Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2015, Article ID 857327, 9 pages
http://dx.doi.org/10.1155/2015/857327
Research Article

How to Choose In Vitro Systems to Predict In Vivo Drug Clearance: A System Pharmacology Perspective

1Bioinformatics Research Center, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China
2Biomedical Engineering Institute, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China
3Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA
4School of Informatics and Computing, Indiana University, Indianapolis, IN 46202, USA
5Pattern Recognition and Intelligent System Institute, College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China
6Department of Obstetrics and Gynecology, School of Medicine, Indiana University, Indianapolis, IN 46202, USA
7Department of Medical and Molecular Genomics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA

Received 13 November 2014; Revised 23 January 2015; Accepted 4 February 2015

Academic Editor: Stelvio M. Bandiera

Copyright © 2015 Lei Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. K. Abduljalil, T. Cain, H. Humphries, and A. Rostami-Hodjegan, “Deciding on success criteria for predictability of pharmacokinetic parameters from in vitro studies: an analysis based on in vivo observations,” Drug Metabolism & Disposition, vol. 42, no. 9, pp. 1478–1484, 2014. View at Publisher · View at Google Scholar
  2. F. Lombardo, R. S. Obach, M. V. Varma, R. Stringer, and G. Berellini, “Clearance mechanism assignment and total clearance prediction in human based upon in silico models,” Journal of Medicinal Chemistry, vol. 57, no. 10, pp. 4397–4405, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. M. Shou, “Prediction of pharmacokinetics and drug-drug interactions from in vitro metabolism data,” Current Opinion in Drug Discovery and Development, vol. 8, no. 1, pp. 66–77, 2005. View at Google Scholar · View at Scopus
  4. D. Zhang, G. Luo, X. Ding, and C. Lu, “Preclinical experimental models of drug metabolism and disposition in drug discovery and development,” Acta Pharmaceutica Sinica B, vol. 2, no. 6, pp. 549–561, 2012. View at Publisher · View at Google Scholar
  5. H. Tang and M. Mayersohn, “A novel model for prediction of human drug clearance by allometric scaling,” Drug Metabolism and Disposition, vol. 33, no. 9, pp. 1297–1303, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. R. A. Stringer, C. Strain-Damerell, P. Nicklin, and J. B. Houston, “Evaluation of recombinant cytochrome p450 enzymes as an in vitro system for metabolic clearance predictions,” Drug Metabolism & Disposition, vol. 37, no. 5, pp. 1025–1034, 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. U. Zanelli, N. P. Caradonna, D. Hallifax, E. Turlizzi, and J. B. Houston, “Comparison of cryopreserved HepaRG cells with cryopreserved human hepatocytes for prediction of clearance for 26 drugs,” Drug Metabolism and Disposition, vol. 40, no. 1, pp. 104–110, 2012. View at Publisher · View at Google Scholar · View at Scopus
  8. K. Ito and J. B. Houston, “Prediction of human drug clearance from in vitro and preclinical data using physiologically based and empirical approaches,” Pharmaceutical Research, vol. 22, no. 1, pp. 103–112, 2005. View at Publisher · View at Google Scholar · View at Scopus
  9. J. Sahi, S. Grepper, and C. Smith, “Hepatocytes as a tool in drug metabolism, transport and safety evaluations in drug discovery,” Current Drug Discovery Technologies, vol. 7, no. 3, pp. 188–198, 2010. View at Google Scholar · View at Scopus
  10. D. F. McGinnity, M. G. Soars, R. A. Urbanowicz, and R. J. Riley, “Evaluation of fresh and cryopreserved hepatocytes as in vitro drug metabolism tools for the prediction of metabolic clearance,” Drug Metabolism and Disposition, vol. 32, no. 11, pp. 1247–1253, 2004. View at Publisher · View at Google Scholar · View at Scopus
  11. P. Zhao, K. L. Kunze, and C. A. Lee, “Evaluation of time-dependent inactivation of CYP3A in cryopreserved human hepatocytes,” Drug Metabolism & Disposition, vol. 33, no. 6, pp. 853–861, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. N. Hariparsad, R. S. Sane, S. C. Strom, and P. B. Desai, “In vitro methods in human drug biotransformation research: implications for cancer chemotherapy,” Toxicology in Vitro, vol. 20, no. 2, pp. 135–153, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. X. Wu, J. Wang, L. Tan et al., “In Vitro ADME profiling using high-throughput rapidfire mass spectrometry: cytochrome P450 inhibition and metabolic stability assays,” Journal of Biomolecular Screening, vol. 17, no. 6, pp. 761–772, 2012. View at Publisher · View at Google Scholar · View at Scopus
  14. O. V. Trubetskoy, J. R. Gibson, and B. D. Marks, “Highly miniaturized formats for in vitro drug metabolism assays using vivid fluorescent substrates and recombinant human cytochrome P450 enzymes,” Journal of Biomolecular Screening, vol. 10, no. 1, pp. 56–66, 2005. View at Publisher · View at Google Scholar · View at Scopus
  15. N. J. Hewitt, M. J. G. Lechón, J. B. Houston et al., “Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies,” Drug Metabolism Reviews, vol. 39, no. 1, pp. 159–234, 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. P. Chao, A. S. Uss, and K. Cheng, “Use of intrinsic clearance for prediction of human hepatic clearance,” Expert Opinion on Drug Metabolism and Toxicology, vol. 6, no. 2, pp. 189–198, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. M. Chiba, Y. Ishii, and Y. Sugiyama, “Prediction of hepatic clearance in human from in vitro data for successful drug development,” The AAPS Journal, vol. 11, no. 2, pp. 262–276, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. R. Niro, J. P. Byers, R. L. Fournier, and K. Bachmann, “Application of a convective-dispersion model to predict in vivo hepatic clearance from in vitro measurements utilizing cryopreserved human hepatocytes,” Current Drug Metabolism, vol. 4, no. 5, pp. 357–369, 2003. View at Publisher · View at Google Scholar · View at Scopus
  19. Y. Naritomi, S. Terashita, A. Kagayama, and Y. Sugiyama, “Utility of hepatocytes in predicting drug metabolism: comparison of hepatic intrinsic clearance in rats and humans in vivo and in vitro,” Drug Metabolism & Disposition, vol. 31, no. 5, pp. 580–588, 2003. View at Publisher · View at Google Scholar · View at Scopus
  20. R. A. Stringer, C. Strain-Damerell, P. Nicklin, and J. B. Houston, “Evaluation of recombinant cytochrome p450 enzymes as an in vitro system for metabolic clearance predictions,” Drug Metabolism and Disposition, vol. 37, no. 5, pp. 1025–1034, 2009. View at Publisher · View at Google Scholar · View at Scopus
  21. Y. Chen, L. Liu, K. Nguyen, and A. J. Fretland, “Utility of intersystem extrapolation factors in early reaction phenotyping and the quantitative extrapolation of human liver microsomal intrinsic clearance using recombinant cytochromes P450,” Drug Metabolism and Disposition, vol. 39, no. 3, pp. 373–382, 2011. View at Publisher · View at Google Scholar · View at Scopus
  22. M. Rowland, C. Peck, and G. Tucker, “Physiologically-based pharmacokinetics in drug development and regulatory science,” Annual Review of Pharmacology and Toxicology, vol. 51, pp. 45–73, 2011. View at Publisher · View at Google Scholar · View at Scopus
  23. L. E. Gerlowski and R. K. Jain, “Physiologically based pharmacokinetic modeling: principles and applications,” Journal of Pharmaceutical Sciences, vol. 72, no. 10, pp. 1103–1127, 1983. View at Publisher · View at Google Scholar · View at Scopus
  24. A. Rostami-Hodjegan, “Physiologically based pharmacokinetics joined with in vitro-in vivo extrapolation of ADME: a marriage under the arch of systems pharmacology,” Clinical Pharmacology and Therapeutics, vol. 92, no. 1, pp. 50–61, 2012. View at Publisher · View at Google Scholar · View at Scopus
  25. A. Rostami-Hodjegan and G. T. Tucker, “Simulation and prediction of in vivo drug metabolism in human populations from in vitro data,” Nature Reviews Drug Discovery, vol. 6, no. 2, pp. 140–148, 2007. View at Publisher · View at Google Scholar · View at Scopus
  26. C. W. Yap, Y. Xue, H. Li et al., “Prediction of compounds with specific pharmacodynamic, pharmacokinetic or toxicological property by statistical learning methods,” Mini-Reviews in Medicinal Chemistry, vol. 6, no. 4, pp. 449–459, 2006. View at Publisher · View at Google Scholar · View at Scopus
  27. O. Demir-Kavuk, J. Bentzien, I. Muegge, and E.-W. Knapp, “DemQSAR: predicting human volume of distribution and clearance of drugs,” Journal of Computer-Aided Molecular Design, vol. 25, no. 12, pp. 1121–1133, 2011. View at Publisher · View at Google Scholar · View at Scopus
  28. Simcyp, http://www.simcyp.com/.
  29. Gastroplus, http://www.simulations-plus.com/.
  30. O. Pelkonen, M. Turpeinen, J. Uusitalo, A. Rautio, and H. Raunio, “Prediction of drug metabolism and interactions on the basis of in vitro investigations,” Basic and Clinical Pharmacology and Toxicology, vol. 96, no. 3, pp. 167–175, 2005. View at Publisher · View at Google Scholar · View at Scopus
  31. N. S. Buchan, D. K. Rajpal, Y. Webster et al., “The role of translational bioinformatics in drug discovery,” Drug Discovery Today, vol. 16, no. 9-10, pp. 426–434, 2011. View at Publisher · View at Google Scholar · View at Scopus
  32. R. S. Obach, F. Lombardo, and N. J. Waters, “Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds,” Drug Metabolism & Disposition, vol. 36, no. 7, pp. 1385–1405, 2008. View at Publisher · View at Google Scholar · View at Scopus
  33. C. Mallo, R. Zaidan, G. Galy et al., “Pharmacokinetics of melatonin in man after intravenous infusion and bolus injection,” European Journal of Clinical Pharmacology, vol. 38, no. 3, pp. 297–301, 1990. View at Publisher · View at Google Scholar · View at Scopus
  34. H. P. Lei, X. Y. Yu, H. T. Xie et al., “Effect of St. John's wort supplementation on the pharmacokinetics of bupropion in healthy male Chinese volunteers,” Xenobiotica, vol. 40, no. 4, pp. 275–281, 2010. View at Publisher · View at Google Scholar · View at Scopus
  35. S. Hill, H. Sikand, and J. Lee, “A case report of seizure induced by bupropion nasal insufflation,” Primary Care Companion to the Journal of Clinical Psychiatry, vol. 9, no. 1, pp. 67–69, 2007. View at Publisher · View at Google Scholar · View at Scopus
  36. T. N. Gengiah, N. H. G. Holford, J. H. Botha, A. L. Gray, K. Naidoo, and S. S. A. Karim, “The influence of tuberculosis treatment on efavirenz clearance in patients co-infected with HIV and tuberculosis,” European Journal of Clinical Pharmacology, vol. 68, no. 5, pp. 689–695, 2012. View at Publisher · View at Google Scholar · View at Scopus
  37. D. A. Chiappetta, C. Hocht, C. Taira, and A. Sosnik, “Oral pharmacokinetics of the anti-HIV efavirenz encapsulated within polymeric micelles,” Biomaterials, vol. 32, no. 9, pp. 2379–2387, 2011. View at Publisher · View at Google Scholar · View at Scopus
  38. M. J. Hayes, M. J. S. Langman, and A. H. Short, “Changes in drug metabolism with increasing age: 2. Phenytoin clearance and protein binding,” British Journal of Clinical Pharmacology, vol. 2, no. 1, pp. 73–79, 1975. View at Google Scholar · View at Scopus
  39. Drug Bank, http://www.drugbank.ca.
  40. S. K. Paulson, M. B. Vaughn, S. M. Jessen et al., “Pharmacokinetics of celecoxib after oral administration in dogs and humans: effect of food and site of absorption,” Journal of Pharmacology and Experimental Therapeutics, vol. 297, no. 2, pp. 638–645, 2001. View at Google Scholar · View at Scopus
  41. A. A. Moghadamnia, A. Rostami-Hodjegan, R. Abdul-Manap, C. E. Wright, A. H. Morice, and G. T. Tucker, “Physiologically based modelling of inhibition of metabolism and assessment of the relative potency of drug and metabolite: dextromethorphan vs. dextrorphan using quinidine inhibition,” British Journal of Clinical Pharmacology, vol. 56, no. 1, pp. 57–67, 2003. View at Publisher · View at Google Scholar · View at Scopus
  42. B. KuKanich and M. G. Papich, “Plasma profile and pharmacokinetics of dextromethorphan after intravenous and oral administration in healthy dogs,” Journal of Veterinary Pharmacology and Therapeutics, vol. 27, no. 5, pp. 337–341, 2004. View at Publisher · View at Google Scholar · View at Scopus
  43. N. Brynne, M. M. Stahl, B. Hallen et al., “Pharmacokinetics and pharmacodynamics of tolterodine in man: a new drug for the treatment of urinary bladder overactivity,” International Journal of Clinical Pharmacology and Therapeutics, vol. 35, no. 7, pp. 287–295, 1997. View at Google Scholar · View at Scopus
  44. R. A. Lefebvre, A. Van Peer, and R. Woestenborghs, “Influence of itraconazole on the pharmacokinetics and electrocardiographic effects of astemizole,” British Journal of Clinical Pharmacology, vol. 43, no. 3, pp. 319–322, 1997. View at Google Scholar · View at Scopus
  45. J. A. Lowry, G. L. Kearns, S. M. Abdel-Rahman et al., “Cisapride: a potential model substrate to assess cytochrome P4503A4 activity in vivo,” Clinical Pharmacology & Therapeutics, vol. 73, no. 3, pp. 209–222, 2003. View at Publisher · View at Google Scholar · View at Scopus
  46. S. Abel, D. Russell, L. A. Whitlock, C. E. Ridgway, A. N. Nedderman, and D. K. Walker, “Assessment of the absorption, metabolism and absolute bioavailability of maraviroc in healthy male subjects,” British Journal of Clinical Pharmacology, vol. 65, supplement 1, pp. 60–67, 2008. View at Publisher · View at Google Scholar · View at Scopus
  47. Z. Desta, T. Kerbusch, and D. A. Flockhart, “Effect of clarithromycin on the pharmacokinetics and pharmacodynamics of pimozide in healthy poor and extensive metabolizers of cytochrome P450 2D6 (CYP2D6),” Clinical Pharmacology & Therapeutics, vol. 65, no. 1, pp. 10–20, 1999. View at Publisher · View at Google Scholar · View at Scopus
  48. C. Brattstram, J. Salve, B. Jansson et al., “Pharmacokinetics and safety of single oral doses of sirolimus (rapamycin) in healthy male volunteers,” Therapeutic Drug Monitoring, vol. 22, no. 5, pp. 537–544, 2000. View at Publisher · View at Google Scholar · View at Scopus
  49. H.-Y. Wu, S. Karnik, A. Subhadarshini et al., “An integrated pharmacokinetics ontology and corpus for text mining,” BMC Bioinformatics, vol. 14, no. 1, article 35, 2013. View at Publisher · View at Google Scholar · View at Scopus
  50. FDA, Drug Interaction Studies-Study Design, Data Analysis, Implications for Dosing, and Labeling Recommendations, 2012.
  51. M. Jamei, S. Marciniak, K. Feng, A. Barnett, G. Tucker, and A. Rostami-Hodjegan, “The Simcyp population-based ADME simulator,” Expert Opinion on Drug Metabolism and Toxicology, vol. 5, no. 2, pp. 211–223, 2009. View at Publisher · View at Google Scholar · View at Scopus
  52. N. Wattanachai, W. Tassaneeyakul, A. Rowland et al., “Effect of albumin on human liver microsomal and recombinant CYP1A2 activities: impact on in vitro-in vivo extrapolation of drug clearance,” Drug Metabolism and Disposition, vol. 40, no. 5, pp. 982–989, 2012. View at Publisher · View at Google Scholar · View at Scopus
  53. H. T'jollyn, J. Snoeys, P. Colin et al., “Physiology-based IVIVE predictions of tramadol from in vitro metabolism data,” Pharmaceutical Research, vol. 32, no. 1, pp. 260–274, 2015. View at Publisher · View at Google Scholar
  54. J. O. Miners, P. I. MacKenzie, and K. M. Knights, “The prediction of drug-glucuronidation parameters in humans: UDP-glucuronosyltransferase enzyme-selective substrate and inhibitor probes for reaction phenotyping and in vitroin vivo extrapolation of drug clearance and drug-drug interaction potential,” Drug Metabolism Reviews, vol. 42, no. 1, pp. 189–201, 2010. View at Publisher · View at Google Scholar · View at Scopus