PK-PD Modeling with the QTc:Is it possible to avoid a TQT Study? Part 2. Approaches to QTc Evaluation During             C...
Approaches to QTc Evaluation During Clinical Development          Role of PK-PD  Recent Examples and Outcomes
The Learn-Confirm Approach forQTc Assessment Learn: Collect ECG data in Phase I/IIa for  exposure-response analysis with ...
PK-QTc Evaluation of Ranolazine (Ranexa)A Comprehensive Database Planned Developed by CV Therapeutics (now Gilead) for th...
Assessment of QTc Effects of Ranolazine                      Infusion to Intolerability Study                      15000  ...
Ranolazine Concentration vs. ∆QTc   Infusion to Intolerability Study                                        100        Slo...
Clinical Events With Potential QTc LinkPhase II/III Controlled Studies                                       Patients with...
Summary—Ranolazine and DQTc The QTc effect of ranolazine is well characterized  – At plasma concentrations exceeding tole...
FDA’s Analysis of YOUR PKQT DataExcerpted from the FDA Reviewer’s comments for the Ranolazine NDA
Concentration-QTc Modelingas a Tool During Development
Use of a Phase I/II PK-QTc Dataset  Shashank Rohatagi et al. ACoP 2008 . ROLE OF MODELING AND SIMULATION IN EVALUATING THE...
First-in-Human Near Thorough QT StudyMalik M. et al. J Clin Pharm. Aug 29, 2008.    Comparison to Completed TQT: A thoroug...
First-in-Human Near Thorough QT StudyMalik M. et al. J Clin Pharm. Aug 29, 2008.    The linear regression model predicts a...
Regulatory Acceptability of the Study?Malik M. et al. J Clin Pharm. Aug 29, 2008.
FIH Study ConclusionsMalik M. et al. J Clin Pharm. Aug 29, 2008. When 2 cohorts of the lowest, middle, and  highest doses...
Using PK-PD Modeling when a TQTStudy is Not Feasible or Ethical Most biologics, due to dosing considerations  (max dose, ...
Droperidol Study #1: PK and QTcAssessment of Single IV Concentration-QT Study of 3 IV bolus doses (0.625 mg, 2.5 mg,  and...
Droperidol Study #2: PK-QTc of Single IV Dosesof 1 mg Droperidol and 4 mg OndansetronCharbit B. et al. Anesthesiology 2008...
Final Thoughts Conc-QTc Modeling is an important tool in the  clinical development plan within ICH E14 More examples of ...
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Paul frohna -PK-PD Modeling and the QTc Issue (part 2- Approaches to QTc Evaluation During Clinical Development)

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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.

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Paul frohna -PK-PD Modeling and the QTc Issue (part 2- Approaches to QTc Evaluation During Clinical Development)

  1. 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. 2. Approaches to QTc Evaluation During Clinical Development Role of PK-PD Recent Examples and Outcomes
  3. 3. The Learn-Confirm Approach forQTc 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. 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. 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 5000VitalsPKECG 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. 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/mLIndividually 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. 7. Clinical Events With Potential QTc LinkPhase II/III Controlled Studies Patients with events, n (%) Ranolazine, mg bid Placebo 500 750 1000 1500Total patients, N 455 181 279 459 187Preferred 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. 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. 9. FDA’s Analysis of YOUR PKQT DataExcerpted from the FDA Reviewer’s comments for the Ranolazine NDA
  10. 10. Concentration-QTc Modelingas a Tool During Development
  11. 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 StudyConclusions: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. 12. First-in-Human Near Thorough QT StudyMalik 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. 13. First-in-Human Near Thorough QT StudyMalik 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. 14. Regulatory Acceptability of the Study?Malik M. et al. J Clin Pharm. Aug 29, 2008.
  15. 15. FIH Study ConclusionsMalik 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. 16. Using PK-PD Modeling when a TQTStudy 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. 17. Droperidol Study #1: PK and QTcAssessment 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. 18. Droperidol Study #2: PK-QTc of Single IV Dosesof 1 mg Droperidol and 4 mg OndansetronCharbit B. et al. Anesthesiology 2008; 109:206–12A crossover study of 16 healthy volunteers. The linear regression was significant withdroperidol (r =0.34, P=0.005) but not with ondansetron (r =0.16, P=0.26). Continuouslines represent the linear regression with the 95% prediction band.
  19. 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

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