Skip to main content
SpringerLink
Log in

Modelling of drug-induced QT-interval prolongation: estimation approaches and translational opportunities

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

Abstract

Safety pharmacology studies are performed to assess whether compounds may provoke severe arrhythmias (e.g. Torsades de Pointes, TdP) and sudden death in man. Although there is strong evidence that drugs inducing TdP in man prolong the QT interval in vivo and block the human ether-a-go-go-related gene (hERG) ion channel in vitro, not all drugs affecting the QT interval or the hERG will induce TdP. Nevertheless, QT-interval prolongation and hERG blockade currently represent the most accepted early risk biomarkers to deselect drugs. An extensive pharmacokinetic/pharmacodynamic (PK/PD) analysis is developed to understand moxifloxacin’s-induced effects on the QT interval by comparing the relationship between results of an in vitro patch-clamp model to in vivo models. The frequentist and the fully Bayesian estimation procedures were compared and provided similar performances when the best model selected in NONMEM is subsequently implemented in WinBUGS, which guarantees a straightforward calculation of the probability of QT-interval prolongation greater than 2.5 % (10 ms). The use of the percent threshold to account for the intrinsic differences between species and a new calculation of the probability curve are introduced. The concentration providing the 50 % probability indicates that dogs are more sensitive than humans to QT-interval prolongation. However, based on the drug effect, a clear distinction between species cannot be made. An operational PK/PD model of agonism was used to investigate the relationship between effects on the hERG and QT-interval prolongation in dogs. The proposed analysis contributes to establish a translational relationship that could potentially reduce the need for thorough QT studies.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Moss AJ (1999) The QT interval and torsade de pointes. Drug Saf 21:5–10

    Article  CAS  PubMed  Google Scholar 

  2. Valentin J-P (2010) Reducing QT liability and proarrhythmic risk in drug discovery and development. Br J Pharmacol 159:5–11

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  3. Pollard CE, Abi Gerges N, Bridgland-Taylor MH, Easter A, Hammond TG, Valentin J-P (2010) An introduction to QT interval prolongation and non-clinical approaches to assessing and reducing risk. Br J Pharmacol 159:12–21

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Shah RR (2002) Drug-induced prolongation of the QT interval: regulatory dilemmas and implications for approval and labelling of a new chemical entity. Fundam Clin Pharmacol 16:147–156

    Article  CAS  PubMed  Google Scholar 

  5. Shah RR (2002) Drug-induced prolongation of the QT interval: why the regulatory concern? Fundam Clin Pharmacol 16:119–124

    Article  CAS  PubMed  Google Scholar 

  6. Shah RR (2002) Can pharmacogenetics help rescue drugs withdrawn from the market? Pharmacogenomics 2006:889–908

    Google Scholar 

  7. Darpo B (2001) Spectrum of drugs prolonging the QT interval and the incidence of torsades de pointes. Eur Heart J 3:70–80

    Article  Google Scholar 

  8. Yap YG, Camm AJ (2003) Drug induced QT prolongation and torsades de pointes. Heart 89:1363–1372

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  9. Redfern WS, Carlsson L, Davis AS, Lynch WG, MacKenzie I, Palethorpe S, Siegl PKS, Strang I, Sullivan AT, Wallis R, Camm AJ, Hammond TG (2003) Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development. Cardiovasc Res 58:32–45

    Article  CAS  PubMed  Google Scholar 

  10. Sarapa N, Britto MR (2008) Challenges of characterizing proarrhythmic risk due to QTc prolongation induced by nonadjuvant anticancer agents. Expert Opin Drug Saf 7:305–318

    Article  CAS  PubMed  Google Scholar 

  11. Rock EP, Finkle J, Fingert HJ, Booth BP, Garnett CE, Grant S, Justice RL, Kovacs RJ, Kowey PR, Rodriguez I, Sanhai WR, Strnadova C, Targum SL, Tsong Y, Uhl K, Stockbridge N (2009) Assessing proarrhythmic potential of drugs when optimal studies are infeasible. Am Heart J 157:827–836

    Article  CAS  PubMed  Google Scholar 

  12. ICH Expert Working Group. ICH Harmonised Tripartite Guideline (2005) E14 clinical evaluation of QT/QTc interval prolongation and proarrhythmic potential for non-antiarrhythmic drugs

  13. ICH Expert Working Group. ICH Harmonised Tripartite Guideline (2000) S7A Safety pharmacology studies for human pharmaceuticals

  14. ICH Expert Working Group. ICH Harmonised Tripartite Guideline (2005) S7B The nonclinical evaluation of the potential for delayed ventricular repolarization (QT interval prolongation) by human pharmaceuticals

  15. DiMasi JA, Hansen RW, Grabowski HG (2003) The price of innovation: new estimates of drug development costs. J Health Econ 22:151–185

    Article  PubMed  Google Scholar 

  16. Cavero I, Mestre M, Guillon JM, Crumb W (2000) Drugs that prolong QT interval as an unwanted effect: assessing their likelihood of inducing hazardous cardiac dysrhythmias. Expert Opin Pharmacother 1:947–973

    Article  CAS  PubMed  Google Scholar 

  17. Hammond TG, Carlsson L, Davis AS, Lynch WG, MacKenzie I, Redfern WS, Sullivan AT, Camm AJ (2001) Methods of collecting and evaluating non-clinical cardiac electrophysiology data in the pharmaceutical industry: results of an international survey. Cardiovasc Res 49:741–750

    Article  CAS  PubMed  Google Scholar 

  18. Netzer R, Ebneth A, Bischoff U, Pongs O (2001) Screening lead compounds for QT interval prolongation. Drug Discov Today 6:78–84

    Article  CAS  PubMed  Google Scholar 

  19. Ollerstam A, Visser SA, Duker G, Forsberg T, Persson AH, Nilsson LB, Bjorkman JA, Gabrielsson J, Al-Saffar A (2007) Comparison of the QT interval response during sinus and paced rhythm in conscious and anesthetized beagle dogs. J Pharmacol Toxicol Methods 56:131–144

    Article  CAS  PubMed  Google Scholar 

  20. Tornoe CW, Garnett CE, Wang Y, Florian J, Li M, Gobburu V (2010) Creation of a knowledge management system for QT analyses. J Clin Pharmacol 51:1035–1042

    Article  PubMed  Google Scholar 

  21. Florian JA, Tornoe CW, Brundage R, Parekh A, Garnett CE (2011) Population pharmacokinetic and concentration-QTc models for moxifloxacin: pooled analysis of 20 thorough QT studies. J Clin Pharmacol 51:1152–1162

    Article  CAS  PubMed  Google Scholar 

  22. Avelox, Bayer Healthcare, West Haven, CT http://www.accessdata.fda.gov/drugsatfda_docs/label/2010/021277s038lbl

  23. Haverkamp W, Kruesmann F, Fritsch A, van Veenhuyzen D, Arvis P (2012) Update on the cardiac safety of Moxifloxacin. Curr Drug Saf 7:149–163

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Chain ASY, Dubois VFS, Danhof M, Sturkenboom MCJM, Della Pasqua O (2013) Identifying the translational gap in the evaluation of drug-induced \(QT_c\) interval prolongation. Br J Clin Pharmacol 76:708–724

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  25. Dubois VFS, Yu H, Danhof M, Della Pasqua O (2015) Model-based evaluation of drug-induced QTc prolongation for compounds in early development. Br J Clin Pharmacol 79:148–161

    Article  CAS  PubMed  Google Scholar 

  26. Gotta V, Cools F, Van Ammel K, Gallacher DJ, Visser SAG, Sannajust F, Morissette P, Danhof M, van der Graaf PH (2015) Inter-study variability of preclinical in vivo safety studies and translational exposure-QTc relationships—a PKPD meta-analysis. Br J Pharmacol. doi:10.1111/bph.13218

    PubMed  Google Scholar 

  27. Siefert HM, Domdey-Bette A, Henninger K, Hucke F, Kohlsdorfer C, Stass HH (1999) Pharmacokinetics of the 8-methoxyquinolone, moxifloxacin: a comparison in humans and other mammalian species. J Antimicrob Chemother 43:69–76

    Article  CAS  PubMed  Google Scholar 

  28. Parkinson J, Visser SAG, Jarvis P, Pollard C, Valentin J-P, Yates JWT, Ewart L (2013) Translational pharmacokinetic-pharmacodynamic modeling of QTc effect in dog and human. J Pharmacol Toxicol 68:357–366

    Article  CAS  Google Scholar 

  29. Holzgrefe H, Ferber G, Champeroux P, Gill M, Honda M, Greiter-Wilke A, Baird T, Meyer O, Saulnier M (2014) Preclinical QT safety assessment: cross-species comparisons and human translation from an industry consortium. J Pharmacol Toxicol 69:61–101

    Article  CAS  Google Scholar 

  30. Chain ASY, Krudys KM, Danhof M, Della Pasqua O (2011) Assessing the probability of drug-induced QTc-interval prolongation during clinical drug development. Clin Pharmacol Ther 90:867–875

    Article  CAS  PubMed  Google Scholar 

  31. Beal S, Sheiner LB, Boeckmann A, Bauer RJ, NONMEM User’s Guides (1989–2009) Icon Development Solutions, Ellicott City, MD, USA

  32. Lunn DJ, Thomas A, Best N, Spiegelhalter DJ (2000) WinBUGS—a Bayesian modeling framework: concepts, structure and extensibility. Stat Comput 10:325–337

    Article  Google Scholar 

  33. Bauer RJ, Guzy S, Ng C (2007) A survey of population analysis methods and software for complex pharmacokinetic and pharmacodynamic models with examples. AAPS J 9:60–83

    Article  Google Scholar 

  34. Russu A, De Nicolao G, Poggesi I, Neve M, Iavarone L, Gomeni R (2008) Dose escalation studies: a comparison between NONMEM and a novel Bayesian tool. In: Population Approach Group in Europe 17th Meeting. Abstract 1339

  35. Neve M, Iavarone L, Petrone M, Gomeni R (2009) Assessment of NONMEM and WinBUGS performances when estimating power and sigmoid Emax models. In: Population Approach Group in Europe 18th Meeting. Abstract 1573

  36. Duffull SB, Kirkpatrick CMJ, Green B, Holford NHG (2005) Analysis of population pharmacokinetic data using NONMEM and WinBUGS. J Biopharm Stat 15:53–73

    Article  PubMed  Google Scholar 

  37. Bonate PL (2011) Pharmacokinetic-pharmacodynamic modeling and simulation. Springer, New York

    Book  Google Scholar 

  38. Black JW, Leff P (1983) Operational model of pharmacological agonism. Proc R Soc Lond 220:141–162

    Article  CAS  PubMed  Google Scholar 

  39. Jonker DM, Kenna LA, Leishman D, Wallis R, Milligan PA, Jonsson EN (2005) A pharmacokinetic-pharmacodynamic model for the quantitative prediction of dofetilide clinical QT prolongation from human ether-a-go-go-related gene current inhibition data. Clin Pharmacol Ther 77:572–582

    Article  CAS  PubMed  Google Scholar 

  40. Rowland M, Sheiner LB, Steimer JL (1985) Variability in drug therapy: description, estimation and control. Raven Press, New York

    Google Scholar 

  41. Piotrovsky V (2005) Pharmacokinetic-pharmacodynamic modeling in the data analysis and interpretation of drug-induced QT/QTc prolongation. AAPS J 7:609–624

    Article  Google Scholar 

  42. Pramanik D (2007) Principles of physiology. Academic Publishers, Kolkata

    Google Scholar 

  43. Spence S, Soper K, Hoe CM, Coleman J (1998) The heart rate-corrected QT interval in conscious beagle dogs: a formula based on analysis of covariance. Toxicol Sci 45:247–258

    Article  CAS  PubMed  Google Scholar 

  44. Development Core Team R (2014) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratory of Medical Biochemistry and Clinical Analysis, Ghent University, Ghent, Belgium

    Eleonora Marostica, Koen Boussery, Jan Van Bocxlaer & An Vermeulen

  2. Global Safety Pharmacology, Janssen R&D, Beerse, Belgium

    Karel Van Ammel, Ard Teisman & David Gallacher

  3. Model Based Drug Development, Janssen R&D, Beerse, Belgium

    Filip De Ridder & An Vermeulen

Authors
  1. Eleonora Marostica
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karel Van Ammel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ard Teisman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Koen Boussery
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jan Van Bocxlaer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Filip De Ridder
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. David Gallacher
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. An Vermeulen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eleonora Marostica.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Marostica, E., Van Ammel, K., Teisman, A. et al. Modelling of drug-induced QT-interval prolongation: estimation approaches and translational opportunities. J Pharmacokinet Pharmacodyn 42, 659–679 (2015). https://doi.org/10.1007/s10928-015-9434-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10928-015-9434-0

Keywords

Search

Navigation