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Mechanistic Approaches to Predicting Oral Drug Absorption

  • Review Article
  • Theme: Towards Integrated ADME Prediction: Past, Present, and Future Directions
  • Published:
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Abstract

Modeling and simulation of oral drug absorption have been widely used in drug discovery, development, and regulation. Predictive absorption models are used to determine the rate and extent of oral drug absorption, facilitate lead drug candidate selection, establish formulation development strategy, and support the development of regulatory policies. This review highlights the development of recent drug absorption models including dispersion and compartmental models. The compartmental models include the compartmental absorption and transit model; Grass model; gastrointestinal transit absorption model; advanced compartmental absorption and transit model; and advanced dissolution, absorption, and metabolism model. Compared to the early absorption models, the above models developed or extended since the mid-1990s have demonstrated greatly improved predictive performance by accounting for multiple factors such as drug degradation, gastric emptying, intestinal transit, first-pass metabolism, and intestinal transport. For future model development, more heterogeneous features of the gastrointestinal tract (villous blood flow, metabolizing enzymes, and transporters), food effects, and drug–drug interactions should be fully characterized and taken into consideration. Moreover, predicting population inter- and intravariability in oral drug absorption can be useful and important for the evaluation of clinical safety and efficacy of drugs. Establishing databases and libraries that contain accurate pharmaceutical and pharmacokinetic information for commercialized and uncommercialized drugs may also be helpful for model development and validation.

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References

  1. Yu LX, Lipka E, Crison JR, Amidon GL. Transport approaches to the biopharmaceutical design of oral drug delivery systems: prediction of intestinal absorption. Adv Drug Deliv Rev. 1996;19:359–76.

    Article  PubMed  CAS  Google Scholar 

  2. Martinez MN, Amidon GL. A mechanistic approach to understanding the factors affecting drug absorption: a review of fundamentals. J Clin Pharmacol. 2002;42:620–43.

    Article  PubMed  CAS  Google Scholar 

  3. Schanker LS. On the mechanism of absorption of drugs from the gastrointestinal tract. J Med Pharm Chem. 1960;2:343–59.

    Article  PubMed  CAS  Google Scholar 

  4. Dressman JB, Amidon GL, Fleisher D. Absorption potential: estimating the fraction absorbed for orally administered compounds. J Pharm Sci. 1985;74:588–9.

    Article  PubMed  CAS  Google Scholar 

  5. Macheras PE, Symillides MY. Toward a quantitative approach for the prediction of the fraction of dose absorbed using the absorption potential concept. Biopharm Drug Dispos. 1989;10:43–53.

    Article  PubMed  CAS  Google Scholar 

  6. Amidon GL, Sinko PJ, Fleisher D. Estimating human oral fraction dose absorbed: a correlation using rat intestinal membrane permeability for passive and carrier-mediated compounds. Pharm Res. 1988;5:651–4.

    Article  PubMed  CAS  Google Scholar 

  7. Sinko PJ, Leesman GD, Amidon GL. Predicting fraction dose absorbed in humans using a macroscopic mass balance approach. Pharm Res. 1991;8:979–88.

    Article  PubMed  CAS  Google Scholar 

  8. Sinko PJ, Leesman GD, Amidon GL. Mass balance approaches for estimating the intestinal absorption and metabolism of peptides and analogues: theoretical development and applications. Pharm Res. 1993;10:271–5.

    Article  PubMed  CAS  Google Scholar 

  9. Oh DM, Curl RL, Amidon GL. Estimating the fraction dose absorbed from suspensions of poorly soluble compounds in humans: a mathematical model. Pharm Res. 1993;10:264–70.

    Article  PubMed  CAS  Google Scholar 

  10. Lennernas H, et al. Regional jejunal perfusion, a new in vivo approach to study oral drug absorption in man. Pharm Res. 1992;9:1243–51.

    Article  PubMed  CAS  Google Scholar 

  11. Ni PF, Ho NFH, Fox JF. Theoretical model studies of intestinal drug absorption v: nonsteady-state fluid flow and absorption. Int J Pharm. 1980;5:33–47.

    Article  CAS  Google Scholar 

  12. Goodacre BC, Murray PJ. A mathematical model of drug absorption. J Clin Hosp Pharm. 1981;6:117–33.

    PubMed  CAS  Google Scholar 

  13. Dressman JB, Fleisher D, Amidon GL. Physicochemical model for dose-dependent drug absorption. J Pharm Sci. 1984;73:4–9.

    Google Scholar 

  14. Dressman JB, Fleisher D. Mixing-tank model for predicting dissolution rate control or oral absorption. J Pharm Sci. 1986;75:109–16.

    Article  PubMed  CAS  Google Scholar 

  15. Oberle RL, Amidon GL. The influence of variable gastric emptying and intestinal transit rates on the plasma level curve of cimetidine; an explanation for the double peak phenomenon. J Pharmacokinet Biopharm. 1987;15:529–44.

    Article  PubMed  CAS  Google Scholar 

  16. Willmann S, Schmitt W, Keldenich J, Dressman JB. A physiologic model for simulating gastrointestinal flow and drug absorption in rats. Pharm Res. 2003;20:1766–71.

    Article  PubMed  CAS  Google Scholar 

  17. Willmann S, et al. A physiological model for the estimation of the fraction dose absorbed in humans. J Med Chem. 2004;47:4022–31.

    Article  PubMed  CAS  Google Scholar 

  18. Willmann S, Edginton AN, Dressman JB. Development and validation of a physiology-based model for the prediction of oral absorption in monkeys. Pharm Res. 2007;24:1275–82.

    Article  PubMed  CAS  Google Scholar 

  19. Custodio JM, Wu CY, Benet LZ. Predicting drug disposition, absorption/elimination/transporter interplay and the role of food on drug absorption. Adv Drug Deliv Rev. 2008;60:717–33.

    Article  PubMed  CAS  Google Scholar 

  20. Webb R, Miller D, Traina V, Gomez H. Benazepril. Cardiovasc Drug Rev. 1990;8:89–104.

    Article  CAS  Google Scholar 

  21. Schran HF, Tse FL, Bhuta SI. Pharmacokinetics and pharmacodynamics of bromocriptine in the rat. Biopharm Drug Dispos. 1985;6:301–11.

    Article  PubMed  CAS  Google Scholar 

  22. Kivisto KT, Kantola T, Neuvonen PJ. Different effects of itraconazole on the pharmacokinetics of fluvastatin and lovastatin. Br J Clin Pharmacol. 1998;46:49–53.

    Article  PubMed  CAS  Google Scholar 

  23. Troutman MD, Thakker DR. Novel experimental parameters to quantify the modulation of absorptive and secretory transport of compounds by P-glycoprotein in cell culture models of intestinal epithelium. Pharm Res. 2003;20:1210–24.

    Article  PubMed  CAS  Google Scholar 

  24. Sinko PJ, Balimane PV. Carrier-mediated intestinal absorption of valacyclovir, the L-valyl ester prodrug of acyclovir: 1. Interactions with peptides, organic anions and organic cations in rats. Biopharm Drug Dispos. 1998;19:209–17.

    Article  PubMed  CAS  Google Scholar 

  25. Han H, et al. 5′-Amino acid esters of antiviral nucleosides, acyclovir, and AZT are absorbed by the intestinal PEPT1 peptide transporter. Pharm Res. 1998;15:1154–9.

    Article  PubMed  CAS  Google Scholar 

  26. Bretschneider B, Brandsch M, Neubert R. Intestinal transport of beta-lactam antibiotics: analysis of the affinity at the H+/peptide symporter (PEPT1), the uptake into Caco-2 cell monolayers and the transepithelial flux. Pharm Res. 1999;16:55–61.

    Article  PubMed  CAS  Google Scholar 

  27. Ganapathy ME, et al. Differential recognition of beta -lactam antibiotics by intestinal and renal peptide transporters, PEPT 1 and PEPT 2. J Biol Chem. 1995;270:25672–7.

    Article  PubMed  CAS  Google Scholar 

  28. Willmann S, Lippert J, Sevestre M. PK-Sim®: a physiologically based pharmacokinetic ‘whole-body’ model. Biosilico 2003;1:121–4.

    Article  CAS  Google Scholar 

  29. Kleine-Besten M, Willmann S, Eddington AN. The prediction of cimetidine absorption profiles with PK-Sim® using in vitro dissolution data. German Chapter Annual Meeting of the Controlled Release Society February: 23–24 (2006).

  30. Blank K, Becker C, Jantratid E. PBPK modeling to demonstrate the impact of variability in CYP3A-mediated metabolism of nifedipine in different subpopulations. The 6th World Meeting on Pharmaceutics, Biopharmaceutics and Pharmaceutical Technology April: 7–10 (2008).

  31. Yu LX, Amidon GL. A compartmental absorption and transit model for estimating oral drug absorption. Int J Pharm. 1999;186:119–25.

    Article  PubMed  CAS  Google Scholar 

  32. Yu LX, Amidon GL. Saturable small intestinal drug absorption in humans: modeling and interpretation of cefatrizine data. Eur J Pharm Biopharm. 1998;45:199–203.

    Article  PubMed  CAS  Google Scholar 

  33. Yu LX. An integrated model for determining causes of poor oral drug absorption. Pharm Res. 1999;16:1883–7.

    Article  PubMed  CAS  Google Scholar 

  34. Kortejarvi H, Urtti A, Yliperttula M. Pharmacokinetic simulation of biowaiver criteria: the effects of gastric emptying, dissolution, absorption and elimination rates. Eur J Pharm Sci. 2007;30:155–66.

    Article  PubMed  CAS  Google Scholar 

  35. Agoram B, Woltosz WS, Bolger MB. Predicting the impact of physiological and biochemical processes on oral drug bioavailability. Adv Drug Deliv Rev. 2001;50(Suppl 1):S41–67.

    Article  PubMed  CAS  Google Scholar 

  36. Lobenberg R, et al. Dissolution testing as a prognostic tool for oral drug absorption: dissolution behavior of glibenclamide. Pharm Res. 2000;17:439–44.

    Article  PubMed  CAS  Google Scholar 

  37. Okumu A, Dimaso M, Lobenberg R. Dynamic dissolution testing to establish in vitro/in vivo correlations for montelukast sodium, a poorly soluble drug. Pharm Res. 2008;25:2778–85.

    Article  PubMed  CAS  Google Scholar 

  38. Tubic-Grozdanis M, Bolger MB, Langguth P. Application of gastrointestinal simulation for extensions for biowaivers of highly permeable compounds. AAPS J. 2008;10:213–26.

    Article  PubMed  CAS  Google Scholar 

  39. Dannenfelser RM, et al. Development of clinical dosage forms for a poorly water soluble drug I: application of polyethylene glycol-polysorbate 80 solid dispersion carrier system. J Pharm Sci. 2004;93:1165–75.

    Article  PubMed  CAS  Google Scholar 

  40. Kuentz M, Nick S, Parrott N, Rothlisberger D. A strategy for preclinical formulation development using Gastroplus as pharmacokinetic simulation tool and a statistical screening design applied to a dog study. Eur J Pharm Sci. 2006;27:91–9.

    Article  PubMed  CAS  Google Scholar 

  41. Wei H, et al. Physicochemical characterization of five glyburide powders: a BCS based approach to predict oral absorption. Eur J Pharm Biopharm. 2008;69:1046–56.

    Article  PubMed  CAS  Google Scholar 

  42. Jones HM, Parrott N, Ohlenbusch G, Lave T. Predicting pharmacokinetic food effects using biorelevant solubility media and physiologically based modelling. Clin Pharmacokinet. 2006;45:1213–26.

    Article  PubMed  CAS  Google Scholar 

  43. De Buck SS, et al. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs. Drug Metab Dispos. 2007;35:1766–80.

    Article  PubMed  Google Scholar 

  44. Tubic M, et al. In silico modeling of non-linear drug absorption for the P-gp substrate talinolol and of consequences for the resulting pharmacodynamic effect. Pharm Res. 2006;23:1712–20.

    Article  PubMed  CAS  Google Scholar 

  45. Mouly S, Paine MF. P-glycoprotein increases from proximal to distal regions of human small intestine. Pharm Res. 2003;20:1595–9.

    Article  PubMed  CAS  Google Scholar 

  46. Grass GM. Simulation models to predict oral drug absorption from in vitro data. Adv Drug Deliv Rev. 1997;23:199–219.

    Article  CAS  Google Scholar 

  47. Norris DA, Leesman GD, Sinko PJ, Grass GM. Development of predictive pharmacokinetic simulation models for drug discovery. J Control Release. 2000;65:55–62.

    Article  PubMed  CAS  Google Scholar 

  48. Parrott N, Lave T. Prediction of intestinal absorption: comparative assessment of Gastroplus and IDEA. Eur J Pharm Sci. 2002;17:51–61.

    Article  PubMed  CAS  Google Scholar 

  49. Bohets H, et al. Strategies for absorption screening in drug discovery and development. Curr Top Med Chem. 2001;1:367–83.

    Article  PubMed  CAS  Google Scholar 

  50. Sawamoto T, et al. Prediction of the plasma concentration profiles of orally administered drugs in rats on the basis of gastrointestinal transit kinetics and absorbability. J Pharm Pharmacol. 1997;49:450–7.

    PubMed  CAS  Google Scholar 

  51. Kimura T, Higaki K. Gastrointestinal transit and drug absorption. Biol Pharm Bull. 2002;25:149–64.

    Article  PubMed  CAS  Google Scholar 

  52. Yokoe J, et al. Analysis and prediction of absorption behavior of colon-targeted prodrug in rats by GI-transit-absorption model. J Control Release. 2003;86:305–13.

    Article  PubMed  CAS  Google Scholar 

  53. Kimura T, et al. Analysis and prediction of absorption profile including hepatic first-pass metabolism of n-methyltyramine, a potent stimulant of gastrin release present in beer, after oral ingestion in rats by gastrointestinal-transit-absorption model. Drug Metab Dispos. 2000;28:577–81.

    PubMed  CAS  Google Scholar 

  54. Kadono K, et al. Analysis and prediction of absorption behavior for theophylline orally administered as powders based on gastrointestinal-transit-absorption (GITA) model. Drug Metab Pharmacokinet. 2002;17:307–15.

    Article  PubMed  CAS  Google Scholar 

  55. Fujioka Y, et al. Prediction of oral absorption of griseofulvin, a BCS class II drug, based on GITA model: utilization of a more suitable medium for in-vitro dissolution study. J Control Release. 2007;119:222–8.

    Article  PubMed  CAS  Google Scholar 

  56. Jamei M, Yang J, T. D. A novel physiologically-based mechanistic model for predicting oral drug absorption: the advanced dissolution, absorption, and metabolism (ADAM) model. 4th World Conference on Drug Absorption, Transport and Delivery (WCDATD) June: 20–22 (2007).

  57. 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;3:491–505.

    Article  PubMed  CAS  Google Scholar 

  58. Horter D, Dressman JB. Influence of physicochemical properties on dissolution of drugs in the gastrointestinal tract. Adv Drug Deliv Rev. 2001;46:75–87.

    Article  PubMed  CAS  Google Scholar 

  59. Wang J, Flanagan DR. General solution for diffusion-controlled dissolution of spherical particles. 1. Theory. J Pharm Sci. 1999;88:731–8.

    Article  PubMed  CAS  Google Scholar 

  60. Polak S, Jamei M, Turner D. Prediction of the in vivo behaviour of modified release formulations of metoprolol from in vitro dissolution profiles using the ADAM model (Simcyp®v8). 10th European ISSX Meeting May: 18–21 (2008).

  61. Ito K, Kusuhara H, Sugiyama Y. Effects of intestinal CYP3A4 and P-glycoprotein on oral drug absorption—theoretical approach. Pharm Res. 1999;16:225–31.

    Article  PubMed  CAS  Google Scholar 

  62. Cong D, Doherty M, Pang KS. A new physiologically based, segregated-flow model to explain route-dependent intestinal metabolism. Drug Metab Dispos. 2000;28:224–35.

    PubMed  CAS  Google Scholar 

  63. Tam D, Tirona RG, Pang KS. Segmental intestinal transporters and metabolic enzymes on intestinal drug absorption. Drug Metab Dispos. 2003;31:373–83.

    Article  PubMed  CAS  Google Scholar 

  64. Cao X, et al. Why is it challenging to predict intestinal drug absorption and oral bioavailability in human using rat model. Pharm Res. 2006;23:1675–86.

    Article  PubMed  CAS  Google Scholar 

  65. Sun D, et al. Comparison of human duodenum and Caco-2 gene expression profiles for 12,000 gene sequences tags and correlation with permeability of 26 drugs. Pharm Res. 2002;19:1400–16.

    Article  PubMed  CAS  Google Scholar 

  66. Yu L. E-adme: predicting bioavailability and permeability. Gordon Research Conference Drug Metabolism. 2001, July.

  67. Paine MF, et al. The human intestinal cytochrome P450 “pie”. Drug Metab Dispos. 2006;34:880–6.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The authors greatly thank Drs. Danny D. Shen and Wallace P. Adams for their reviews and editing of this manuscript.

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Authors and Affiliations

  1. Office of Generic Drugs, Food and Drug Administration, 7519 Standish Place, Rockville, Maryland, 20855, USA

    Weili Huang, Sau Lawrence Lee & Lawrence X. Yu

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  1. Weili Huang
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  2. Sau Lawrence Lee
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  3. Lawrence X. Yu
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Correspondence to Lawrence X. Yu.

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Guest Editors: Lawrence X. Yu, Steven C. Sutton, and Michael B. Bolger

Opinions expressed in this manuscript are those of Huang, Lee, and Yu and do not necessarily reflect the views or policies of the FDA.

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Huang, W., Lee, S.L. & Yu, L.X. Mechanistic Approaches to Predicting Oral Drug Absorption. AAPS J 11, 217–224 (2009). https://doi.org/10.1208/s12248-009-9098-z

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