Skip to main content

Advertisement

Log in

Application of population pharmacokinetic modeling in early clinical development of the anticancer agent E7820

  • Phase I Studies
  • Published:
Investigational New Drugs Aims and scope Submit manuscript

Summary

The aim of this study was to assess the population pharmacokinetics (PopPK) of the novel oral anti-cancer agent E7820. Both a non-linear mixed effects modeling analysis and a non-compartmental analysis (NCA) were performed and results were compared. Data were obtained from a phase I dose escalation study in patients with malignant solid tumors or lymphomas. E7820 was administered daily for 28 days, followed by a washout period of 7 days prior to the start of subsequent cycles. A one compartment model with linear elimination from the central compartment was shown to give adequate fit, while absorption was described using a turnover model. Final population parameter estimates of basic PK parameters obtained with the PopPK method were (RSE): clearance, 6.24 L/h (7.1%), volume of distribution, 66.0 L (8.5%), mean transit time to the absorption compartment, 0.638 h (6.5%). The intake of food prior to dose administration slowed absorption (2.8-fold, RSE 13%) and increased relative bioavailability of E7820 by 36% (RSE 14%), although the effect on C max and AUC was not significant. Comparison with the NCA approach showed approximately equal PK parameter estimates and food effect measures, although specific advantages of PopPK included efficiency in use of data and more appropriate assessment of variability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Funahashi Y et al (2002) Sulfonamide derivative, E7820, is a unique angiogenesis inhibitor suppressing an expression of integrin alpha2 subunit on endothelium. Cancer Res 62:6116–6123

    PubMed  CAS  Google Scholar 

  2. Semba T et al (2004) An angiogenesis inhibitor E7820 shows broad-spectrum tumor growth inhibition in a xenograft model: possible value of integrin alpha2 on platelets as a biological marker. Clin Cancer Res 10:1430–1438. doi:10.1158/1078-0432.CCR-0109-03

    Article  PubMed  CAS  Google Scholar 

  3. Cross MJ, Claesson-Welsh L (2001) FGF and VEGF function in angiogenesis: signalling pathways, biological responses and therapeutic inhibition. Trends Pharmacol Sci 22:201–207 doi:10.1016/S0165-6147(00)01676-X

    Article  PubMed  CAS  Google Scholar 

  4. Stavri GT et al (1995) Basic fibroblast growth factor upregulates the expression of vascular endothelial growth factor in vascular smooth muscle cells. Synergistic interaction with hypoxia. Circulation 92:11–14

    PubMed  CAS  Google Scholar 

  5. Goodsell DS (2003) The molecular perspective: VEGF and angiogenesis. Stem Cells 21:118–119 doi:10.1634/stemcells.21-1-118

    Article  PubMed  Google Scholar 

  6. Mita MM et al (2005) Pharmacokinetics (PK) and pharmacodynamics (PD) of E7820-an oral sulfonamide with novel, alpha-2 integrin mediated antiangiogenic properties: results of a phase I study. J Clin Oncol 23:3082 Meeting Abstracts

    Google Scholar 

  7. Mita MM et al (2006) Phase I study of an anti-angiogenic agent with a novel mechanism of action E7820: safety, pharmacokinetics (PK) and pharmacodynamic (PD) studies in patients (pts) with solid tumors. J Clin Oncol 24:3048 Meeting Abstractsdoi:10.1200/JCO.2004.00.9720

    Article  Google Scholar 

  8. FDA (1999) Guidance for industry: population pharmacokinetics.

  9. Guo F, Letrent SP, Sharma A (2007) Population pharmacokinetics of a HER2 tyrosine kinase inhibitor CP-724,714 in patients with advanced malignant HER2 positive solid tumors. Cancer Chemother Pharmacol 60:799–809 doi:10.1007/s00280-007-0427-6

    Article  PubMed  CAS  Google Scholar 

  10. Lee CKK et al (2006) Population pharmacokinetics of troxacitabine, a novel dioxolane nucleoside analogue. Clin Cancer Res 12:2158–2165 doi:10.1158/1078-0432.CCR-05-2249

    Article  PubMed  CAS  Google Scholar 

  11. Urien S, Rezaí K, Lokiec F (2005) Pharmacokinetic modelling of 5-FU production from capecitabine—a population study in 40 adult patients with metastatic cancer. J Pharmacokinet Pharmacodyn 32:817–833 doi:10.1007/s10928-005-0018-2

    Article  PubMed  CAS  Google Scholar 

  12. Urien S et al (2003) Phase I population pharmacokinetics of irofulven. Anticancer Drugs 14:353–358 doi:10.1097/00001813-200306000-00005

    Article  PubMed  CAS  Google Scholar 

  13. van Kesteren C et al (2002) Development and validation of limited sampling strategies for prediction of the systemic exposure to the novel anticancer agent E7070 (N-(3-chloro-7-indolyl)-1,4-benzenedisulphonamide). Br J Clin Pharmacol 54:463–471 doi:10.1046/j.1365-2125.2002.01684.x

    Article  PubMed  Google Scholar 

  14. Nguyen L et al (2002) Population pharmacokinetics model and limited sampling strategy for intravenous vinorelbine derived from phase I clinical trials. Br J Clin Pharmacol 53:459–468 doi:10.1046/j.1365-2125.2002.01581.x

    Article  PubMed  CAS  Google Scholar 

  15. Crul M et al (2002) Population pharmacokinetics of the novel anticancer agent KRN7000. Cancer Chemother Pharmacol 49:287–293 doi:10.1007/s00280-001-0413-3

    Article  PubMed  CAS  Google Scholar 

  16. Tanswell P et al (2001) Population pharmacokinetics of antifibroblast activation protein monoclonal antibody F19 in cancer patients. Br J Clin Pharmacol 51:177–180 doi:10.1111/j.1365-2125.2001.01335.x

    Article  PubMed  CAS  Google Scholar 

  17. Zhou H et al (2000) Population pharmacokinetics/toxicodynamics (PK/TD) relationship of SAM486A in phase I studies in patients with advanced cancers. J Clin Pharmacol 40:275–283 doi:10.1177/00912700022008946

    Article  PubMed  CAS  Google Scholar 

  18. Thomson AH et al (1999) Population pharmacokinetics in phase I drug development: a phase I study of PK1 in patients with solid tumours. Br J Cancer 81:99–107 doi:10.1038/sj.bjc.6690657

    Article  PubMed  CAS  Google Scholar 

  19. FDA (2000) Good laboratory practice for nonclinical laboratory studies

  20. FDA (2002) Guidance for industry: food-effect bioavailability and fed bioequivalence studies

  21. Pinheiro JC, Bates DM (2000) Mixed-effect models in S and S-Plus. Springer, Berlin Heidelberg New York

    Google Scholar 

  22. Beal SL, Sheiner LB (1989) NONMEM users guides. Icon Development Solutions, Ellicott City, Maryland, USA

  23. Soy D, Beal SL, Sheiner LB (2004) Population one-compartment pharmacokinetic analysis with missing dosage data. Clin Pharmacol Ther 76:441–451 doi:10.1016/j.clpt.2004.07.010

    Article  PubMed  CAS  Google Scholar 

  24. Byon W, Fletcher CV, Brundage RC (2008) Impact of censoring data below an arbitrary quantification limit on structural model misspecification. J Pharmacokinet Pharmacodyn 35(1):101–116 (Feb)

    Google Scholar 

  25. Beal SL (2001) Ways to fit a PK model with some data below the quantification limit. J Pharmacokinet Pharmacodyn 28:481–504 doi:10.1023/A:1012299115260

    Article  PubMed  CAS  Google Scholar 

  26. Abramowitz M, Stegun IA (1972) Handbook of mathematical functions. National Bureau of Standards, Washington

    Google Scholar 

  27. Karlsson MO, Savic RM (2007) Diagnosing model diagnostics. Clin Pharmacol Ther 82:17–20 doi:10.1038/sj.clpt.6100241

    Article  PubMed  CAS  Google Scholar 

  28. Savic RM, Jonker DM, Kerbusch T, Karlsson MO (2007) Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies. J Pharmacokinet Pharmacodyn 34(5):711–726 (Oct)

    Article  PubMed  CAS  Google Scholar 

  29. Lindbom L, Pihlgren P, Jonsson EN (2005) PsN-Toolkit—a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed 79:241–257 doi:10.1016/j.cmpb.2005.04.005

    Article  PubMed  Google Scholar 

  30. Jonsson EN, Karlsson O (1999) Xpose—an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM. Comput Methods Programs Biomed 58:51–64 doi:10.1016/S0169-2607(98)00067-4

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ron J. Keizer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Keizer, R.J., Zamacona, M.K., Jansen, M. et al. Application of population pharmacokinetic modeling in early clinical development of the anticancer agent E7820. Invest New Drugs 27, 140–152 (2009). https://doi.org/10.1007/s10637-008-9164-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10637-008-9164-x

Keywords

Navigation