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Optimization of Combined Antitumor Chemotherapy with Bevacizumab by Means of Mathematical Modeling

In: Trends in Biomathematics: Modeling, Optimization and Computational Problems

Author

Listed:
  • M. B. Kuznetsov

    (P.N. Lebedev Physical Institute of the Russian Academy of Sciences)

  • A. V. Kolobov

    (P.N. Lebedev Physical Institute of the Russian Academy of Sciences
    Institute of Numerical Mathematics of the Russian Academy of Sciences)

Abstract

Unlike traditional tumor treatment which kills proliferating cells, antiangiogenic therapy is aimed at blocking of angiogenesis, i.e., new blood vessels formation, which should decrease oxygen and nutrients inflow to tumor and thus slow down its growth. It has been found that antiangiogenic drugs have limited anticancer efficiency and cannot completely eradicate tumor when used alone. The first developed antiangiogenic drug bevacizumab is nowadays frequently administered as part of combined therapy together with cytotoxic or cytostatic drugs. However, action of bevacizumab inevitably influences inflow of drugs to the tumor. Therefore, a great challenge concerning such type of combined therapy is the problem of optimal scheduling of chemotherapeutic and antiangiogenic drugs administration in order to maximize resulting antitumor effect and minimize side-effects. With the help of mathematical modeling we compare efficiencies of different schemes of palliative combined chemotherapy with bevacizumab. We suggest a new scheme of drugs administration which may lead to enhanced antitumor effect compared to classical clinical scheme of simultaneous drug administration.

Suggested Citation

  • M. B. Kuznetsov & A. V. Kolobov, 2018. "Optimization of Combined Antitumor Chemotherapy with Bevacizumab by Means of Mathematical Modeling," Springer Books, in: Rubem P. Mondaini (ed.), Trends in Biomathematics: Modeling, Optimization and Computational Problems, pages 347-363, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-91092-5_24
    DOI: 10.1007/978-3-319-91092-5_24
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