Skip to main content

Understanding the Oral Absorption of Irbesartan Using Biorelevant Dissolution Testing and PBPK Modeling

Abstract

Poorly soluble weak bases form a significant proportion of the drugs available in the market thereby making it imperative to understand their absorption behavior. This work aims to mechanistically understand the oral absorption behavior for a weakly basic drug, Irbesartan (IRB), by investigating its pH dependent solubility, supersaturation, and precipitation behavior. Simulations performed using the equilibrium solubility could not accurately predict oral absorption. A multi-compartmental biorelevant dissolution testing model was used to evaluate dissolution in the stomach and duodenal compartment and mimic oral drug administration. This model exhibited sustained intestinal supersaturation (2–4-fold) even upon varying flow rates (4 mL/min, 7 mL/min, and mono-exponential transfer) from gastric to intestinal compartment. Simulation of oral absorption using GastroPlus™ and dissolution data collectively predicted plasma exposure with higher accuracy (% prediction error values within ± 15%), thereby indicating that multi-compartment dissolution testing enabled an improved prediction for oral pharmacokinetics of Irbesartan. Additionally, precipitates obtained in the intestinal compartment were characterized to determine the factors underlying intestinal supersaturation of Irbesartan. The solid form of these precipitates was amorphous with considerable particle size reduction. This indicated that following gastric transit, precipitate formation in the amorphous form coupled with an approximately 10 times particle size reduction could be potential factors leading to the generation and sustenance of intestinal drug supersaturation.

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

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

Abbreviations

ACAT:

Advanced compartmental absorption and transit model

API:

Active pharmaceutical ingredient

AUC:

Area under the curve

BCS:

Biopharmaceutics classification system

Cmax :

Maximal concentration

CR:

Complete release

DSC:

Differential scanning calorimetry

G+:

GastroPlus™

GIT:

Gastrointestinal tract

HPLC:

High pressure liquid chromatography

IRB:

Irbesartan

IVIVC:

In vitro in vivo correlation

IVISIV:

In vitro-in silico-in vivo

Ksp :

Solubility product constant

PBPK:

Physiologically based pharmacokinetics

PK:

Pharmacokinetics

pKa :

pH corresponding to 50% ionization

PE:

Prediction error

PXRD:

Powder X-ray diffraction

S:

Solubility (ionized + unionized form)

SO :

Intrinsic solubility

SEM:

Scanning electron microscopy

SGF:

Simulated gastric fluid

SIF:

Simulated intestinal fluid

Tg :

Glass transition temperature

Tm :

Melting point

Tmax :

Time of maximal concentration

USP:

United States Pharmacopeia

Vd :

Volume of distribution

References

  1. 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.

    CAS  PubMed  Google Scholar 

  2. Chiang P-C, La H, Zhang H, Wong H. Systemic concentrations can limit the oral absorption of poorly soluble drugs: an investigation of non-sink permeation using physiologically based pharmacokinetic modeling. Mol Pharm. 2013;10(11):3980–8.

    CAS  PubMed  Google Scholar 

  3. Williams HD, Trevaskis NL, Charman SA, Shanker RM, Charman WN, Pouton CW, et al. Strategies to address low drug solubility in discovery and development. Pharmacol Rev. 2013;65(1):315–499.

    PubMed  Google Scholar 

  4. Ottaviani G, Gosling DJ, Patissier C, Rodde S, Zhou L, Faller B. What is modulating solubility in simulated intestinal fluids? Eur J Pharm Sci. 2010;41(3):452–7.

    CAS  PubMed  Google Scholar 

  5. Bevernage J, Brouwers J, Brewster ME, Augustijns P. Evaluation of gastrointestinal drug supersaturation and precipitation: strategies and issues. Int J Pharm. 2013;453(1):25–35.

    CAS  PubMed  Google Scholar 

  6. Otsuka K, Shono Y, Dressman J. Coupling biorelevant dissolution methods with physiologically based pharmacokinetic modelling to forecast in-vivo performance of solid oral dosage forms. J Pharm Pharmacol. 2013;65(7):937–52.

    CAS  PubMed  Google Scholar 

  7. Taupitz T, Dressman JB, Klein S. In vitro tools for evaluating novel dosage forms of poorly soluble, weakly basic drugs: case example ketoconazole. J Pharm Sci. 2013;102(10):3645–52.

    CAS  PubMed  Google Scholar 

  8. Frank KJ, Locher K, Zecevic DE, Fleth J, Wagner KG. In vivo predictive mini-scale dissolution for weak bases: advantages of pH-shift in combination with an absorptive compartment. Eur J Pharm Sci. 2014;61:32–9.

    CAS  PubMed  Google Scholar 

  9. Kostewicz ES, Abrahamsson B, Brewster M, Brouwers J, Butler J, Carlert S, et al. In vitro models for the prediction of in vivo performance of oral dosage forms. Eur J Pharm Sci. 2014;57:342–66.

    CAS  PubMed  Google Scholar 

  10. Takeuchi S, Tsume Y, Amidon GE, Amidon GL. Evaluation of a three compartment in vitro gastrointestinal simulator dissolution apparatus to predict in vivo dissolution. J Pharm Sci. 2014;103(11):3416–22.

    CAS  PubMed  Google Scholar 

  11. Berlin M, Ruff A, Kesisoglou F, Xu W, Wang MH, Dressman JB. Advances and challenges in PBPK modeling–analysis of factors contributing to the oral absorption of atazanavir, a poorly soluble weak base. Eur J Pharm Biopharm. 2015;93(1):267–80.

    CAS  PubMed  Google Scholar 

  12. 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(1):203–12.

    CAS  PubMed  Google Scholar 

  13. 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.

    CAS  PubMed  Google Scholar 

  14. Bhattachar SN, Perkins EJ, Tan JS, Burns LJ. Effect of gastric pH on the pharmacokinetics of a bcs class II compound in dogs: utilization of an artificial stomach and duodenum dissolution model and gastroplus,™ simulations to predict absorption. J Pharm Sci. 2011;100(11):4756–65.

    CAS  PubMed  Google Scholar 

  15. Psachoulias D, Vertzoni M, Goumas K, Kalioras V, Beato S, Butler J, et al. Precipitation in and supersaturation of contents of the upper small intestine after administration of two weak bases to fasted adults. Pharm Res. 2011;28(12):3145–58.

    CAS  PubMed  Google Scholar 

  16. Carlert S, Åkesson P, Jerndal G, Lindfors L, Lennernäs H, Abrahamsson B. In vivo dog intestinal precipitation of mebendazole: a basic BCS class II drug. Mol Pharm. 2012;9(10):2903–11.

    CAS  PubMed  Google Scholar 

  17. 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Peters SA. Physiological Model for Absorption. In: Physiologically-based pharmacokinetic (PBPK) modeling and simulations: principles, methods, and applications in the pharmaceutical industry. Hoboken: Wiley; 2012. p. 17–84.

    Google Scholar 

  19. Psachoulias D, Vertzoni M, Butler J, Busby D, Symillides M, Dressman J, et al. An in vitro methodology for forecasting luminal concentrations and precipitation of highly permeable lipophilic weak bases in the fasted upper small intestine. Pharm Res. 2012;29(12):3486–98.

    CAS  PubMed  Google Scholar 

  20. Thelen K, Coboeken K, Willmann S, Dressman JB, Lippert J. Evolution of a detailed physiological model to simulate the gastrointestinal transit and absorption process in humans, part II: extension to describe performance of solid dosage forms. J Pharm Sci. 2012;101(3):1267–80.

    CAS  PubMed  Google Scholar 

  21. 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.

    CAS  PubMed  Google Scholar 

  22. Dokoumetzidis A, Kalantzi L, Fotaki N. Predictive models for oral drug absorption: from in silico methods to integrated dynamical models. Expert Opin Drug Metab Toxicol. 2007;3(4):491–505.

    CAS  PubMed  Google Scholar 

  23. Zhou R, Moench P, Heran C, Lu X, Mathias N, Faria TN, et al. pH-dependent dissolution in vitro and absorption in vivo of weakly basic drugs: development of a canine model. Pharm Res. 2005;22(2):188–92.

    CAS  PubMed  Google Scholar 

  24. Koziolek M, Garbacz G, Neumann M, Weitschies W. Simulating the postprandial stomach: biorelevant test methods for the estimation of intragastric drug dissolution. Mol Pharm. 2013;10(6):2211–21.

    CAS  PubMed  Google Scholar 

  25. Kambayashi A, Dressman JB. An in vitro–in silico–in vivo approach to predicting the oral pharmacokinetic profile of salts of weak acids: case example dantrolene. Eur J Pharm Biopharm. 2013;84(1):200–7.

    CAS  PubMed  Google Scholar 

  26. Heigoldt U, Sommer F, Daniels R, Wagner K-G. Predicting in vivo absorption behavior of oral modified release dosage forms containing pH-dependent poorly soluble drugs using a novel pH-adjusted biphasic in vitro dissolution test. Eur J Pharm Biopharm. 2010;76(1):105–11.

    CAS  PubMed  Google Scholar 

  27. Chawla G, Bansal A. A comparative assessment of solubility advantage from glassy and crystalline forms of a water-insoluble drug. Eur J Pharm Sci. 2007;32(1):45–57.

    CAS  PubMed  Google Scholar 

  28. 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.

    CAS  PubMed  Google Scholar 

  29. Mathias NR, Xu Y, Patel D, Grass M, Caldwell B, Jager C, et al. Assessing the risk of pH-dependent absorption for new molecular entities: a novel in vitro dissolution test, physicochemical analysis, and risk assessment strategy. Mol Pharm. 2013;10(11):4063–73.

    CAS  PubMed  Google Scholar 

  30. Kaur N, Narang A, Bansal AK. Use of biorelevant dissolution and PBPK modeling to predict oral drug absorption. Eur J Pharm Biopharm. 2018;129:222–46.

    CAS  PubMed  Google Scholar 

  31. Mudie DM, Murray K, Hoad CL, Pritchard SE, Garnett MC, Amidon GL, et al. Quantification of gastrointestinal liquid volumes and distribution following a 240 mL dose of water in the fasted state. Mol Pharm. 2014;11(9):3039–47.

    CAS  PubMed  Google Scholar 

  32. Pharmaceuticals S. Avapro/Irbesartan and Irbesartan and hydrochlorothiazide. Silver Spring: US Food and Drug Administration; 1997.

    Google Scholar 

  33. Hansmann S, Darwich A, Margolskee A, Aarons L, Dressman J. Forecasting oral absorption across biopharmaceutics classification system classes with physiologically based pharmacokinetic models. J Pharm Pharmacol. 2016;68(12):1501–15.

    CAS  PubMed  Google Scholar 

  34. Vachharajani NN, Shyu WC, Smith RA, Greene DS. The effects of age and gender on the pharmacokinetics of irbesartan. Br J Clin Pharmacol. 1998;46(6):611–3.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Chapy H, Klieber S, Brun P, Gerbal-Chaloin S, Boulenc X, Nicolas O. PBPK modeling of irbesartan: incorporation of hepatic uptake. Biopharm Drug Dispos. 2015;36(8):491–506.

    CAS  PubMed  Google Scholar 

  36. Vachharajani NN, Shyu WC, Mantha MS, Park JS, Greene DS, Barbhaiya RH. Lack of effect of food on the oral bioavailability of irbesartan in healthy male volunteers. J Clin Pharmacol. 1998;38(5):433–6.

    CAS  PubMed  Google Scholar 

  37. Chawla G, Bansal AK. Molecular mobility and physical stability of amorphous irbesartan. Sci Pharm. 2008;77(3):695–710.

    Google Scholar 

  38. Mitra A, Fadda H. Effect of surfactants, gastric emptying, and dosage form on supersaturation of dipyridamole in an in vitro model simulating the stomach and duodenum. Mol Pharm. 2014;11(8):2835–44.

    CAS  PubMed  Google Scholar 

  39. Hens B, Brouwers J, Corsetti M, Augustijns P. Supersaturation and precipitation of posaconazole upon entry in the upper small intestine in humans. J Pharm Sci. 2015.

  40. Jambhekar SS, Breen PJ. Drug dissolution: significance of physicochemical properties and physiological conditions. Drug Discov Today. 2013;18(23):1173–84.

    CAS  PubMed  Google Scholar 

  41. Hörter D, Dressman J. Influence of physicochemical properties on dissolution of drugs in the gastrointestinal tract. Adv Drug Deliv Rev. 2001;46(1):75–87.

    PubMed  Google Scholar 

  42. Wiedmann TS, Kamel L. Examination of the solubilization of drugs by bile salt micelles. J Pharm Sci. 2002;91(8):1743–64.

    CAS  PubMed  Google Scholar 

  43. Arnold YE, Imanidis G, Kuentz MT. Advancing in-vitro drug precipitation testing: new process monitoring tools and a kinetic nucleation and growth model. J Pharm Pharmacol. 2011;63(3):333–41.

    CAS  PubMed  Google Scholar 

  44. Shono Y, Jantratid E, Kesisoglou F, Reppas C, Dressman JB. Forecasting in vivo oral absorption and food effect of micronized and nanosized aprepitant formulations in humans. Eur J Pharm Biopharm. 2010;76(1):95–104.

    CAS  PubMed  Google Scholar 

  45. Narang AS, Badawy S, Ye Q, Patel D, Vincent M, Raghavan K, et al. Role of self-association and supersaturation in oral absorption of a poorly soluble weakly basic drug. Pharm Res. 2015;32(8):1–16.

    Google Scholar 

  46. Nernst W. Theorie der Reaktionsgeschwindigkeit in heterogenen Systemen. Z Phys Chem. 1904;47(1):52–5.

    CAS  Google Scholar 

  47. Brunner E. Reaktionsgeschwindigkeit in Heterogenen Systemen. Phys Chem. 1904;47(1):56–102.

    Google Scholar 

  48. Mitra A, Kesisoglou F. Impaired drug absorption due to high stomach pH: a review of strategies for mitigation of such effect to enable pharmaceutical product development. Mol Pharm. 2013;10(11):3970–9.

    CAS  PubMed  Google Scholar 

  49. Kletzl H, Giraudon M, Ducray PS, Abt M, Hamilton M, Lum BL. Effect of gastric pH on erlotinib pharmacokinetics in healthy individuals: omeprazole and ranitidine. Anti-Cancer Drugs. 2015;26(5):565–72.

    CAS  PubMed  Google Scholar 

  50. Blum RA, D'andrea DT, Florentino BM, Wilton JH, Hilligoss DM, Gardner MJ, et al. Increased gastric pH and the bioavailability of fluconazole and ketoconazole. Ann Intern Med. 1991;114(9):755–7.

    CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Arvind Kumar Bansal.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

ESM 1

(DOCX 619 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kaur, N., Thakur, P.S., Shete, G. et al. Understanding the Oral Absorption of Irbesartan Using Biorelevant Dissolution Testing and PBPK Modeling. AAPS PharmSciTech 21, 102 (2020). https://doi.org/10.1208/s12249-020-01643-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1208/s12249-020-01643-x

KEY WORDS

  • weak base
  • biorelevant
  • PBPK modeling
  • GastroPlus™