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Pharmacodynamic modeling of chemotherapeutic effects: Application of a transit compartment model to characterize methotrexate effects in vitro

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Abstract

The time course of chemotherapeutic effect is often delayed relative to the time course of chemotherapeutic exposure. In many cases, this delay is difficult to characterize mathematically through the use of standard pharmacodynamic models. In the present work, we investigated the relationship between methotrexate (MTX) exposure and the time course of MTX effects on tumor cell growth in culture. Two cancer cell lines, Ehrlich ascites cells and sarcoma 180 cells, were exposed for 24 hours to MTX concentrations that varied more than 700-fold (0.19–140 μg/mL). Viable cells were counted on days 1, 3, 5, 7, 9, 11, 13, 15, 17, 20, 22, and 24 for Ehrlich ascites cells and on days 1, 2, 3, 5, 7, 9, 11, 13, 14, 15, 17, 19, and 21 for sarcoma 180 cells, through the use of a tetrazolium assay. Although MTX was removed 24 hours after application, cell numbers reached nadir values more than 100 hours after MTX exposure. Data from each cell line were fitted to 3 pharmacodynamic models of chemotherapeutic cell killing: a cell cycle phase-specific model, a phase-nonspecific model, and a transit compartment model (based on the general model recently reported by Mager and Jusko, Clin Pharmacol Ther. 70:210–216, 2001). The transit compartment model captured the data much more accurately than the standard pharmacodynamic models, with correlation coefficients ranging from 0.86 to 0.999. This report shows the successful application of a transit compartment model for characterization of the complex time course of chemotherapeutic effects; such models may be very useful in the development of optimization strategies for cancer chemotherapy.

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References

  1. Lokich J, Anderson N. Dose intensity for bolus versus infusion chemotherapy administration: review of the literature for 27 anti-neoplastic agents. Ann Oncol. 1997;8:15–25.

    Article  CAS  PubMed  Google Scholar 

  2. Aisner J, Van Echo DA, Whitacre M, Wiernik PH. A phase I trial of continuous infusion VP16-213 (etoposide). Cancer Chemother Pharmacol. 1982;7:157–160.

    Article  CAS  PubMed  Google Scholar 

  3. Frei ED, Bickers JN, Hewlett JS, et al. Dose schedule and antitumor studies of arabinosyl cytosine (NSC 63878). Cancer Res. 1969;29:1325–1332.

    CAS  PubMed  Google Scholar 

  4. Wiernik PH, Schwartz EL, Strauman JJ, et al. Phase I clinical and pharmacokinetic study of taxol. Cancer Res. 1987;47:2486–2493.

    CAS  PubMed  Google Scholar 

  5. O Dwyer PJ, Hudes GR, Walczak J, et al. Phase I and pharmacokinetic study of the novel platinum analogue CI-973 on a 5-daily dose schedule. Cancer Res. 1992;52:6746–6753.

    CAS  Google Scholar 

  6. Minami H, Sasaki Y, Saijo N, et al. Indirect-response model for the time course of leukopenia with anticancer drugs. Clin Pharmacol Ther. 1998;64:511–521.

    Article  CAS  PubMed  Google Scholar 

  7. Minami H, Sasaki Y, Watanabe T, Ogawa M. Pharmacodynamic modeling of the entire time course of leukopenia after a 3-hour infusion of paclitaxel. Jpn J Cancer Res. 2001;92:231–238.

    Article  CAS  PubMed  Google Scholar 

  8. Friberg LE, Freijs A, Sandstrom M, Karlsson MO. Semiphysiological model for the time course of leukocytes after varying schedules of 5-fluorouracil in rats. J Pharmacol Exp Ther. 2000;295:734–740.

    CAS  PubMed  Google Scholar 

  9. Jodrell DI, Egorin MJ, Canetta RM, et al. Relationships between carboplatin exposure and tumor response and toxicity in patients with ovarian cancer. J Clin Oncol. 1992;10:520–528.

    CAS  PubMed  Google Scholar 

  10. Stewart CF, Baker SD, Heideman RL, et al. Clinical pharmacodynamics of continuous infusion topotecan in children: systemic exposure predicts hematologic toxicity. J Clin Oncol. 1994;12:1946–1954.

    CAS  PubMed  Google Scholar 

  11. Cellarier E, Terret C, Labarre P, et al. Pharmacokinetic study of cystemustine, administered on a weekly schedule in cancer patients. Ann Oncol. 2002;13:760–769.

    Article  CAS  PubMed  Google Scholar 

  12. Van Kesteren C, Mathot RA, Raymond E, et al. Population pharmacokinetics and pharmacokinetic-pharmacodynamic relationships of the novel anticancer agent E7070 in four phase I studies. Br J Clin Pharmacol. 2002;53:553P.

    Google Scholar 

  13. Zhou H, Choi L, Lau H, et al. Population pharmacokinetics/toxicodynamics (PK/TD) relationship of SAM486A in phase I studies in patients with advanced cancers. J Clin Pharmacol. 2000;40:275–283.

    Article  CAS  PubMed  Google Scholar 

  14. Gimmel S, Maurer HR. Growth kinetics of L1210 leukemic cells exposed to different concentration courses of methotrexate in vitro. Cancer Chemother Pharmacol. 1994;34:351–355.

    Article  CAS  PubMed  Google Scholar 

  15. Braakhuis BJ, Ruiz van Haperen VW, Boven E, et al. Schedule-dependent antitumor effect of gemcitabine in in vivo model system. Semin Oncol. 1995;22:42–46.

    CAS  PubMed  Google Scholar 

  16. Kishi S, Goto N, Nakamura T, Ueda T. Evaluation of cell-killing effects of 1-beta-D-arabinofuranosylcytosine and daunorubicin by a new computer-controlled in vitro pharmacokinetic simulation system. Cancer Res. 1999;59:2629–2634.

    CAS  PubMed  Google Scholar 

  17. Mager DE, Jusko WJ. Pharmacodynamic modeling of time-dependent transduction systems. Clin Pharmacol Ther. 2001;70:210–216.

    Article  CAS  PubMed  Google Scholar 

  18. Jusko WJ. Pharmacodynamics of chemotherapeutic effects: dose-time-response relationships for phase-nonspecific agents. J Pharm Sci. 1971;60:892–895.

    Article  CAS  PubMed  Google Scholar 

  19. Jusko WJ. A pharmacodynamic model for cell-cycle-specific chemotherapeutic agents. J Pharmacokin Biopharm. 1973;1:175–200.

    Article  CAS  Google Scholar 

  20. Sun YN, Jusko WJ. Transit compartments versus gamma distribution function to model signal transduction processes in pharmacodynamics. J Pharm Sci. 1998;87:732–737.

    Article  CAS  PubMed  Google Scholar 

  21. Tada H, Shiho O, Kuroshima K, et al. An improved colorimetric assay for interleukin 2. J Immunol Methods. 1986;93:157–165.

    Article  CAS  PubMed  Google Scholar 

  22. D Argenio DZ, Schumitzky A. ADAPT II Users Guide: Pharmacokinetic/Pharmacodynamic Systems Analysis Software. Los Angeles, CA: Biomedical Simulations Resource; 1997.

    Google Scholar 

  23. Levasseur LM, Slocum HK, Rustum YM, Greco WR. Modeling of the time-dependency of in vitro drug cytotoxicity and resistance. Cancer Res. 1998;58:5749–5761.

    CAS  PubMed  Google Scholar 

  24. Hassan SB, Jonsson E, Larsson R, Karlsson MO. Model for time dependency of cytotoxic effect of CHS 828 in vitro suggests two different mechanisms of action. J Pharmacol Exp Ther. 2001;299:1140–1147.

    CAS  PubMed  Google Scholar 

  25. Rodman JH, Relling MV, Stewart CF, et al. Clinical pharmacokinetics and pharmacodynamics of anticancer drugs in children. Semin Oncol. 1993;20:18–29.

    CAS  PubMed  Google Scholar 

  26. Evans WE, Relling MV, Rodman JH, et al. Conventional compared with individualized chemotherapy for childhood acute lymphoblastic leukemia. N Engl J Med. 1998;338:499–505.

    Article  CAS  PubMed  Google Scholar 

  27. Sheiner LB, Stanski DR, Vozeh S, et al. Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine. Clin Pharmacol Ther. 1979;25:358–371.

    Article  CAS  PubMed  Google Scholar 

  28. Dayneka NL, Garg V, Jusko WJ. Comparison of four basic models of indirect pharmacodynamic responses. J Pharmacokinet Biopharm. 1993;21:457–478.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Labat C, Mansour K, Malmary MF, et al. Chronotoxicity of methotrexate in mice after intraperitoneal administration. Chronobiologia. 1987;14:267–275.

    CAS  PubMed  Google Scholar 

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Correspondence to Joseph P. Balthasar.

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Published October 29, 2002

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Lobo, E.D., Balthasar, J.P. Pharmacodynamic modeling of chemotherapeutic effects: Application of a transit compartment model to characterize methotrexate effects in vitro. AAPS J 4, 42 (2002). https://doi.org/10.1208/ps040442

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  • DOI: https://doi.org/10.1208/ps040442

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