Skip to main content
Log in

Clinical Trial Simulation Using Therapeutic Effect Modeling: Application to Ivabradine Efficacy in Patients with Angina Pectoris

  • Published:
Journal of Pharmacokinetics and Pharmacodynamics Aims and scope Submit manuscript

Abstract

Ivabradine is a new bradycardic agent with a potential indication for stable angina pectoris. To investigate the best compromise between efficacy, safety, drug regimen, and number of patients to include in a phase III study, we conducted Monte Carlo simulations using a full therapeutic model. The binary clinical outcome, chest pain, was simulated using a physiologic model in which the coronary reserve was derived from the heart rate. Safety was defined as being heart rate dependent. Using real data to build a pharmacokinetic–pharmacodynamic model controlling drug effect (i.e., heart rate decrease), and resampling heart rate profiles from the database, 100 clinical trials (N=200) were simulated for five oral doses (2.5, 5, 10, 20, and 40 mg QD or BID) of ivabradine. Only 25% of the simulated trials showed a significant effect of ivabradine with doses up to 10 mg QD, and 48 and 55% of the trials with doses of 10 mg BID and 20 mg QD, respectively, and more than 80% of the trials with a 40 mg daily dose. For safety, 4% of patients had at least one adverse event in the untreated group, and from 5 to 13% in the treated groups for the lowest to the highest dose, respectively. The number of subjects to include in a future trial to obtain a 15% decrease in chest pain under the assumption of a 68% base risk, is 239 subjects per group with 10 mg BID or 196 with 20 mg QD. These results illustrate how clinical trial simulations including a PK/PD model as well as a physiopathologic mechanistic model, describing the relationship between the intermediate and clinical endpoint, and the resampling of real patients from a large database can help in designing future phase III trials.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

REFERENCES

  1. C. C. Peck and R. E. Desjardins. Simulation of clinical trials: encouragement and cautions. Applied Clinical Trials. 5:30–32 (1996).

    Google Scholar 

  2. M. D. Hale, W. R. Gillepsie, S. K. Gupta, B. Tuk, and N. H. Holford. Clinical trial simulation: streamlining your drug development process. Applied Clinical Trials. 8:35–40 (1996).

    Google Scholar 

  3. L. Aarons, M. O. Karlsson, F. Mentre, F. Rombout, and J. L. Steimer. Role of modelling and simulation in Phase I drug development. Eur. J. Pharm. Sci. 13:115–122 (2001).

    PubMed  Google Scholar 

  4. L. B. Sheiner and J. L. Steimer. Pharmacokinetic/Pharmacodynamic modelling in drug development. Annu. Rev. Pharmacol. Toxicol. 40:67–95 (2000).

    PubMed  Google Scholar 

  5. N. H. G. Holford, H. C. Kimko, J. P. R. Montelone, and C. C. Peck. Simulation of clinical trials. Annu. Rev. Pharmacol. Toxicol. 40:209–234 (2000).

    Article  PubMed  Google Scholar 

  6. H. C. Kimko, S. S. Reele, N. H. Holford, and C. C. Peck. Prediction of the outcome of a phase 3 clinical trial of an antischizophrenic agent (quetiapine fumarate) by simulation with a population pharmacokinetic and pharmacodynamic model. Clin. Pharmacol. Ther. 68:568–577 (2000).

    PubMed  Google Scholar 

  7. N. H. Holford, H. C. Kimko, J. P. Monteleone, and C. C. Peck. Simulation of clinical trials. Annu. Rev. Pharmacol. Toxicol. 40:209–234 (2000).

    Article  PubMed  Google Scholar 

  8. C. Veyrat-Follet, R. Bruno, R. Olivares, G. R. Rhodes, and P. Chaikin. Clinical trial simulation of docetaxel in patients with cancer as a tool for dosage optimization Clin. Pharmacol. Ther. 68:677–687 (2000).

    PubMed  Google Scholar 

  9. J. P. Boissel, J. P. Collet, and M. Haugh. Surrogate endpoints: a basis for a rational approach. Eur. J. Clin. Pharmacol. 43:235–244 (1992).

    PubMed  Google Scholar 

  10. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin. Pharmacol. Ther. 69:89–95 (2001).

    PubMed  Google Scholar 

  11. M. Tomita. Whole-cell simulation: a grand challenge of the 21st century. Trends Biotechnol. 19:205–210 (2001).

    PubMed  Google Scholar 

  12. S. M. Ngai, M. M. Way, H. Chan, S. K. Tsui, C. Y. Lee, and K. P. Fung. In silico studies of energy metabolism of normal and diseased heart. Mol. Biol. Rep. 27:123–128 (2000).

    PubMed  Google Scholar 

  13. I. Ragueneau, C. Laveille, R. Jochemsen, G. Resplandy, C. Funck-Brentano, and P. Jaillon. Phamacokinetic-pharmacodynamic modeling of the effects of ivabradine, a direct sinus node inhibitor, on HR in healthy volunteers. Clin. Pharmacol. Ther. 64:192–203 (1998).

    PubMed  Google Scholar 

  14. F. Gueyffier, F. Boutitie, C. Cornu, G. Julien, P. Poncelet, A. Sebaoun, C. Avierinos, and J. P. Boissel. Présentation d'OCTAVE II. Une étude épidémiologique en cours en France sur la valeur pronostique ajoutée par la mesure ambulatoire de la pression artérielle. Arch. Mal. Coeur. Vaiss. 89:1381–1388 (1996).

    PubMed  Google Scholar 

  15. F. Gueyffier, C. Cornu, N. Bossard, C. Mercier, P. Poncelet, A. Sebaoun, G. Julien, C. Avierinos, J. Y. Fraboulet, and J. P. Boissel. Intérêt pronostique de la mesure ambulatoire de la pression artérielle en France. Premiers résultats de l'étude OCTAVE II. Arch. Mal. Coeur. Vaiss. 92:1151–1157 (1999).

    PubMed  Google Scholar 

  16. S. B. Duffull, S. Chabaud, P. Nony, C. Laveille, P. Girard, and L. Aarons. A pharmacokinetic simulation model for ivabradine in healthy volunteers. Eur. J. Pharm. Sci. 10:285–294 (2000).

    PubMed  Google Scholar 

  17. S. B. Duffull and L. Aarons. Development of a sequential linked pharmacokinetic and pharmacodynamic simulation model for ivabradine in healthy volunteers. Eur. J. Pharm. Sci. 10:275–284 (2000).

    PubMed  Google Scholar 

  18. S. L. Beal, A. J. Boeckman, and L. B. S heiner. NONMEM Users Guide, NONMEM Project Group, San Francisco: University of California (1996).

    Google Scholar 

  19. Y. Yano, S. L. Beal, and L. B. Sheiner. Evaluating pharmacokinetic/pharmacodynamic models using the posterior predictive check. J. Pharmacokinet. Pharmacodyn 28:171–192 (2001).

    PubMed  Google Scholar 

  20. F. Kappel and R. O. Peer. A mathematical model for fundamental regulation processes in the cardiovascular system. J. Math. Biol. 31:611–631 (1993).

    PubMed  Google Scholar 

  21. A. Maseri, S. Chierchia, and J. C. Kaski. Mixed angina pectoris. Am. J. Cardiol. 56:30E-33E (1985).

    PubMed  Google Scholar 

  22. D. H. Spodick. Normal sinus heart rate redefined. Eur. Heart. J. 14:865 (1993).

    PubMed  Google Scholar 

  23. D. H. Spodick. Normal sinus heart rate: sinus tachycardia and sinus bradycardia redefined. Am. Heart. J. 124:1119–1121 (1992).

    PubMed  Google Scholar 

  24. P. Francheteau, J. L. Steimer, H. Merdjan, M. Guerret, and C. Dubray. A mathematical model for dynamics of cardiovascular drug action: application to intravenous dihydropyridines in healthy volunteers. J. Pharmacokinet. Biopharm. 21:489–514 (1993).

    PubMed  Google Scholar 

  25. F. S. Grodins. Integrative cardiovascular physiology: a mathematical synthesis of cardiac and blood vessel hemodynamics. Q. Rev. Biol. 34:93–116 (1959).

    PubMed  Google Scholar 

  26. SAS User Guide, version 6, 1st ed., Cary (NC), SAS Institute, 1990.

  27. S-PLUS4 Programmer's Guide, version 4.0, MathSoft. Inc., Seattle, Washington, 1997.

  28. J. T. Casagrande, M. C. Pike, and P. G. Smith. An improved approximate formula for calculating sample sizes for comparing two binomial distributions. Biometrics. 34:483–486 (1978).

    PubMed  Google Scholar 

  29. S. Glasser, D. Michie, U. Thadani, and W. Baiker for the Zatebradine investigators. Effects of Zatebradine, a sinus node inhibitor, on HR and exercise duration in chronic stable angina. Am. J. Cardiol. 79:1401–1405 (1997).

    PubMed  Google Scholar 

  30. W. Frishman, C. Pepine, R. Weiss, and W. Baiker for the Zatebradine investigators. Addition of Zatebradine, a direct sinus node inhibitor, provides no greater exercise tolerance benefit in patients with angina taking extended-release Nifedipine: results of a multicenter, randomized, double blind placebo-controlled, parallel-group study. J. Am. Coll. Cardiol. 26:305–312 (1995).

    PubMed  Google Scholar 

  31. J. Stamler, D. Wentworth, and J. D. Neaton. Is relationship between serum cholesterol and risk of premature death from coronary heart disease continuous and graded? Findings in 356,222 primary screenees of the multiple risk factor intervention trial (MRFIT). J. Am. Med. Assoc. 256:2823–2828 (1986).

    Google Scholar 

  32. J. D. Cohen. Abnormal electrocardiograms and cardiovascular risk: role of silent myocardial ischemia. Evidence from MRFIT. Am. J. Cardiol. 70:14F-18F (1992).

    PubMed  Google Scholar 

  33. F. Gueyffier, J. P. Boissel, F. Boutitie, S. Pocock, J. Coope J. Cutler, T. Ekbom, R. Fagard, L. Friedman, K. Kerlikowske, M. Perry, R. Prineas, and E. Schron. Effect of antihypertensive treatment in patients having already suffered from stroke. Gathering the evidence. The INDANA (Individual Data Analysis of Antihypertensive intervention trials) Project Collaborators. Stroke. 28:2557–2562 (1997).

    PubMed  Google Scholar 

  34. A. J. Dobson, A. Evans, M. Ferrario, K. A. Kuulasmaa, V. A. Moltchanov, S. Sans, H. Tunstall-Pedoe, J. O. Tuomilehto, H. Wedel, and J. Yarnell. Changes in estimated coronary risk in the 1980s: data from 38 populations in the WHO MONICA Project. World Health Organization. Monitoring trends and determinants in cardiovascular diseases. Ann. Med. 30:199–205 (1998).

    PubMed  Google Scholar 

  35. Geigy Scientific Tables, Volume 5, Heart and Circulation. Edited by C. Lentner. Published by Ciba-Geigy, 1990.

  36. D. G. Brown, E. L. Bolson, and H. T. Dodge. Dynamic mechanisms in human coronary stenosis. Circulation. 70:917 (1984).

    PubMed  Google Scholar 

  37. B. De Bruyne, J. Bartunek, S. U. Sys, and G. R. Heyndrickx. Relation between myocardial fractional flow reserve calculated from coronary pressure measurements and exerciseinduced myocardial ischemia.Circulation. 92:39–46 (1995).

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sylvie Chabaud.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chabaud, S., Girard, P., Nony, P. et al. Clinical Trial Simulation Using Therapeutic Effect Modeling: Application to Ivabradine Efficacy in Patients with Angina Pectoris. J Pharmacokinet Pharmacodyn 29, 339–363 (2002). https://doi.org/10.1023/A:1020953107162

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1020953107162

Navigation