Dr. Paul Frohna, a biotech consultant with expertise in translational medicine and clinical pharmacology, presents an overview of the FDA's evolving perspectives on the QTc issue and the stand alone thorough QTc study.

1. PK-PD Modeling with the QTc:
Is it possible to avoid a TQT Study?
Part 2. Approaches to QTc Evaluation During
Clinical Development
Paul A. Frohna, MD, PhD, PharmD
Biotechnology Consultant
Frohna Biotech Consulting
www.frohnabiotechconsulting.com

2. Approaches to QTc Evaluation
During Clinical Development
Role of PK-PD
Recent Examples and Outcomes

3. The Learn-Confirm Approach for
QTc Assessment
 Learn: Collect ECG data in Phase I/IIa for
exposure-response analysis with PK and DQTc
– Requires advanced planning
– Helps determine Phase III ECG monitoring frequency
– Risk reduction strategy
 Confirm: Design your TQT study based on your
―Learn‖ analysis
– May allow smaller sample sizes
 May be acceptable to regulatory authorities
when a TQT study is infeasible or when
significant amounts of QTc data have already
been collected (some examples will be given)

4. PK-QTc Evaluation of Ranolazine (Ranexa)
A Comprehensive Database Planned
 Developed by CV Therapeutics (now Gilead) for the
symptomatic treatment of angina
– Cardiac drug that has multiple electrophysiologic effects
and an uncertain MOA, but not an anti-arrhythmic
 All ECGs in CVT-sponsored studies read by a
central core ECG laboratory
 Population QTc analysis of data from 15 studies
– 15,819 QTc-plasma concentration pairs
– All observations at steady state
 CV Therapeutics and FDA agreed that ranolazine
prolonged QTc but patient risk was different

5. Assessment of QTc Effects of Ranolazine
Infusion to Intolerability Study
15000
31 subjects: 16 male, 15 female
5137 ECGs (3355 on ranolazine)
Target [RAN], ng/mL
Placebo (single-blind, all subjects)
Ranolazine (double-blind)
10000
5000
Vitals
PK
ECG
0
-24 0 24 48 72 96 120 -24 0 24 48 72 96 120 -24 0 24 48 72 96 120
Time, hr
Ranolazine n = 22 Ranolazine n = 22 Ranolazine n = 7
Placebo n = 6 Placebo n = 6 Placebo n = 3

6. Ranolazine Concentration vs. ∆QTc
Infusion to Intolerability Study
100 Slope = 2.29 msec per 1000 ng/mL (R2 = 0.20)
80
ΔQTc vs averaged baseline, msec
60
40
20
0
-20 The target concentration of
15,000 ng/mL could not be
-40 reached due to dizziness,
nausea, postural hypotension,
-60 diplopia, somnolence, syncope,
50% 95% Max and paresthesia.
-80
-100
0 2000 4000 6000 8000 10000 12000
Plasma ranolazine concentration, ng/mL
Individually optimized regressions of mean RR intervals and median QT intervals.
Percentiles are peak concentrations on 1000 mg bid in CVT 3031 and CVT 3033 shown for comparison.

7. Clinical Events With Potential QTc Link
Phase II/III Controlled Studies
Patients with events, n (%)
Ranolazine, mg bid
Placebo 500 750 1000 1500
Total patients, N 455 181 279 459 187
Preferred term
Dizziness 6 (1.3) 2 (1.1) 10 (3.6) 29 (6.3) 22 (11.8)
Heart arrest 1 (0.2) 0 0 1 (0.2) 0
Palpitation 5 (1.1) 0 2 (0.7) 2 (0.4) 4 (2.1)
Sudden death 2 (0.4) 1 (0.6) 1 (0.4) 1 (0.2) 0
Syncope 0 0 0 5 (1.1) 3 (1.6)
Ventricular fibrillation 0 1 (0.6) 0 0 0
Ventricular tachycardia 0 0 1 (0.4) 0 0
Torsade de pointes 0 0 0 0 0

8. Summary—Ranolazine and DQTc
 The QTc effect of ranolazine is well characterized
– At plasma concentrations exceeding tolerability
– Remains linear at 2.4 msec per 1000 ng/mL
 The slope of the ranolazine vs DQTc relationship was
not altered by important covariates:
– Heart rate – Heart failure – Age
– Gender – Diuretics – Anti-anginals
– This is a different profile from drugs known to cause TdP
 Intolerability limits exposure to concentrations
associated with larger QTc increases
 Approved by FDA and EMA

9. FDA’s Analysis of YOUR PKQT Data
Excerpted from the FDA Reviewer’s comments for the Ranolazine NDA

10. Concentration-QTc Modeling
as a Tool During Development

11. Use of a Phase I/II PK-QTc Dataset
Shashank Rohatagi et al. ACoP 2008 . ROLE OF MODELING AND SIMULATION IN EVALUATING THE
QTc PROLONGATION POTENTIAL OF DRUGS
Model based on Phase I/IIa Data Results from TQT Study
Conclusions:
1. Negative TQT study results with the anti-diabetic drug confirmed negative
simulation results from phase I/II C-QT models.
2. C-QT modeling should be implemented as a standard part of modeling and
simulation at different phases of drug development and used in conjunction with
other data that influence the need and/or the timing of a TQT study.

12. First-in-Human Near Thorough QT Study
Malik M. et al. J Clin Pharm. Aug 29, 2008.
Comparison to Completed TQT: A thorough QT study was completed after the studies
used to build the PK and E-R models. The TQT study was negative, indicating
agreement with the C-QT model.

13. First-in-Human Near Thorough QT Study
Malik M. et al. J Clin Pharm. Aug 29, 2008.
The linear regression model predicts a mean 0.6-millisecond QTc interval
prolongation per every 1000-ng/mL increase in drug concentration

14. Regulatory Acceptability of the Study?
Malik M. et al. J Clin Pharm. Aug 29, 2008.

15. FIH Study Conclusions
Malik M. et al. J Clin Pharm. Aug 29, 2008.
 When 2 cohorts of the lowest, middle, and
highest doses were pooled (12 subjects per
active Tx group), the spreads of placebo-
corrected ΔΔQTc values were within the
regulatory requirements (single-sided 95%
confidence interval <10 milliseconds) at all time
points.
 The ECG design of the FIH study provided data of
regulatory acceptable accuracy at a small fraction
of the cost of a full thorough QT study.
 No disclosure if the data were accepted by FDA

16. Using PK-PD Modeling when a TQT
Study is Not Feasible or Ethical
 Most biologics, due to dosing considerations
(max dose, half-life, etc…), MOA and potential
side effect profile
 When you can’t use healthy subjects
– Toxicity : Droperidol—small molecule anti-emetic
– Most anti-cancer agents, particularly cytotoxics
• Example—Erlotinib (Tarceva®, Genentech/OSI)
– Started TQT but first 6 subjects developed severe facial
rash at clinical dose so stopped the study
– Designed PK-QT sub-study within the Phase 3 program at a
couple of academic, high enrolling sites with capabilities of
doing ―intensive PK‖ and QTc recording—FDA accepted

17. Droperidol Study #1: PK and QTc
Assessment of Single IV
 Concentration-QT Study of 3 IV bolus doses (0.625 mg, 2.5 mg,
and 5 mg) of droperidol were studied in a 4 period, single-blind,
placebo-controlled, crossover trial in healthy subjects.
 8 subjects were enrolled and exposed to one or more doses for a
total of 15 exposures
 Study was stopped because of moderate to severe
neuropsychiatric side effects experienced by the volunteers.
 Trend toward a dose dependent increase in the mean maximal
QTc interval change from baseline (placebo subtracted) of 1, 13,
and 30 milliseconds on the 3 doses respectively.
 Outlier QTc changes of 77 and 79 msec on 2.5 & 5 mg
M.Desai1, A.Pinto2, A.Adigun2, J.Hilligoss2, S.H.Haidar1, N.Chang1, B.Rappaport1, S.M.Huang1,
J.C.Gorski2, S.D.Hall2, 1CDER, FDA, Rockville, MD, 2Indiana University, Indianapolis, IN

18. Droperidol Study #2: PK-QTc of Single IV Doses
of 1 mg Droperidol and 4 mg Ondansetron
Charbit B. et al. Anesthesiology 2008; 109:206–12
A crossover study of 16 healthy volunteers. The linear regression was significant with
droperidol (r =0.34, P=0.005) but not with ondansetron (r =0.16, P=0.26). Continuous
lines represent the linear regression with the 95% prediction band.

19. Final Thoughts
 Conc-QTc Modeling is an important tool in the
clinical development plan within ICH E14
 More examples of Conc-QTc modeling of Phase I
and II data accurately predicting the results from
TQT studies will lead to greater regulatory
acceptance of these efforts
 Conc-QTc data collection requires careful
planning early in clinical development to make the
most of your clinical trials and to understand your
ECG risk early
 Ultimate goal is to not have to do the TQT study,
which IS possible but you need to be prepared