Journals / EMU Journal of Pharmaceutical Sciences / 2026 / Volume: 9 Issue: 2

Formulation Development and In-Vitro-In-Vivo Correlation (IVIVC) Level A of Vonoprazan Tablets (20 mg) Using a Convolution-Based Method

Panna Thapa(Kathmandu University)0000-0003-4491-3656
Pages
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Publication Date
2026-09-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These results demonstrate acceptable correlation for all pharmacokinetics parameters indicating that the developed model has good predictive performance.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The present study aimed to develop a 20 mg Vonoprazan tablet formulation and a convolution-based Level A IVIVC model was developed using published in-vivo data.
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Key Findings & Data:High-performance Liquid Chromatography (HPLC) was used to analyze drug concentration.
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Conclusion & Impact:These results demonstrate acceptable correlation for all pharmacokinetics parameters indicating that the developed model has good predictive performance.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:vonoprazan · IVIVC · Dissolution

Abstract

The present study aimed to develop a 20 mg Vonoprazan tablet formulation and a convolution-based Level A IVIVC model was developed using published in-vivo data. Various hits and trials were done to obtain desired release profiles by changing concentration of super disintegrants, hardness of tablets and dissolution Speeds. High-performance Liquid Chromatography (HPLC) was used to analyze drug concentration. Pharmacokinetic parameters such as Maximum Plasma Drug Concentration (Cmax), Time to reach maximum concentration (Tmax) and Area Under Curve (AUC) were predicted using convolution method based on in-vitro data. The predicted pharmacokinetic parameters: Cmax = 16.61 ng/ml, Tmax = 1.98 hr, and AUC₀–∞ = 187.14 ng·h/ml showed close agreement with observed values Cmax = 18.2 ng/ml, Tmax = 1.98 hr, AUC₀–₂₄ = 160.8 ng·h/ml, AUC₀–∞ = 179.3 ng·h/ml. The %PE for Cmax is 8.74%, AUC₀–∞ is 4.37% and Tmax is 1.0 %. These results demonstrate acceptable correlation for all pharmacokinetics parameters indicating that the developed model has good predictive performance. The developed formulation demonstrated a close correlation between in vitro dissolution and in-vivo absorption profiles, confirming the predictability of the model. This study supports the potential of convolution-based modeling as a reliable approach for formulation optimization and regulatory biowaiver justification.

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Cite This Article

Bhattarai, B., Budhathoki, U., Thapa, P. (2026). Formulation Development and In-Vitro-In-Vivo Correlation (IVIVC) Level A of Vonoprazan Tablets (20 mg) Using a Convolution-Based Method. EMU Journal of Pharmaceutical Sciences, Volume: 9 Issue: 2. https://doi.org/10.54994/emujpharmsci.1943756

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References (23)

  1. Echizen H (2016). The First-in-Class Potassium-Competitive Acid Blocker, Venireman Fumarate: Pharmacokinetic and Pharmacodynamic Considerations. Clin Pharmacokinetics 55(4): 409–418.
  2. Vinayagam S, Mittal N, Kaushal J (2024). Vonoprazan: A promising advancement in proton pump inhibitor therapy. Int J Basic Clin Pharmacol 13(4): 573–579.
  3. Sachs G, Shin JM, Vagin O, Lambrecht N, Yakubov I, et al. (2007). The gastric H, K ATPase as a drug target: past, present, and future. J Clin Gastroenterol 41(Suppl. 2): 226–S242.
  4. Shin JM, Sachs G (2009). Long-lasting inhibitors of the gastric H+, K+-ATPase. Expert Rev Clin Pharmacol 2(5): 461–468.
  5. Savarino E, Martinucci I, Furnari M, Romana C, Pellegatta G. et al. (2016). Vonoprazan for treatment of gastroesophageal reflux: Pharmacodynamic and pharmacokinetic considerations. Expert Opin Drug Metab Toxicol 12(11): 1333–1341.
  6. Hori Y, Imanishi A, Matsukawa J, Tsukimi Y, Nishida H, et al. (2010). 1-[5-(2-Fluorophenyl)-1-(pyridin-3-ylsulfonyl)-1H-pyrrol-3-yl]-N-methylmethanamine Monofumarate (TAK-438), a Novel and Potent Potassium-Competitive Acid Blocker for the Treatment of Acid-Related Diseases. J Pharmacol Exp Ther 335(1): 231–238.
  7. Oshima T, Miwa H (2018). Potent Potassium-Competitive Acid Blockers: A New Era for the Treatment of Acid-Related Diseases. J Neurogastroenterol Motil 24: 334–344.
  8. Liqiu M, Zhao B, Huang F (2017). Vonoprazan fumarate composition and preparation method thereof. https://patents.google.com/patent/WO2018133009A1/en. Accessed 10 March 2026.
  9. Takeda Pharmaceutical Co. Ltd. (2014). https://www.pmda.go.jp/files/000211075.pdf. Accessed 10 March 2026.
  10. Jenkins H, Sakurai Y, Nishimura A, Okamoto H, Hibberd M, et al. (2015). Randomised clinical trial: Safety, tolerability, pharmacokinetics and pharmacodynamics of repeated doses of TAK-438 (vonoprazan), a novel potassium-competitive acid blocker, in healthy male subjects. Aliment Pharmacol Ther 41(7): 636–648.
  11. Otake K, Sakurai Y, Nishida H, Fukui H, Tagawa Y, et al. (2016). Characteristics of the Novel Potassium-Competitive Acid Blocker Vonoprazan Fumarate (TAK-438). Advances in Therapy 33: 1140–1157.
  12. Sugano K (2018). Vonoprazan fumarate, a novel potassium-competitive acid blocker, in the management of gastroesophageal reflux disease: Safety and clinical evidence to date. Ther Adv Gastroenterol 11.
  13. USFDA. (1997). Extended-release solid dosage forms: Development, evaluation and application of in vitro/in vivo correlations. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/extended-release-oral-dosage-forms-development-evaluation-and-application-vitroin-in-vivo-correlations. Accessed 10 March 2026.
  14. Taha NF, Emara LH (2022). Convolution- and Deconvolution-Based Approaches for Prediction of Pharmacokinetic Parameters of Diltiazem Extended-Release Products in Flow-Through Cell Dissolution Tester. AAPS PharmSciTech 23: 202.
  15. Nainar S, Rajiah K, Angamuthu S, Prabakaran D, Kasibhatta R (2012). Biopharmaceutical Classification System in In Vitro/In Vivo Correlation: Concept and Development Strategies in Drug Delivery. Trop J Pharm Res 11(2): 201–210.
  16. Kaur P, Jiang X, Duan J, Stier E (2015). Applications of In Vitro-In Vivo Correlations in Generic Drug Development: Case Studies. AAPS J 17(4): 1035–1039.
  17. Gillespie WR (1997). Convolution-based approaches for in vivo-in vitro correlation modeling. Adv Exp Med Biol 423: 53–65.
  18. Ghosh A, Bhaumik UK, Bose A, Mandal U, Gowda V, et al. (2008). Extended Release Dosage Form of Glipizide: Development and Validation of a Level A in Vitro-in Vivo Correlation. Biol Pharm Bull 31(10): 1946–1951.
  19. Mulford DJ, Leifke E, Hibberd M, Cowden CW, et al. (2021). The Effect of Food on the Pharmacokinetics of the Potassium-Competitive Acid Blocker Vonoprazan. Clin Pharmacol Drug Dev 11(2): 278–284.
  20. Davanço MG., Campos, D. R., Dalmora, S. L., & Storpirtis, S. (2020). A twenty-year overview of the scientific literature on in vitro–in vivo correlation. International Journal of Pharmaceutics 586: 119713.
  21. Cardot JM, Beyssac E, Alric M (2007). In vitro–in vivo correlation: Importance of dissolution in IVIVC. European Journal of Pharmaceutical Sciences 30(2): 97–116.
  22. Kaur P, Jiang X, Duan J, Stier E (2015). Applications of in vitro–in vivo correlations in generic drug development: Case studies. The AAPS Journal 17(4): 1035–1039.
  23. U.S. Food and Drug Administration. (1997). Extended release oral dosage forms: Development, evaluation, and application of in vitro/in vivo correlations: Guidance for industry. U.S. Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research. FDA Guidance for Industry: Extended Release Oral Dosage Forms—Development, Evaluation, and Application of In Vitro/In Vivo Correlations