Basic concepts in physiologically based pharmacokinetic modeling in drug discovery and development

CPT: Pharmacometrics and Systems Pharmacology

Volumn 2, Issue 8, 2013, Pages

  Jones, H M ^a   Rowland Yeo, K ^b  

^a PFIZER INC   (United States)

^b CERTARA UK LIMITED   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPARTMENT MODEL; DRUG ABSORPTION; DRUG ACCUMULATION; DRUG CLEARANCE; DRUG CONCENTRATION; DRUG DEVELOPMENT; DRUG INDUSTRY; DRUG PENETRATION; DRUG SOLUBILITY; FOOD AND DRUG ADMINISTRATION; HUMAN; MODEL; PHARMACOKINETICS; PHYSIOLOGICALLY BASED PHARMACOKINETIC; PLASMA CONCENTRATION-TIME CURVE; PRIORITY JOURNAL; SIMULATION;

EID: 84883409705     PISSN: None     EISSN: 21638306     Source Type: Journal    
DOI: 10.1038/psp.2013.41     Document Type: Article

References (75)

1. Mitragotri, S. et al. Mathematical models of skin permeability: an overview. Int. J. Pharm. 418, 115-129 (2011).
2. Gabrielsson, J. & Weiner, D. Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications. 4th edn. (Swedish Pharmaceutical Press, Stockholm, Sweden, 2007).
3. Rowland Yeo, K., Aarabi, M., Jamei, M. & Rostami-Hodjegan, A. Modeling and predicting drug pharmacokinetics in patients with renal impairment. Expert Rev. Clin. Pharmacol. 4, 261-274 (2011).
4. Rostami-Hodjegan, A. Physiologically based pharmacokinetics joined with in vitro-in vivo extrapolation of ADME: a marriage under the arch of systems pharmacology. Clin. Pharmacol. Ther. 92, 50-61 (2012).
5. Teorell, T. Studies on the diffusion effect upon ionic distribution: II. Experiments on ionic accumulation. J. Gen. Physiol. 21, 107-122 (1937).
6. Bischoff, K.B., Dedrick, R.L., Zaharko, D.S. & Longstreth, J.A. Methotrexate pharmacokinetics. J. Pharm. Sci. 60, 1128-1133 (1971).
7. Nestorov, I. Whole-body physiologically based pharmacokinetic models. Expert Opin. Drug Metab. Toxicol. 3, 235-249 (2007).
8. Tanaka, C., Kawai, R. & Rowland, M. Dose-dependent pharmacokinetics of cyclosporin A in rats: events in tissues. Drug Metab. Dispos. 28, 582-589 (2000).
9. Poulin, P. & Theil, F.P. Prediction of pharmacokinetics prior to in vivo studies. Mechanism-based prediction of volume of distribution. J. Pharm. Sci. 91, 129-156 (2002).
10. Berezhkovskiy, L.M. Determination of volume of distribution at steady state with complete consideration of the kinetics of protein and tissue binding in linear pharmacokinetics. J. Pharm. Sci. 93, 364-374 (2004).
11. Rodgers, T. & Rowland, M. Mechanistic approaches to volume of distribution predictions: understanding the processes. Pharm. Res. 24, 918-933 (2007).
12. Rowland, M., Peck, C. & Tucker, G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu. Rev. Pharmacol. Toxicol. 51, 45-73 (2011).
13. Pang, K.S. & Durk, M.R. Physiologically-based pharmacokinetic modeling for absorption, transport, metabolism and excretion. J. Pharmacokinet. Pharmacodyn. 37, 591-615 (2010).
14. Fenneteau, F., Poulin, P. & Nekka, F. Physiologically based predictions of the impact of inhibition of intestinal and hepatic metabolism on human pharmacokinetics of CYP3A substrates. J. Pharm. Sci. 99, 486-514 (2010).
15. Huang, S.M., Abernethy, D.R., Wang, Y., Zhao, P. & Zineh, I. The utility of modeling and simulation in drug development and regulatory review. J. Pharm. Sci. (2013); e-pub ahead of print 24 May 2013.
16. Guidance for Industry. Drug Interaction Studies-Study Design, Data Analysis, Implications for Dosing, and Labeling Recommendations. Food and Drug Admininstration, US Department of Health and Human Services, February 2012 http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/ Guidances/ucm292362.pdf . Accessed 01 April 2012.
17. Guideline on the Investigation of Drug Interactions. European Medicines Agency, 2012 http://www.ema.europa.eu/docs/en-GB/document-library/Serennac- guideline/2012/07/wcs00129606.pdf . Accessed 27 November 2012.
18. Zhao, P., Rowland, M. & Huang, S.M. Best practice in the use of physiologically based pharmacokinetic modeling and simulation to address clinical pharmacology regulatory questions. Clin. Pharmacol. Ther. 92, 17-20 (2012).
19. Nestorov, I.A., Aarons, L.J., Arundel, P.A. & Rowland, M. Lumping of whole-body physiologically based pharmacokinetic models. J. Pharmacokinet. Biopharm. 26, 21-46 (1998).
20. Rowland Yeo, K., Jamei, M., Yang, J., Tucker, G.T. & Rostami-Hodjegan, A. Physiologically based mechanistic modelling to predict complex drug-drug interactions involving simultaneous competitive and time-dependent enzyme inhibition by parent compound and its metabolite in both liver and gut-the effect of diltiazem on the timecourse of exposure to triazolam. Eur. J. Pharm. Sci. 39, 298-309 (2010).
21. Blakey, G.E., Nestorov, I.A., Arundel, P.A., Aarons, L.J. & Rowland, M. Quantitative structure-pharmacokinetics relationships: I. Development of a whole-body physiologically based model to characterize changes in pharmacokinetics across a homologous series of barbiturates in the rat. J. Pharmacokinet. Biopharm. 25, 277-312 (1997).
22. Jones, H.M., Parrott, N., Jorga, K. & Lavé, T. A novel strategy for physiologically based predictions of human pharmacokinetics. Clin. Pharmacokinet. 45, 511-542 (2006).
23. Jones, H.M. et al. Simulation of human intravenous and oral pharmacokinetics of 21 diverse compounds using physiologically based pharmacokinetic modelling. Clin. Pharmacokinet. 50, 331-347 (2011).
24. Sinha, V.K., Snoeys, J., Osselaer, N.V., Peer, A.V., Mackie, C. & Heald, D. From preclinical to human-prediction of oral absorption and drug-drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach in an industrial setting: a workflow by using case example. Biopharm. Drug Dispos. 33, 111-121 (2012).
25. Chen, Y., Jin, J.Y., Mukadam, S., Malhi, V. & Kenny, J.R. Application of IVIVE and PBPK modeling in prospective prediction of clinical pharmacokinetics: strategy and approach during the drug discovery phase with four case studies. Biopharm. Drug Dispos. 33, 85-98 (2012).
26. De Buck, S.S., Sinha, V.K., Fenu, L.A., Nijsen, M.J., Mackie, C.E. & Gilissen, R.A. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs. Drug Metab. Dispos. 35, 1766-1780 (2007).
27. Sugano, K. Introduction to computational oral absorption simulation. Expert Opin. Drug Metab. Toxicol. 5, 259-293 (2009).
28. Agoram, B., Woltosz, W.S. & Bolger, M.B. Predicting the impact of physiological and biochemical processes on oral drug bioavailability. Adv. Drug Deliv. Rev. 50 (suppl. 1), S41-S67 (2001).
29. Willmann, S., Schmitt, W., Keldenich, J., Lippert, J. & Dressman, J.B. A physiological model for the estimation of the fraction dose absorbed in humans. J. Med. Chem. 47, 4022-4031 (2004).
30. Jamei, M. et al. Population-based mechanistic prediction of oral drug absorption. AAPS J. 11, 225-237 (2009).
31. Brown, R.P., Delp, M.D., Lindstedt, S.L., Rhomberg, L.R. & Beliles, R.P. Physiological parameter values for physiologically based pharmacokinetic models. Toxicol. Ind. Health 13, 407-484 (1997).
32. Edginton, A.N. & Willmann, S. Physiology-based simulations of a pathological condition: prediction of pharmacokinetics in patients with liver cirrhosis. Clin. Pharmacokinet. 47, 743-752 (2008).
33. Johnson, T.N., Boussery, K., Rowland-Yeo, K., Tucker, G.T. & Rostami-Hodjegan, A. A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance. Clin. Pharmacokinet. 49, 189-206 (2010).
34. Thompson, C.M. et al. Database for physiologically based pharmacokinetic (PBPK) modeling: physiological data for healthy and health-impaired elderly. J. Toxicol. Environ. Health. B. Crit. Rev. 12, 1-24 (2009).
35. Johnson, T.N., Rostami-Hodjegan, A. & Tucker, G.T. Prediction of the clearance of eleven drugs and associated variability in neonates, infants and children. Clin. Pharmacokinet. 45, 931-956 (2006).
36. Abduljalil, K., Furness, P., Johnson, T.N., Rostami-Hodjegan, A. & Soltani, H. Anatomical, physiological and metabolic changes with gestational age during normal pregnancy: a database for parameters required in physiologically based pharmacokinetic modelling. Clin. Pharmacokinet. 51, 365-396 (2012).
37. Ghobadi, C. et al. Application of a systems approach to the bottom-up assessment of pharmacokinetics in obese patients: expected variations in clearance. Clin. Pharmacokinet. 50, 809-822 (2011).
38. Plowchalk, D.R. & Rowland Yeo, K. Prediction of drug clearance in a smoking population: modeling the impact of variable cigarette consumption on the induction of CYP1A2. Eur. J. Clin. Pharmacol. 68, 951-960 (2012).
39. Jamei, M., Dickinson, G.L. & Rostami-Hodjegan, A. A framework for assessing interindividual 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. 24, 53-75 (2009).
40. Jamei, M., Marciniak, S., Feng, K., Barnett, A., Tucker, G. & Rostami-Hodjegan, A. The Simcyp population-based ADME simulator. Expert Opin. Drug Metab. Toxicol. 5, 211-223 (2009).
41. Hallifax, D., Foster, J.A. & Houston, J.B. Prediction of human metabolic clearance from in vitro systems: retrospective analysis and prospective view. Pharm. Res. 27, 2150-2161 (2010).
42. Houston, J.B. Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance. Biochem. Pharmacol. 47, 1469-1479 (1994).
43. Rostami-Hodjegan, A. & Tucker, G.T. Simulation and prediction of in vivo drug metabolism in human populations from in vitro data. Nat. Rev. Drug Discov. 6, 140-148 (2007).
44. Shiran, M.R., Proctor, N.J., Howgate, E.M., Rowland-Yeo, K., Tucker, G.T. & Rostami-Hodjegan, A. Prediction of metabolic drug clearance in humans: in vitro-in vivo extrapolation vs allometric scaling. Xenobiotica. 36, 567-580 (2006).
45. Mahmood, I. & Sahajwalla, C. Interspecies scaling of biliary excreted drugs. J. Pharm. Sci. 91, 1908-1914 (2002).
46. Paine, S.W., Ménochet, K., Denton, R., McGinnity, D.F. & Riley, R.J. Prediction of human renal clearance from preclinical species for a diverse set of drugs that exhibit both active secretion and net reabsorption. Drug Metab. Dispos. 39, 1008-1013 (2011).
47. Bi, Y.A., Kazolias, D. & Duignan, D.B. Use of cryopreserved human hepatocytes in sandwich culture to measure hepatobiliary transport. Drug Metab. Dispos. 34, 1658-1665 (2006).
48. Jones, H.M. et al. Mechanistic pharmacokinetic modeling for the prediction of transportermediated disposition in humans from sandwich culture human hepatocyte data. Drug Metab. Dispos. 40, 1007-1017 (2012).
49. Schmitt, W. General approach for the calculation of tissue to plasma partition coefficients. Toxicol. In Vitro 22, 457-467 (2008).
50. Peyret, T., Poulin, P. & Krishnan, K. A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals. Toxicol. Appl. Pharmacol. 249, 197-207 (2010).
51. Graham, H., Walker, M., Jones, O., Yates, J., Galetin, A. & Aarons, L. Comparison of in-vivo and in-silico methods used for prediction of tissue: plasma partition coefficients in rat. J. Pharm. Pharmacol. 64, 383-396 (2012).
52. Poulin, P. & Theil, F.P. Development of a novel method for predicting human volume of distribution at steady-state of basic drugs and comparative assessment with existing methods. J. Pharm. Sci. 98, 4941-4961 (2009).
53. Lennernäs, H. Human intestinal permeability. J. Pharm. Sci. 87, 403-410 (1998).
54. Jantratid, E., Janssen, N., Reppas, C. & Dressman, J.B. Dissolution media simulating conditions in the proximal human gastrointestinal tract: an update. Pharm. Res. 25, 1663-1676 (2008).
55. Parrott, N., Lukacova, V., Fraczkiewicz, G. & Bolger, M.B. Predicting pharmacokinetics of drugs using physiologically based modeling-application to food effects. AAPS J. 11, 45-53 (2009).
56. Jones, H.M., Parrott, N., Ohlenbusch, G. & Lavé, T. Predicting pharmacokinetic food effects using biorelevant solubility media and physiologically based modelling. Clin. Pharmacokinet. 45, 1213-1226 (2006).
57. Watson, K.J., Davis, J. & Jones, H.M. Application of physiologically based pharmacokinetic modeling to understanding the clinical pharmacokinetics of UK-369,003. Drug Metab. Dispos. 39, 1203-1213 (2011).
58. Poirier, A., Cascais, A.C., Funk, C. & Lavé, T. Prediction of pharmacokinetic profile of valsartan in humans based on in vitro uptake-transport data. Chem. Biodivers. 6, 1975-1987 (2009).
59. Watanabe, T., Kusuhara, H., Maeda, K., Shitara, Y. & Sugiyama, Y. Physiologically based pharmacokinetic modeling to predict transporter-mediated clearance and distribution of pravastatin in humans. J. Pharmacol. Exp. Ther. 328, 652-662 (2009).
60. Bungay, P.J., Tweedy, S., Howe, D.C., Gibson, K.R., Jones, H.M. & Mount, N.M. Preclinical and clinical pharmacokinetics of PF-02413873, a nonsteroidal progesterone receptor antagonist. Drug Metab. Dispos. 39, 1396-1405 (2011).
61. Yamazaki, S. et al. Prediction of oral pharmacokinetics of cMet kinase inhibitors in humans: physiologically based pharmacokinetic model versus traditional one-compartment model. Drug Metab. Dispos. 39, 383-393 (2011).
62. Vieira, M.L. et al. Predicting drug interaction potential with a physiologically based pharmacokinetic model: a case study of telithromycin, a time-dependent CYP3A inhibitor. Clin. Pharmacol. Ther. 91, 700-708 (2012).
63. Varma, M.V., Lai, Y., Feng, B., Litchfield, J., Goosen, T.C. & Bergman, A. Physiologically based modeling of pravastatin transporter-mediated hepatobiliary disposition and drugdrug interactions. Pharm. Res. 29, 2860-2873 (2012).
64. Rowland-Yeo, K., Jamei, M., Aarabi, M. & Rostami-Hodjegan, A. Application of physiologically based pharmacokinetic (PBPK) modelling for prediction of complex drug-drug interactions (DDIs) involving OATP1B1-mediated uptake and cytochrome P450 (CYP) metabolism and multiple inhibitors. Clin. Pharmacol. Ther. 91, S47-S48 (2012).
65. Gelman, A. & Rubin, D.B. Markov chain Monte Carlo methods in biostatistics. Stat. Methods Med. Res. 5, 339-355 (1996).
66. Huang, S.M. & Rowland, M. The role of physiologically based pharmacokinetic modeling in regulatory review. Clin. Pharmacol. Ther. 91, 542-549 (2012).
67. Niemi, M., Kajosaari, L.I., Neuvonen, M., Backman, J.T. & Neuvonen, P.J. The CYP2C8 inhibitor trimethoprim increases the plasma concentrations of repaglinide in healthy subjects. Br. J. Clin. Pharmacol. 57, 441-447 (2004).
68. Di, L. et al. A novel relay method for determining low-clearance values. Drug Metab. Dispos. 40, 1860-1865 (2012).
69. Vicini, P. & van der Graaf, P.H. Systems pharmacology for drug discovery and development: paradigm shift or flash in the pan? Clin. Pharmacol. Ther. 93, 379-381 (2013).
70. Shah, D.K. & Betts, A.M. Towards a platform PBPK model to characterize the plasma and tissue disposition of monoclonal antibodies in preclinical species and human. J. Pharmacokinet. Pharmacodyn. 39, 67-86 (2012).
71. Mandic, Z. & Gabelica, V. Ionization, lipophilicity and solubility properties of repaglinide. J. Pharm. Biomed. Anal. 41, 866-871 (2006).
72. Hatorp, V., Walther, K.H., Christensen, M.S. & Haug-Pihale, G. Single-dose pharmacokinetics of repaglinide in subjects with chronic liver disease. J. Clin. Pharmacol. 40, 142-152 (2000).
73. van Heiningen, P.N. et al. Absorption, metabolism and excretion of a single oral dose of (14)C-repaglinide during repaglinide multiple dosing. Eur. J. Clin. Pharmacol. 55, 521-525 (1999).
74. Kajosaari, L.I., Laitila, J., Neuvonen, P.J. & Backman, J.T. Metabolism of repaglinide by CYP2C8 and CYP3A4 in vitro: effect of fibrates and rifampicin. Basic Clin. Pharmacol. Toxicol. 97, 249-256 (2005).
75. Gertz, M., Harrison, A., Houston, J.B. & Galetin, A. Prediction of human intestinal firstpass metabolism of 25 CYP3A substrates from in vitro clearance and permeability data. Drug Metab. Dispos. 38, 1147-1158 (2010).