Skip to main content

Concentration Profiles of Carvedilol: A Comparison Between In Vitro Transfer Model and Dissolution Testing

Journal of Pharmaceutical Innovation volume 14, pages 123–131 (2019)Cite this article

Abstract

Purpose

The study aims to investigate the transfer behavior of the weakly basic BCS class II model drug carvedilol from the stomach to the small intestine and compare the concentration profiles of carvedilol that were determined during the in vitro transfer model and dissolution testing.

Methods

An in vitro transfer model, previously introduced by Kostewicz et al., was used in this study. A donor phase of simulated gastric fluid was used to predissolve Dilatrend® tablet (25 mg carvedilol). Media that simulate and cover the physiological pH and buffer capacity ranges of the intestinal fluid were used as acceptor phases. pH measurements were reported to investigate the effect of addition of donor phase containing predissolved carvedilol on lowering the pH of the acceptor media. The f2 similarity factor was used to compare the concentration profiles of carvedilol determined during the in vitro transfer model.

Results

Carvedilol was completely dissolved in all tested acceptor phases, resulted in no precipitation. The buffering capacity of the acceptor phase plays an important role in determining its pH. A discrepancy was found between the concentrations of carvedilol in all tested acceptor phases obtained using the transfer model and those reported using dissolution apparatus II in corresponding media.

Conclusions

Results showed that dissolution testing using apparatus II might not be sufficient to predict its transfer from the stomach into the small intestine and that the in vitro transfer model may be more effective at mimicking the conditions in the gastrointestinal tract.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Hamed R, Awadallah A, Sunoqrot S, Tarawneh O, Nazzal S, AlBaraghthi T, et al. pH-dependent solubility and dissolution behavior of carvedilol—case example of a weakly basic BCS class II drug. AAPS PharmSciTech. 2016;17(2):418–26.

    Article  CAS  PubMed  Google Scholar 

  2. Al Ameri MN, Nayuni N, Kumar KA, Perrett D, Tucker A, Johnston A. The differences between the branded and generic medicines using solid dosage forms: in-vitro dissolution testing. Results Pharma Sci. 2012;2:1–8.

    Article  CAS  PubMed  Google Scholar 

  3. Tsume Y, Takeuchi S, Matsui K, Amidon GE, Amidon GL. In vitro dissolution methodology, mini-gastrointestinal simulator (mGIS), predicts better in vivo dissolution of a weak base drug, dasatinib. Eur J Pharm Sci. 2015;76:203–12.

    Article  CAS  PubMed  Google Scholar 

  4. Kou D, Dwaraknath S, Fischer Y, Nguyen D, Kim M, Yiu H, et al. Biorelevant dissolution models for a Weak Base to facilitate formulation development and overcome reduced bioavailability caused by Hypochlordyria or Achlorhydria. Mol Pharm. 2017;14(10):3577–87.

    Article  CAS  PubMed  Google Scholar 

  5. Klein S, Buchanan NL, Buchanan CM. Miniaturized transfer models to predict the precipitation of poorly soluble weak bases upon entry into the small intestine. AAPS PharmSciTech. 2012;13(4):1230–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Kostewicz ES, Wunderlich M, Brauns U, Becker R, Bock T, Dressman JB. Predicting the precipitation of poorly soluble weak bases upon entry in the small intestine. J Pharm Pharmacol. 2004;56(1):43–51.

    Article  CAS  PubMed  Google Scholar 

  7. Ruff A, Fiolka T, Kostewicz ES. Prediction of ketoconazole absorption using an updated in vitro transfer model coupled to physiologically based pharmacokinetic modelling. Eur J Pharm Sci. 2017;100:42–55.

    Article  CAS  PubMed  Google Scholar 

  8. Okumu A, DiMaso M, Löbenberg R. Computer simulations using GastroPlus™ to justify a biowaiver for etoricoxib solid oral drug products. Eur J Pharm Biopharm. 2009;72(1):91–8.

    Article  CAS  PubMed  Google Scholar 

  9. Tsume Y, Amidon G, Takeuchi S. Dissolution effect of gastric and intestinal pH fora BCS class II drug, pioglitazone: new in vitro dissolution system to predict in vivo dissolution. J Bioequiv Availab. 2013;5(6):224–7.

    Article  CAS  Google Scholar 

  10. Wagner C, Jantratid E, Kesisoglou F, Vertzoni M, Reppas C, Dressman JB. Predicting the oral absorption of a poorly soluble, poorly permeable weak base using biorelevant dissolution and transfer model tests coupled with a physiologically based pharmacokinetic model. Eur J Pharm Biopharm. 2012;82(1):127–38.

    Article  CAS  PubMed  Google Scholar 

  11. Kambayashi A, Yasuji T, Dressman JB. Prediction of the precipitation profiles of weak base drugs in the small intestine using a simplified transfer (“dumping”) model coupled with in silico modeling and simulation approach. Eur J Pharm Biopharm. 2016;103:95–103.

    Article  CAS  PubMed  Google Scholar 

  12. Zhong Y, Jing G, Tian B, Huang H, Zhang Y, Gou J, et al. Supersaturation induced by Itraconazole/Soluplus® micelles provided high GI absorption in vivo. Asian J Pharm Sci. 2016;11(2):255–64.

    Article  Google Scholar 

  13. Vertzoni M, Dressman J, Butler J, Hempenstall J, Reppas C. Simulation of fasting gastric conditions and its importance for the in vivo dissolution of lipophilic compounds. Eur J Pharm Biopharm. 2005;60(3):413–7.

    Article  CAS  PubMed  Google Scholar 

  14. Klein S, Wempe MF, Zoeller T, Buchanan NL, Lambert JL, Ramsey MG, et al. Improving glyburide solubility and dissolution by complexation with hydroxybutenyl-beta-cyclodextrin. J Pharm Pharmacol. 2009;61(1):23–30.

    Article  CAS  PubMed  Google Scholar 

  15. Hamed R, AlJanabi R, Sunoqrot S, Abbas A. The effect of pH, buffer capacity and ionic strength on quetiapine fumarate release from matrix tablets prepared using two different polymeric blends. Drug Dev Ind Pharm. 2017:1–13.

  16. Dressman JB, Amidon GL, Reppas C, Shah VP. Dissolution testing as a prognostic tool for oral drug absorption: immediate release dosage forms. Pharm Res. 1998;15(1):11–22.

    Article  CAS  PubMed  Google Scholar 

  17. Klein S, Rudolph M, Dressman J. Drug release characteristics of different mesalazine products using USP apparatus 3 to simulate passage through the GI tract. Dissolut Technol. 2002;9:6–12.

    Article  Google Scholar 

  18. Marques MRC, Loebenberg R, Almukainzi M. Simulated biological fluids with possible application in dissolution testing. Dissolut Technol. 2011;18(3):15–28.

    Article  CAS  Google Scholar 

  19. Asare-Addo K, Conway BR, Larhrib H, Levina M, Rajabi-Siahboomi AR, Tetteh J, et al. The effect of pH and ionic strength of dissolution media on in-vitro release of two model drugs of different solubilities from HPMC matrices. Colloid Surface B. 2013;111:384–91.

    Article  CAS  Google Scholar 

  20. Costa P, Manuel J, Lobo S. Modeling and comparison of dissolution profiles. Eur J Pharm Sci. 2001;13(2):123–33.

    Article  CAS  Google Scholar 

  21. Health UDo, Services H, Food, Administration D. Dissolution Testing of Immediate Release Solid Oral Dosage Forms, Guidance for Industry. Center for Drug Evaluation and Research (CDER), US government printing office, Washington, DC, USA. 1997.

  22. Gowthamarajan K, Singh SK. Dissolution testing for poorly soluble drugs: a continuing perspective. Dissolut Technol. 2010;17(3):24–32.

    Article  CAS  Google Scholar 

  23. Tsume Y, Mudie DM, Langguth P, Amidon GE, Amidon GL. The biopharmaceutics classification system: subclasses for in vivo predictive dissolution (IPD) methodology and IVIVC. Eur J Pharm Sci. 2014;57:152–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hsieh Y-L, Ilevbare GA, Van Eerdenbrugh B, Box KJ, Sanchez-Felix MV, Taylor LS. pH-induced precipitation behavior of weakly basic compounds: determination of extent and duration of supersaturation using potentiometric titration and correlation to solid state properties. Pharm Res. 2012;29(10):2738–53.

    Article  CAS  PubMed  Google Scholar 

  25. Stillhart C, Dürr D, Kuentz M. Toward an improved understanding of the precipitation behavior of weakly basic drugs from oral lipid-based formulations. J Pharm Sci. 2014;103(4):1194–203.

    Article  CAS  PubMed  Google Scholar 

  26. Kourentas A, Vertzoni M, Stavrinoudakis N, Symillidis A, Brouwers J, Augustijns P, et al. An in vitro biorelevant gastrointestinal transfer (BioGIT) system for forecasting concentrations in the fasted upper small intestine: design, implementation, and evaluation. Eur J Pharm Sci. 2016;82:106–14.

    Article  CAS  PubMed  Google Scholar 

  27. McCarthy CA, Faisal W, O'shea JP, Murphy C, Ahern RJ, Ryan KB, et al. In vitro dissolution models for the prediction of in vivo performance of an oral mesoporous silica formulation. J Control Release. 2017;250:86–95.

    Article  CAS  PubMed  Google Scholar 

  28. Loftsson T, Vogensen SB, Desbos C, Jansook P. Carvedilol: solubilization and cyclodextrin complexation: a technical note. AAPS PharmSciTech. 2008;9(2):425–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Incecayir T. The effects of surfactants on the solubility and dissolution profiles of a poorly water-soluble basic drug, carvedilol. Die Pharmazie-an international. J Pharm Sci. 2015;70(12):784–90.

    CAS  Google Scholar 

  30. Tsume Y, Langguth P, Garcia-Arieta A, Amidon GL. In silico prediction of drug dissolution and absorption with variation in intestinal pH for BCS class II weak acid drugs: ibuprofen and ketoprofen. Biopharm Drug Dispos. 2012;33(7):366–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This project was financially supported by the Deanship of Academic Research and Graduate Studies at Al-Zaytoonah University of Jordan.

Author information

Authors and Affiliations

  1. Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan, P.O. Box 130, Amman, 11733, Jordan

    Rania Hamed & Areej Kamal

Authors
  1. Rania Hamed
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Areej Kamal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rania Hamed.

Electronic Supplementary Material

Fig. 1S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in acetate buffer. Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 21 kb)

High Resolution image (TIF 29 kb)

Fig. 2S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in blank FaSSIF. Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 23 kb)

High Resolution image (TIF 29 kb)

Fig. 3S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in blank FeSSIF. Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 22 kb)

High Resolution image (TIF 29 kb)

Fig. 4S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in SIFsp. Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 22 kb)

High Resolution image (TIF 29 kb)

Fig. 5S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in water. Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 20 kb)

High Resolution image (TIF 28 kb)

Fig. 6S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in phosphate buffer 6.25 mM (pH 6.8). Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 22 kb)

High Resolution image (TIF 29 kb)

Fig. 7S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in phosphate buffer 12.5 mM (pH 6.8). Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 23 kb)

High Resolution image (TIF 29 kb)

Fig. 8S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in phosphate buffer 25 mM (pH 6.8). Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 23 kb)

High Resolution image (TIF 29 kb)

Fig. 9S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in phosphate buffer 50 mM (pH 6.8). Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 22 kb)

High Resolution image (TIF 28 kb)

Fig. 10S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in phosphate buffer 100 mM (pH 6.8). Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 22 kb)

High Resolution image (TIF 28 kb)

Fig. 11S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in phosphate buffer 100 mM (pH 7.2). Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 22 kb)

High Resolution image (TIF 28 kb)

Fig. 12S

CTransfer and CDissolution profiles of carvedilol from Dilatrend® tablets in phosphate buffer 100 mM (pH 7.8). Data are represented as the mean ± SD (CTransfer, n = 3 and CDissolution, n = 6) (PNG 20 kb)

High Resolution image (TIF 26 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hamed, R., Kamal, A. Concentration Profiles of Carvedilol: A Comparison Between In Vitro Transfer Model and Dissolution Testing. J Pharm Innov 14, 123–131 (2019). https://doi.org/10.1007/s12247-018-9337-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12247-018-9337-x

Keywords

  • Transfer model
  • Weak base
  • BCS class II
  • Dissolution
  • Gastrointestinal fluid
  • Carvedilol