Skip to main content
SpringerLink
Log in

Comment on: “A Physiologically Based Pharmacokinetic Drug-Disease Model to Predict Carvedilol Exposure in Adult and Paediatric Heart Failure Patients by Incorporating Pathophysiological Changes in Hepatic and Renal Blood”

  • Letter to the Editor
  • Published:
Clinical Pharmacokinetics Aims and scope Submit manuscript

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

References

  1. Benowitz NL, Meister W. Pharmacokinetics in patients withcardiac failure. Clin Pharmacokinet. 1976;1(6):389–405.

    Article  PubMed  CAS  Google Scholar 

  2. Shammas FV, Dickstein K. Clinical pharmacokinetics in heart failure: an updated review. Clin Pharmacokinet. 1988;15(2):94–113.

    Article  PubMed  CAS  Google Scholar 

  3. Ogawa R, Stachnik JM, Echizen H. Clinical pharmacokinetics of drugs in patients with heart failure: an update (part 1, drugs administered intravenously). Clin Pharmacokinet. 2013;52(3):169–85.

    Article  PubMed  CAS  Google Scholar 

  4. Ogawa R, Stachnik JM, Echizen H. Clinical pharmacokinetics of drugs in patients with heart failure: an update (part 2, drugs administered orally). Clin Pharmacokinet. 2014;53(12):1083–114.

    Article  PubMed  CAS  Google Scholar 

  5. Rasool MF, Khalil F, Läer S. A physiologically based pharmacokinetic drug-disease model to predict carvedilol exposure in adult and paediatric heart failure patients by incorporating pathophysiological changes in hepatic and renal blood flows. Clin Pharmacokinet. 2015;54(9):943–62.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  6. Leithe ME, Margorien RD, Hermiller JB, et al. Relationship between central hemodynamics and regional blood flow in normal subjects and in patients with congestive heart failure. Circulation. 1984;69(1):57–64.

    Article  PubMed  CAS  Google Scholar 

  7. Muller AF, Batin P, Evans S, et al. Regional blood flow in chronic heart failure: the reason for the lack of correlation between patients’ exercise tolerance and cardiac output? Br Heart J. 1992;67(6):478–81.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  8. Leier CV. Regional blood flow in human congestive heart failure. Am Heart J. 1992;124(3):726–38.

    Article  PubMed  CAS  Google Scholar 

  9. Peters SA. Physiologically-based pharmacokinetic (PBPK) modeling and simulations: principles, methods, and applications in the pharmaceutical industry. New York: Wiley; 2012.

    Book  Google Scholar 

  10. Peters SA. Evaluation of a generic physiologically based pharmacokinetic model for line shape analysis. Clin Pharmacokinet. 2008;47(4):261–75.

    Article  PubMed  CAS  Google Scholar 

  11. Nestorov I. Whole body pharmacokinetic models. Clin Pharmacokinet. 2003;42(10):883–908.

    Article  PubMed  CAS  Google Scholar 

  12. Carlton LD, Pollack GM, Brouwer KL. Physiologic pharmacokinetic modeling of gastrointestinal blood flow as a rate-limiting step in the oral absorption of digoxin: implications for patients with congestive heart failure receiving epoprostenol. J Pharm Sci. 1996;85(5):473–7.

    Article  PubMed  CAS  Google Scholar 

  13. Lee RE, Aldoori MI. Blood flow to the limbs. In: Salmasi AA, Iskandrian AS, editors. Cardiac output and regional blood flow in health and disease. The Netherlands: Kluwer Academic Publishers; 1993. p. 505–22.

    Chapter  Google Scholar 

  14. Johnson TN, Rostami-Hodjegan A, Tucker GT. Prediction of the clearance of eleven drugs and associated variability in neonates, infants and children. Clin Pharmacokinet. 2006;45(9):931–56.

    Article  PubMed  CAS  Google Scholar 

  15. Johnson TN, Boussery K, Rowland-Yeo K, et al. A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance. Clin Pharmacokinet. 2010;49(3):189–206.

    Article  PubMed  CAS  Google Scholar 

  16. Edginton AN, Schmitt W, Willmann S. Development and evaluation of a generic physiologically based pharmacokinetic model for children. Clin Pharmacokinet. 2006;45(10):1013–34.

    Article  PubMed  CAS  Google Scholar 

  17. Edginton AN, Willmann S. Physiology-based simulations of a pathological condition: prediction of pharmacokinetics in patients with liver cirrhosis. Clin Pharmacokinet. 2008;47(11):743–52.

    Article  PubMed  Google Scholar 

  18. Yang J, Jamei M, Yeo KR, et al. Prediction of intestinal first-pass drug metabolism. Curr Drug Metab. 2007;8(7):676–84.

    Article  PubMed  CAS  Google Scholar 

  19. Jamei M, Dickinson GL, Rostami-Hodjegan A. A framework for assessing inter-individual variability in pharmacokinetics using virtual human populations and integrating general knowledge of physical chemistry, biology, anatomy, physiology and genetics: a tale of ‘bottom-up’ vs ‘top-down’ recognition of covariates. Drug Metab Pharmacokinet. 2009;24(1):53–75.

    Article  PubMed  CAS  Google Scholar 

  20. Jamei M, Turner D, Yang J, et al. Population-based mechanistic prediction of oral drug absorption. AAPS J. 2009;11(2):225–37.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  21. Crouthamel WG, Diamond L, Dittert LW, et al. Drug absorption VII: influence of mesenteric blood flow on intestinal drug absorption in dogs. J Pharm Sci. 1975;64(4):664–71.

    Article  PubMed  CAS  Google Scholar 

  22. Crouthamel W, Doluisio JT, Johnson RE, et al. Effect of mesenteric blood flow on intestinal drug absorption. J Pharm Sci. 1970;59(6):878–9.

    Article  PubMed  CAS  Google Scholar 

  23. Winne D. Influence of blood flow on intestinal absorption of xenobiotics. Pharmacology. 1980;21(1):1–15.

    Article  PubMed  CAS  Google Scholar 

  24. de Koning BAE, Mooij M, Johnson TN, et al. Developmental changes in the processes governing oral drug absorption. In: Bar-Shalom D, Rose K, editors. Pediatric formulations: a road map. New York: Springer; 2014. p. 25–42.

    Chapter  Google Scholar 

  25. Yu G, Zheng QS, Li GF. Similarities and differences in gastrointestinal physiology between neonates and adults: a physiologically based pharmacokinetic modeling perspective. AAPS J. 2014;16(6):1162–6.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  26. Maharaj AR, Edginton AN, Fotaki N. Assessment of age-related changes in pediatric gastrointestinal solubility. Pharm Res. doi:10.1007/s11095-015-1762-7. (Epub 29 July 2015).

  27. Challacombe DN, Edkins S, Brown GA. Duodenal bile acids in infancy. Arch Dis Child. 1975;50(11):837–43.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  28. Zhao P, Rowland M, Huang SM. Best practice in the use of physiologically based pharmacokinetic modeling and simulation to address clinical pharmacology regulatory questions. Clin Pharmacol Ther. 2012;92(1):17–20.

    Article  PubMed  CAS  Google Scholar 

  29. Sandek A, Swidsinski A, Schroedl W, et al. Intestinal blood flow in patients with chronic heart failure: a link with bacterial growth, gastrointestinal symptoms, and cachexia. J Am Coll Cardiol. 2014;64(11):1092–102.

    Article  PubMed  Google Scholar 

  30. Gruhn N, Larsen FS, Boesgaard S, et al. Cerebral blood flow in patients with chronic heart failure before and after heart transplantation. Stroke. 2001;32(11):2530–3.

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

Guo Yu would like to thank Simcyp Limited for providing academic licenses for the Simcyp Simulator.

Author information

Authors and Affiliations

  1. Center for Drug Clinical Research, Shanghai University of Chinese Medicine, No. 1200 Cailun Road, 201203, Shanghai, China

    Guo-Fu Li, Shui-Yu Zhao & Qing-Shan Zheng

  2. Yangzhou Maternal and Child Care Service Center, Yangzhou University, Yangzhou, China

    Xiao Gu

  3. Laboratory of Pharmacogenomics and Pharmacokinetic Research, Subei People’s Hospital, Yangzhou, China

    Guo Yu

  4. Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, China

    Guo Yu

Authors
  1. Guo-Fu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiao Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guo Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shui-Yu Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qing-Shan Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Guo-Fu Li or Qing-Shan Zheng.

Ethics declarations

Conflicts of interest

Guo-Fu Li, Xiao Gu, Guo Yu, Shui-Yu Zhao, and Qing-Shan Zheng have no conflicts of interest to declare that are directly relevant to the content of this letter.

Funding

No sources of funding were used to assist in the preparation of this letter.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, GF., Gu, X., Yu, G. et al. Comment on: “A Physiologically Based Pharmacokinetic Drug-Disease Model to Predict Carvedilol Exposure in Adult and Paediatric Heart Failure Patients by Incorporating Pathophysiological Changes in Hepatic and Renal Blood”. Clin Pharmacokinet 55, 133–137 (2016). https://doi.org/10.1007/s40262-015-0348-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40262-015-0348-1

Keywords

Search

Navigation