shown because because poor fit of concentrationresponse linear models did not allow for reliable predictions of ΔΔJ-Tpeakc for chloroquine and
ΔΔQTc for lopinavir/ritonavir. At concentrations causing mean ΔΔQTc prolongations above 10 ms,
the concentration-matched mean ΔΔJ-Tpeakc changes remained close to zero or decreased forbalanced blockers but increased proportionally to QTc for the predominant hERG blockers. The
normalized concentration-response relationships are consistent across studies and drugs withbalanced blockers prolonging QTc without prolonging J-Tpeakc, while predominant hERG blockers
prolong QTc and J-Tpeakc.16, 18
It is important to note that the presence vs. absence of J-Tpeakc prolongation interpreted inisolation alone does not necessarily portend the presence vs. absence of proarrhythmic risk. CiPA
proposes that the ECG data should be interpreted with the nonclinical ion channel data and in silico
Torsade Metric Score. In addition, moxifloxacin is a drug that is a predominant hERG blocker,
however it has weak hERG block at standard clinical exposures and thus a substantially lower risk of
torsade compared to dofetilide or quinidine.

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Potential Implications of CiPA

Accepted Article

ICH E14 states that it is inconclusive as to whether drugs that prolong QTc are proarrhythmic andthat certain factors may modify the risk of QTc prolongation, including prolonging QTc up to a“plateau” value and that proarrhythmic risk might be influenced by other pharmacologic effects(e.g., other ion channel effects in addition to hERG block).2 While ICH S7B and E14 guidelines statethat the presence of QTc prolongation does not mean that a drug will cause arrhythmias and thepresence of QTc prolongation should support planning for and interpretation of subsequent clinicalstudies, the way they have been used in practice has been to sometimes drop compounds or drugs
from development, which may not always be appropriate.40
One of the potential impacts of CiPA is to better inform when QTc prolonging drugs require intensive
ECG monitoring in Phase 3 trials. ICH E14 describes a nuanced approach for ECG monitoring in latestage trials in the Q&A (see Figure 1 in Vicente et al.13). Briefly, the results can be divided into
categories of whether the mean ΔΔQTc at therapeutic exposures is <10 ms, 10-20 ms or >20 ms. In
the current ICH E14 Q&A, if the ΔΔQTc at maximal “worst case” therapeutic exposures is <10 ms,
only routine ECG monitoring is recommended in late phase trials. Or, if higher exposures are only
expected in a limited subset of patients, intensive ECG monitoring may only be required in thatspecific patient population. However, if the ΔΔQTc effect is 10-20 ms at therapeutic exposure,
intensive ECGs are needed, and if ΔΔQTc is >20 ms, intensive ECGs and risk mitigation strategies are
warranted.
It has been proposed that CiPA could impact clinical development for a drug with ΔΔQTc effect of
10-20 ms at worst-case therapeutic exposures, where a combined nonclinical and clinical integrated
risk assessment should be taken into account to determine what level of ECG monitoring isappropriate in Phase 3. If the ΔΔQTc effect is >20 ms at therapeutic concentrations, it is anticipatedthat intensive ECG monitoring would still be required; however, the combined nonclinical andclinical data could be taken into account to better inform the type and extent of ECG monitoring andrisk mitigation strategies. In addition, a goal of CiPA is to enable updating drug labels to be more
informative about proarrhythmic risk, not just QT prolongation.

Conclusions
Results of this study suggest that concentration-response analysis of QTc and J-Tpeakc candifferentiate QTc prolonging drugs with predominant hERG block from drugs that have balanced ionchannel block. However, small sample sizes (10 subjects) may be insufficient to characterize
concentration-response relationships for some multi-channel blocking drugs.
Methods

This study (clinicaltrials.gov number NCT03070470) was approved by the FDA Research Involving
Human Subjects Committee and the local institutional review board. All subjects gave written
informed consent and the study was performed at a Phase 1 clinic (Spaulding Clinical, West Bend,
WI). The study rationale and design along with the protocol were previously published.13 The designis briefly summarized below.

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Accepted Article

Part 1 was a double-blind, randomized, placebo-controlled, 1-period parallel design to assess theeffects of three balanced blockers (ranolazine, verapamil, and lopinavir/ritonavir combination), one
predominant hERG blocker (chloroquine) and one placebo on the QTc and J-Tpeakc intervals in 50
healthy subjects. This parallel design is similar to early phase 1 studies and resulted in each study
drug being administered to 10 subjects, and placebo to 10 subjects, in 3 consecutive days to achieve
low and high drug plasma concentration levels on days 1 and 3, respectively. Administered drugs,
their dosing times and their pharmacokinetic time profiles are shown in Figure 1.
Part 2 was a double-blind, randomized, 2-period crossover design in 10 subjects to assess whether
diltiazem (calcium channel block) can reduce the QTc prolongation from dofetilide (hERG block) by
shortening J-Tpeakc. In the dofetilide alone period, subjects received dofetilide on days 1 and 3. In
the diltiazem + dofetilide period, subjects received diltiazem alone on days 1 and 2, and diltiazem +dofetilide on day 3. Dosing times and PK profiles are shown in Figure 4.

ECG assessment
Continuous ECG recordings were performed using the Mortara Surveyor system (Mortara,
Milwaukee, WI) sampled at 500 Hz with an amplitude resolution of 2.5 µV. From the continuousrecording, three ECGs were extracted before the draw of each pharmacokinetic sample, based onheart rate stability and signal quality41 at 28 time-points during the treatment periods: -1 hour, -30
minutes, 0 (immediately before first oral dose on Day 1), 0.5, 2, 2.5, 3.5, 4.5, 5, 6, 8.5, 14, 24, 27.5,
32.5, 38, 48, 50, 50.5, 51.5, 52.5, 53, 54, 54.5, 55, 59, 61, and 73 hours after time 0 or the first oral
dose on Day 1. The ECG extractions at -1 hour, -30 minutes, and time 0 (immediately before first oral
dose on Day 1) were used for the baseline.13 Semi-automated measurements of the PR, QRS, JTpeak, Tpeak-Tend, and QT interval were performed using the derived vector magnitude lead in the
median beat. Briefly, automatic annotations from CalECG (AMPS LLC, New York, NY) for global P
onset, QRS on set and offset, and from a previously developed algorithm42 for Tpeak and Tend weregenerated. Next, two independent ECG readers blinded to treatment and time adjusted themeasurements using high-resolution images using previously developed software.43
None of the drugs caused an absolute mean ΔΔHR > 10 beats per minute (bpm), so the QT interval
and J-Tpeak intervals were corrected for heart rate with pre-specified population correction
formulas.13 Specifically, the QT interval was corrected for heart rate using Fridericia’s correction(QTc=QT/(RR/1,000 ms)1/3, with RR in ms).44 Similarly, the J-Tpeak interval was corrected for heart
rate (J-Tpeakc=J-Tpeak/(RR/1,000 ms)0.58, with RR in ms).14 No correction was performed for the
Tpeak-Tend interval, as prior studies have shown a lack of rate dependence at resting heart rates.14,45

Pharmacokinetic sample analysis
Six validated liquid chromatography tandem mass spectrometric methods were used forpharmacokinetic sample analysis. The first method was the determination of dofetilide in K2EDTA
human plasma using deuterated dofetilide as the internal standard (IS) using simple methanol based
protein precipitation. Reversed-phase ultra-performance liquid chromatographic (UPLC) separation
was achieved with an Acquity UPLC C18 column (2.1 x 100 mm, 1.8 micron). Mass spectrometricThis article is protected by copyright. All rights reserved.

Accepted Article

detection was set at mass transitions of m/z 442.2→198.2. The second, third and fourth methods
were developed for diltiazem, ranolazine and verapamil. All three analytes and their deuterated
internal standards were chromatographed on Zorbax SB-C18 column (50 X 2.1 mm, 3.5 micron) after
simple protein precipitation using acetonitrile. Mass spectrometric detections were set at m/z 415.3→178.0, m/z 428.3→279.0 and m/z 455.3→177.1 for diltiazem, ranolazine and verapamil,
respectively. The fifth method, determination of chloroquine, and sixth method, simultaneous
determination of lopinavir and ritonavir in K2EDTA human plasma were developed. All three analytes
and their deuterated internal standards were chromatographed on Phenomenex, Kinetex C18 column(50 x 2.1 mm, 1.7 micron). Mass spectrometric detections were set at mass transitions of m/z
320.2→247.2, m/z 629.0→155.2, m/z 722.0→268.1 for chloroquine, lopinavir and ritonavir,
respectively.

Drug categories
Drug categories (i.e., balanced vs. predominant hERG block) were assigned based on ion channel
data available during study design as previously described,13, 19 and not on the qNet score from the insilico model. Ranolazine and verapamil are balanced blockers (similar potency for hERG and latesodium and for hERG and calcium, respectively). Lopinavir/ritonavir blocks hERG, calcium and latesodium at similar potencies and was included as a balanced blocker. Chloroquine has substantiallymore potent hERG block compared to calcium or late sodium and was labeled as a predominanthERG blocker. Drug categories may be different if based on qNet and new ion channel data acquiredwith current CiPA protocols.20

Statistical analysis
The statistical analysis plan was previously published.13 Concentration-response modeling was
performed following current best practices46 with prespecified models. Linear-mixed effects models
were used to characterize the relationship between drug concentration and ECG changes. Thechange from baseline (Δ) for each ECG biomarker (e.g., the average ΔQTc, ΔJ-Tpeakc) by time-point
was the dependent variable, for which baseline was defined as the mean of the three predose ECG
readings on Day 1 for each period. In part 1, we used linear mixed-effects models where ΔECG was
the dependent variable (e.g., ΔQTc, ΔJ-Tpeakc) and drug concentration (set to 0 for placebo),
nominal timepoint, treatment (coded 0 for placebo and 1 for active drug) were included as fixed
effects and subject was included as random effect on intercept and drug concentration (i.e., allowing
each subject to have his own concentration-response relationship). In part 2, we used a linear
mixed-effects model where ΔECG was the dependent variable (e.g., ΔQTc, ΔJ-Tpeakc), dofetilide anddiltiazem concentrations as well as dofetilide-diltiazem interaction were included as fixed effects,
and subject was included as a random effect on intercept and dofetilide and diltiazem
concentrations. All data before withdrawals or discontinuations were included in the analysis. All
statistical analyses were performed in R 3.5.0 (R Foundation for Statistical Computing, Vienna,
Austria).

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Study Highlights

Accepted Article

What is the current knowledge on the topic?
Drug-induced hERG block and QTc prolongation are associated with torsade de pointes. However,there are QTc prolonging drugs that have low torsade risk because they have balanced block of
inward currents (late sodium or L-type calcium) in addition to hERG.

What question did this study address?
Can concentration-response analysis of the J-Tpeakc interval be used in small sample size studies toconfirm that balanced ion channel-blocking drugs do not prolong J-Tpeakc?

What does this study add to our knowledge?
A lack of J-Tpeakc prolongation can confirm balanced ion channel-block, however small sample sizestudies (10 subjects per drug) may be insufficient to characterize concentration-response
relationships in some cases.

How might this change clinical pharmacology or translational science?
A comprehensive non-clinical CiPA assessment combined with assessment of the J-Tpeakc interval
may be able to inform the intensity of ECG monitoring in phase 3 trials and drug labeling for mild-tomoderate QTc prolonging drugs.

Acknowledgements
This work was supported by the FDA Safety Research Interest Group and Critical Path Initiative in theCenter for Drug Evaluation and Research, the FDA’s Office of Women’s Health, and by a research
fellowship from the Oak Ridge Institute for Science and Education through an interagency
agreement between the U.S. Department of Energy and the FDA. We would like to thank staff at
Spaulding Clinical Research for executing the clinical study (NCT03070470).

Authors contributions
D.G.S., J.V., R.Z., L.J., R.OJ., J.W.M., C.S., S.K., P.S., V.P., M.K.M., J.L., J.F., C.G., and N.S. wrote themanuscript; D.G.S., J.V., R.Z., L.J., J.W.M., P.S., V.P., M.K.M., C.G., and N.S. designed the research;
D.G.S., J.V., R.Z., L.J., J.W.M., C.S., and S.K. performed the research; J.V., R.OJ., R.Z., V.P., M.K.M., L.J.,
J.F., C.G., and D.G.S. analyzed the data.

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Figures legends
Figure 1: Part 1 PK time profiles
Figure 1: Mean (dots) and standard error (error bars) of pharmacokinetic plasma concentration
profiles for ranolazine, verapamil, lopinavir, ritonavir, and chloroquine per timepoint after first doseon day 1. Dashed vertical lines show the time of active treatment doses for ranolazine (1,500 mg
after breakfast and in the evening), verapamil (120 mg immediate release after breakfast and in theafternoon, 240 mg extended release in the evening), lopinavir/ritonavir (lopinavir 800 mg/ritonavir
200 mg after breakfast and in the evening), and chloroquine (1,000 mg Day 1, 500 mg Day 2, and
1,000 mg Day 3, all before breakfast). Oral placebo was administered at dosing timepoints that had
no active treatment dosing as well as throughout all the dosing timepoints in the placebo treatmentarm (not shown).

Figure 2: Part 1 PD time profiles
Figure 2: Drug-induced changes (mean ± 90% confidence interval) for the placebo-corrected change
from baseline (ΔΔ) of QTc (black) and J-Tpeakc (orange) for (a) ranolazine, (b) verapamil, (c)lopinavir/ritonavir and (d) chloroquine. Horizontal dashed line corresponds with 0 ms. The y-axis
range of each panel has been adjusted to enhance interpretation. See ECG analysis report in the
online supplement for plots with full free-scale y-axis range including Tpeak-Tend.

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Figure 3: Part 1 concentration-response plots

Accepted Article

Figure 3: Predicted drug-induced placebo-corrected changes from baseline (ΔΔ) using concentrationresponse models for QTc (black) and J-Tpeakc (orange) for (a) ranolazine, (b) verapamil, (c)lopinavir/ritonavir and (d) chloroquine. The solid line with gray shaded area denotes the modelpredicted mean placebo-adjusted ΔΔ with 90% confidence interval (CI) as a function ofconcentration. Horizontal solid line with tick marks show the range of plasma concentrations divided
into deciles. Vertical error bars denote the observed means and 90% CI for the ΔΔ within eachplasma concentration decile. Vertical dashed lines correspond with population average maximum
concentration (Cmax) on days 1 (low Cmax) and 3 (high Cmax). Horizontal dashed and dotted lines
correspond with 0 ms and 10 ms ΔΔ, respectively. The y-axis range of each panel has been adjusted
to enhance interpretation. See ECG analysis report in the online supplement for plots with full freescale y-axis range as well as other ECG measurements.

Figure 4: Part 2 PK time profiles
Figure 4: Mean (dots) and standard error (error bars) of pharmacokinetic plasma concentration
profiles per timepoint after first dose on day 1 for dofetilide by itself (top panel) and for diltiazem +dofetilide combination (bottom panel). Bottom panel shows diltiazem concentration (right Y axis,
green solid lines) and dofetilide (right Y axis, black dashed line). Dosing times were in the morning(after breakfast) and in the evening of days 1 and 2, and after breakfast in the morning of day 3.
Dashed vertical lines show the time of active treatment doses for dofetilide (0.125 mg and 0.375 mg
after breakfast on days 1 and 3, respectively, of dofetilide alone period, and 0.25 mg after breakfast
on day 3 in the diltiazem + dofetilide period) and diltiazem (120 mg immediate release after
breakfast on days 1 and 3, and 240 mg in the evening of days 1 and 2). Oral placebo wasadministered at dosing timepoints matching part 1 and that had no active treatment dosing (notshown).

Figure 5: Part 2 PD time-profiles and concentration-response linearity
plots
Figure 5: Top row panels show drug-induced changes (mean±90% confidence interval) for thechange from baseline (Δ) of (a) QTc, (b) J-Tpeakc and (c) Tpeak-Tend on day 3 of dofetilide alone(black) and diltiazem + dofetilide (orange) treatments. The y-axis range of each panel has beenadjusted to enhanced interpretation. Bottom row panels show exploratory plots with linear
regression fit through all the data for dofetilide alone (black) and diltiazem + dofetilide (orange) for
drug-induced changes from baseline (Δ) in (a) QTc, (b) J-Tpeakc, and (c) Tpeak-Tend. Note that there
is no change in ΔQTc prolongation associated with dofetilide (hERG block) when diltiazem (calcium
block) is coadministered. See online supplement for full time profiles as well as concentrationresponse plots of dofetilide (hERG block) vs. dofetilide + diltiazem (hERG + calcium) vs. dofetilide +mexiletine (hERG + late sodium).

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Figure 6: ΔΔQTc and ΔΔJ-Tpeakc concentration-response for several
predominant hERG and balanced ion channel blocking drugs

Accepted Article

Figure 6: As concentration of drug increases, balanced blockers prolong ΔΔQTc (top left) without
prolonging ΔΔJ-Tpeakc (bottom left), but predominant hERG blokers prolong both ΔΔQTc (top rigth)
and ΔΔJ-Tpeak (bottom right). Plots show mean (color lines) and 90% confidence intervals (shade
areas) predictions for drug-induced baseline- and placebo-corrected changes in QTc (ΔΔQTc, y axis,
top panels) and ΔΔJ-Tpeakc (y axis, bottom panels) vs. drug concentration (x axis) fromconcentration-response models. Before plotting, each drug concentration was normalized to theconcentration that caused 20 ms ΔΔQTc prolongation in its corresponding study. Balanced blockers
shown include ranolazine (hERG + late sodium, blue), and verapamil (hERG + calicum, green).
Predominant hERG blockers shown are dofetilide (gray), moxifloxacin (dark orange), and quinidine(light orange). Data from this study for multiple dosing of ranolazine (ranolazine-2) and verapamil(solid lines) and from two prior studies with single oral dose design (ranolazine-1, dofetilide-1, andquinidine from Johannesen et. al 2014,15 dashed lines; dofetilide-2 and moxifloxacin from
Johannesen et al. 2016,17 dotted lines). Chloroquine and lopinavir/ritonavir not shown because
because poor fit of concentration-response linear models did not allow for reliable predictions of
ΔΔJ-Tpeakc (chloroquine) and ΔΔQTc (lopinavir/ritonavir). Black horizontal lines show 0 ms (dashed)
and 10 ms (dotted) thresholds for QTc (top panels) and ΔΔJ-Tpeakc (bottom panels). Ranges of X andY axes adjusted to to facilitate comparison.

Supplementary MaterialsHTML with Analysis CodeSupplemental Material

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ccepted Articl

Table 1: Part 1 drug-induced ECG predicted changes

Drug

Day

Cmax

ΔΔQTc

ΔΔJ-Tpeakc

ΔΔTpeak-Tend

ΔΔPR

ΔΔQRS

Ranolazine

11191.2 ng/mL

14.1 [7.5 to 20.8] ms

2.2 [-4.3 to 8.7] ms

11.9 [5.9 to 17.9] ms

0.7 [-2.5 to 3.8] ms-0.5 [-3.3 to 2.3] ms

33046.3 ng/mL

28.2 [18.3 to 38.2] ms

1.2 [-9.5 to 12.0] ms

25.7 [14.7 to 36.7] ms

3.1 [-0.8 to 6.9] ms-0.2 [-3.5 to 3.0] ms

1

101.0 ng/mL

8.6 [4.4 to 12.9] ms

3.6 [-2.4 to 9.7] ms

4.4 [0.6 to 8.2] ms

13.2 [7.2 to 19.2] ms

0.3 [-2.0 to 2.7] ms

3

398.4 ng/mL

13.9 [10.0 to 17.8] ms-2.6 [-11.4 to 6.1] ms

14.9 [9.1 to 20.6] ms

52.2 [27.9 to 76.6] ms** 1.8 [-1.7 to 5.4] ms

110734.2 ng/mL*

1.2 [-5.4 to 7.8] ms*

14.8 [10.3 to 19.4] ms

324351.5 ng/mL*-2.9 [-14.6 to 8.8] ms*

33.5 [22.7 to 44.4] ms** *1

228.8 ng/mL

30.7 [22.6 to 38.9] ms*

13.1 [8.4 to 17.9] ms

9.3 [2.8 to 15.8] ms

5.5 [3.0 to 8.0] ms

3404.9 ng/mL

50.5 [38.5 to 62.5] ms*

24.9 [17.2 to 32.7] ms

14.8 [4.7 to 24.9] ms

9.9 [6.1 to 13.6] ms

Verapamil

Lopinavir

Chloroquine*

Drug-induced placebo-corrected changes from baseline for QTc, J-Tpeakc, Tpeak-Tend, PR and QRS intervals at Cmax of days 1 and 3 for each treatment inPart 1. *: Values not reported because poor fit of concentration-response linear models did not allow for reliable predictions. **: Goodness of fit plotssuggest linear models may overestimate ΔΔPR effects around Cmax (see text and online supplement for comparison with E-max and sigmoid models).

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