Skip to main content

Advertisement

SpringerLink
Log in

Integrated Pharmacokinetic-Driven Approach to Screen Candidate Anticancer Drugs for Brain Tumor Chemotherapy

  • Research Article
  • Published:
The AAPS Journal Aims and scope Submit manuscript

Abstract

The goal of the study was to develop an effective screening strategy to select new agents for brain tumor chemotherapy from a series of low molecular weight anticancer agents [ON123x] by the combined use of in silico, in vitro cytotoxicity, and in vitro ADME profiling studies. The results of these studies were cast into a pipeline of tier 1 and tier 2 procedures that resulted in the identification of ON123300 as the lead compound. Of the 154 ON123xx compounds, 13 met tier 1 screening criteria based on physicochemical properties [i.e., MW < 450 Da, predicted log P between 2 and 3.5] and in vitro glioma cell cytotoxicity [i.e., IC50 < 10 μM] and were further tested in tier 2 assays. The tier 2 profiling studies consisted of metabolic stability, MDCK-MDR1 cell permeability and plasma and brain protein binding that were combined to globally assess whether favorable pharmacokinetic properties and brain penetration could be achieved in vivo. In vivo cassette dosing studies were conducted in mice for 12 compounds that permitted examination of in vitro/in vivo relationships that confirmed the suitability of the in vitro assays. A parameter derived from the in vitro assays accurately predicted the extent of drug accumulation in the brain based on the area under the drug concentration–time curve in brain measured in the cassette dosing study (r 2 = 0.920). Overall, the current studies demonstrated the value of an integrated pharmacokinetic-driven approach to identify potentially efficacious agents for brain tumor chemotherapy.

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

Access this article

Log in via an institution

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. Levin VA. Are gliomas preventable? Recent Results Cancer Res. 2007;174:205–15.

    Article  PubMed  CAS  Google Scholar 

  2. Ningaraj NS. Drug delivery to brain tumours: challenges and progress. Expert Opin Drug Deliv. 2006;3(4):499–509.

    Article  PubMed  CAS  Google Scholar 

  3. Motl S, Zhuang Y, Waters CM, Stewart CF. Pharmacokinetic considerations in the treatment of CNS tumours. Clin Pharmacokinet. 2006;45(9):871–903.

    Article  PubMed  CAS  Google Scholar 

  4. Narayanan R, Gunturi SB. In silico ADME modelling: prediction models for blood–brain barrier permeation using a systematic variable selection method. Bioorg Med Chem. 2005;13(8):3017–28.

    Article  PubMed  CAS  Google Scholar 

  5. Gerebtzoff G, Seelig A. In silico prediction of blood–brain barrier permeation using the calculated molecular cross-sectional area as main parameter. J Chem Inf Model. 2006;46(6):2638–50.

    Article  PubMed  CAS  Google Scholar 

  6. Bendels S, Kansy M, Wagner B, Huwyler J. In silico prediction of brain and CSF permeation of small molecules using PLS regression models. Eur J Med Chem. 2008;43(8):1581–92. Epub 2007 Nov 26.

    Article  PubMed  CAS  Google Scholar 

  7. Wang Q, Rager JD, Weinstein K, Kardos PS, Dobson GL, Li J, et al. Evaluation of the MDR-MDCK cell line as a permeability screen for the blood–brain barrier. Int J Pharm. 2005;288(2):349–59. Epub 2004 Dec 15.

    Article  PubMed  CAS  Google Scholar 

  8. Taub ME, Podila L, Ely D, Almeida I. Functional assessment of multiple P-glycoprotein (P-gp) probe substrates: influence of cell line and modulator concentration on P-gp activity. Drug Metab Dispos. 2005;33(11):1679–87.

    Article  PubMed  CAS  Google Scholar 

  9. Vichai V, Kirtikara K. Sulforhodamine B colorimetric assay for cytotoxicity screening. Nat Protoc. 2006;1(3):1112–6.

    Article  PubMed  CAS  Google Scholar 

  10. Yang Z, Zadjura LM, Marino AM, D’Arienzo CJ, Malinowski J, Gesenberg C, et al. Utilization of in vitro Caco-2 permeability and liver microsomal half-life screens in discovering BMS-488043, a novel HIV-1 attachment inhibitor with improved pharmacokinetic properties. J Pharm Sci. 2010;99(4):2135–52.

    PubMed  CAS  Google Scholar 

  11. Stringer R, Nicklin PL, Houston JB. Reliability of human cryopreserved hepatocytes and liver microsomes as in vitro systems to predict metabolic clearance. Xenobiotica. 2008;38(10):1313–29.

    Article  PubMed  CAS  Google Scholar 

  12. Boudinot FD, Jusko WJ. Fluid shifts and other factors affecting plasma protein binding of prednisolone by equilibrium dialysis. J Pharm Sci. 1984;73(6):774–80.

    Article  PubMed  CAS  Google Scholar 

  13. Dow N (2006) Determination of compound binding to plasma proteins. Curr Protoc Pharmacol. Chapter 7:Unit7.5.

    Google Scholar 

  14. Maurer TS, Debartolo DB, Tess DA, Scott DO. Relationship between exposure and nonspecific binding of thirty-three central nervous system drugs in mice. Drug Metab Dispos. 2005;33(1):175–81. Epub 2004 Oct 22.

    Article  PubMed  CAS  Google Scholar 

  15. Obach RS, Baxter JG, Liston TE, Silber BM, Jones BC, MacIntyre F, et al. The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. J Pharmacol Exp Ther. 1997;283(1):46–58.

    PubMed  CAS  Google Scholar 

  16. Iwatsubo T, Hirota N, Ooie T, Suzuki H, Shimada N, Chiba K, et al. Prediction of in vivo drug metabolism in the human liver from in vitro metabolism data. Pharmacol Ther. 1997;73(2):147–71.

    Article  PubMed  CAS  Google Scholar 

  17. Waterhouse RN. Determination of lipophilicity and its use as a predictor of blood–brain barrier penetration of molecular imaging agents. Mol Imaging Biol. 2003;5(6):376–89.

    Article  PubMed  Google Scholar 

  18. van de Waterbeemd H, Gifford E. ADMET in silico modelling: towards prediction paradise? Nat Rev Drug Discov. 2003;2:192–204. Review.

    Article  PubMed  Google Scholar 

  19. Narla RK, Liu XP, Myers DE, Uckun FM. 4-(3′-Bromo-4′hydroxylphenyl)-amino-6,7-dimethoxyquinazoline: a novel quinazoline derivative with potent cytotoxic activity against human glioblastoma cells. Clin Cancer Res. 1998;4(6):1405–14.

    PubMed  CAS  Google Scholar 

  20. Barazzuol L, Jena R, Burnet NG, Jeynes JC, Merchant MJ, Kirkby KJ, et al. In vitro evaluation of combined temozolomide and radiotherapy using x rays and high-linear energy transfer radiation for glioblastoma. Radiat Res. 2012;177(5):651–62.

    Article  PubMed  CAS  Google Scholar 

  21. Luqiu Z, Yiquan K, Gengqiang L, Yijing L, Xiaodan J, Yingqian C. A new design immunotoxin for killing high-grade glioma U87 cells: From in vitro to in vivo. J Immunotoxicol. 2012; 1–6.

  22. Di L, Kerns EH, Carter GT. Strategies to assess blood–brain barrier penetration. Expert Opin Drug Discov. 2008;2(6):677–87. Volume 3, Number 6.

    Article  Google Scholar 

  23. Reichel A. Addressing central nervous system (CNS) penetration in drug discovery: basics and implications of the evolving new concept. Chem Biodivers. 2009;6(11):2030–49.

    Article  PubMed  CAS  Google Scholar 

  24. Hammarlund-Udenaes M, Fridén M, Syvänen S, Gupta A. On the rate and extent of drug delivery to the brain. Pharm Res. 2008;25(8):1737–50.

    Article  PubMed  CAS  Google Scholar 

  25. Read KD, Braggio S. Assessing brain free fraction in early drug discovery. Expert Opin Drug Metab Toxicol. 2010;6(3):337–44.

    Article  PubMed  CAS  Google Scholar 

  26. Zhang MY, Kerns E, McConnell O, Sonnenberg-Reines J, Zaleska MM, Steven Jacobsen J, et al. Brain and plasma exposure profiling in early drug discovery using cassette administration and fast liquid chromatography-tandem mass spectrometry. J Pharm Biomed Anal. 2004;34(2):359–68.

    Article  PubMed  Google Scholar 

  27. He K, Qian M, Wong H, Bai SA, He B, Brogdon B, et al. N-in-1 dosing pharmacokinetics in drug discovery: experience, theoretical and practical considerations. J Pharm Sci. 2008;97:2568–80.

    Article  PubMed  CAS  Google Scholar 

  28. Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J Pharm Sci. 2001;90(6):749–84.

    Article  PubMed  CAS  Google Scholar 

  29. Obach RS. Nonspecific binding to microsomes: impact on scale-up of in vitro intrinsic clearance to hepatic clearance as assessed through examination of warfarin, imipramine, and propranolol. Drug Metab Dispos. 1997;25(12):1359–69.

    PubMed  CAS  Google Scholar 

Download references

Acknowledgment

This work was supported by NIH grant CA127063 [JMG].

Author information

Authors and Affiliations

  1. Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1603, New York, New York, 10029, USA

    Hua Lv, Xiaoping Zhang, Jyoti Sharma & James M. Gallo

  2. Department of Oncological Sciences, Mount Sinai School of Medicine, New York, New York, 10029, USA

    M. V. Ramana Reddy & E. Premkumar Reddy

Authors
  1. Hua Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoping Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jyoti Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. V. Ramana Reddy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. E. Premkumar Reddy
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. James M. Gallo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to James M. Gallo.

Electronic Supplementary Materials

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 15 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lv, H., Zhang, X., Sharma, J. et al. Integrated Pharmacokinetic-Driven Approach to Screen Candidate Anticancer Drugs for Brain Tumor Chemotherapy. AAPS J 15, 250–257 (2013). https://doi.org/10.1208/s12248-012-9428-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1208/s12248-012-9428-4

KEY WORDS

Search

Navigation