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A multiple time-scale computational model of a tumor and its micro environment
On optimal and suboptimal treatment strategies for a mathematical model of leukemia
1. | Mannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163 Mannheim, Germany |
2. | Moscow State University of Railway Engineering, Obraztsova 15, Moscow, 127994, Russian Federation, Russian Federation |
References:
[1] |
E. K. Afenya and D. E. Bentil, Models of acute myeloblastic leukemia and its chemotherapy,, in, (1995). Google Scholar |
[2] |
E. K. Afenya, Cancer treatment strategies and mathematical modeling,, in, (1998), 1. Google Scholar |
[3] |
E. K. Afenya and C. P. Calderón, Modeling disseminated cancers: A review of mathematical models,, Comm. Theor. Biol., 8 (2003), 225.
doi: 10.1080/08948550302449. |
[4] |
E. K. Afenya and C. P. Calderón, A brief look at a normal cell decline and inhibition in acute leukemia,, J. Can. Det. Prev., 20 (1996), 171. Google Scholar |
[5] |
E. K. Afenya, Acute leukemia and chemotherapy: a modeling viewpoint,, Math. Biosci., 138 (1996), 79.
doi: 10.1016/S0025-5564(96)00086-7. |
[6] |
A. V. Antipov and A. S. Bratus', Mathematical model of optimal chemotherapy strategy with allowance for cell population dynamics in a heterogeneous tumor,, Zh. Vychisl. Mat. Mat. Fiz., 49 (2009), 1907.
|
[7] |
A. S. Bratus, E. Fimmel, Y. Todorov, Y. S. Semenov and F. Nürnberg, On strategies on a mathematical model for leukemia therapy,, Nonlinear Analysis: Real World Applications, 13 (2012), 1044.
doi: 10.1016/j.nonrwa.2011.02.027. |
[8] |
B. D. Clarkson, Acute myelocytic leukemia in adults,, Cancer, 30 (1972), 1572.
doi: 10.1002/1097-0142(197212)30:6<1572::AID-CNCR2820300624>3.0.CO;2-M. |
[9] |
B. Djulbegovic and S. Svetina, Mathematical model of acute myeloblastic leukemia: an investigation of a relevant kinetic parameters,, Cell Tissue Kinet., 18 (1985), 307. Google Scholar |
[10] |
M. Engelhart, D. Lebiedz and S. Sager, Optimal control for selected cancer chemotherapy ODE models: A view on the potential of optimal schedules and choice of objective function,, Mathematical Biosciences, 229 (2011), 123.
doi: 10.1016/j.mbs.2010.11.007. |
[11] |
A. F. Filippov, "Differential Equations with Discontinuous Righthand Sides,", Springer, (1988).
|
[12] |
K. R. Fister and J. C. Panetta, Optimal control applied to competing chemotherapeutic cell-kill strategies,, SIAM Journal on Applied Mathematics, 63 (2003), 1954.
doi: 10.1137/S0036139902413489. |
[13] |
K. R. Fister and J. C. Panetta, Optimal control applied to cell-cycle-specific cancer chemotherapy,, SIAM Journal on Applied Mathematics, 60 (2000), 1059.
doi: 10.1137/S0036139998338509. |
[14] |
C. L. Frenzen and J. D. Murray:, A cell kinetics justification for Gompertz equation,, SIAM J. Appl. Math., 46 (1986), 614.
doi: 10.1137/0146042. |
[15] |
C. Guiot, P. G. Degiorgis, P. P. Delsanto, P. Gabriele and T. S. Deisboeck, Does tumour growth follow a universal law?,, J. Theor. Biol., 225 (2003), 147.
doi: 10.1016/S0022-5193(03)00221-2. |
[16] |
"Handbook of Cancer Models with Applications," (W.-Y. Tan, L. Hanin Eds.), Ser. Math. Biology and Medicine;, World Scientific. Vol. 9, (2008). Google Scholar |
[17] |
N. H. G. Holford and L. B. Sheiner, Understanding the dose-effect relationship-clinical application of pharmacokinetic-pharmacodynamic models,, Clin. Pharmacokin, 6 (1981), 429.
doi: 10.2165/00003088-198106060-00002. |
[18] |
D. E. Kirk, "Optimal Contol Theory: An Introduction,", Prentice-Hall, (1970). Google Scholar |
[19] |
U. Ledzewicz, A. d'Onofrio, H. Maurer and H. Schaettler, On optimal delivery of combination therapy for tumors,, Mathematical Biosciences, 222 (2009), 13.
doi: 10.1016/j.mbs.2009.08.004. |
[20] |
U. Ledzewicz and H. Schaettler, Optimal controls for a model with pharmacokinetics maximizing bone marrow in cancer chemotherapy,, Mathematical Biosciences, 206 (2007), 320.
doi: 10.1016/j.mbs.2005.03.013. |
[21] |
A. S. Matveev and A. V. Savkin, Optimal control regimens: influence of tumours on normal cells and several toxicity constraints,, IMA J. Math. Appl. Med. Biol., 18 (2001), 25.
doi: 10.1093/imammb/18.1.25. |
[22] |
L. Norton and R. Simon, The Norton-Simon Hypothesis: designing more effective and less toxic chemotherapeutic regimens,, Nature Clinical Practice, 3 (2006). Google Scholar |
[23] |
L. Norton and R. Simon, Tumor size, sensitivity to therapy, and design of treatment schedules,, Cancer Treat Rep., 61 (1977), 1307. Google Scholar |
[24] |
J. C. Panetta, A mathematical model of breast and ovarian cancer treated with paclitaxel,, Mathematical Biosciences, 146 (1997), 89.
doi: 10.1016/S0025-5564(97)00077-1. |
[25] |
S. I. Rubinow and J. L. Lebowitz, A mathematical model of the acute myeloblastic leukemic state in man,, Biophys. J., 16 (1976), 897.
doi: 10.1016/S0006-3495(76)85740-2. |
[26] |
F. Schabel, Jr., H. Skipper and W. Wilcox, Experimental evaluation of potential anti-cancer agents. XIII. On the criteria and kinetics associated with curability of experimental leukemia,, Cancer Chemo. Rep., 25 (1964), 1. Google Scholar |
[27] |
L. B. Sheiner and N. H. G. Holford, Determination of maximum effect,, Clin. Pharmacology & Therapeutics, 71 (2002).
doi: 10.1067/mcp.2002.122277. |
[28] |
G. W. Swan and T. L. Vincent, Optimal control analysis in the chemotherapy of IgG multiple myeloma,, Bull. Math. Biol., 39 (1977), 317. Google Scholar |
[29] |
Y. Todorov, E. Fimmel, A. S. Bratus, Y. S. Semenov and F. Nürnberg, An optimal strategy for leukemia therapy: A multi-objective approach,, Russian Journal of Numerical Analysis and Mathematical Modelling, 26 (2011), 589.
|
show all references
References:
[1] |
E. K. Afenya and D. E. Bentil, Models of acute myeloblastic leukemia and its chemotherapy,, in, (1995). Google Scholar |
[2] |
E. K. Afenya, Cancer treatment strategies and mathematical modeling,, in, (1998), 1. Google Scholar |
[3] |
E. K. Afenya and C. P. Calderón, Modeling disseminated cancers: A review of mathematical models,, Comm. Theor. Biol., 8 (2003), 225.
doi: 10.1080/08948550302449. |
[4] |
E. K. Afenya and C. P. Calderón, A brief look at a normal cell decline and inhibition in acute leukemia,, J. Can. Det. Prev., 20 (1996), 171. Google Scholar |
[5] |
E. K. Afenya, Acute leukemia and chemotherapy: a modeling viewpoint,, Math. Biosci., 138 (1996), 79.
doi: 10.1016/S0025-5564(96)00086-7. |
[6] |
A. V. Antipov and A. S. Bratus', Mathematical model of optimal chemotherapy strategy with allowance for cell population dynamics in a heterogeneous tumor,, Zh. Vychisl. Mat. Mat. Fiz., 49 (2009), 1907.
|
[7] |
A. S. Bratus, E. Fimmel, Y. Todorov, Y. S. Semenov and F. Nürnberg, On strategies on a mathematical model for leukemia therapy,, Nonlinear Analysis: Real World Applications, 13 (2012), 1044.
doi: 10.1016/j.nonrwa.2011.02.027. |
[8] |
B. D. Clarkson, Acute myelocytic leukemia in adults,, Cancer, 30 (1972), 1572.
doi: 10.1002/1097-0142(197212)30:6<1572::AID-CNCR2820300624>3.0.CO;2-M. |
[9] |
B. Djulbegovic and S. Svetina, Mathematical model of acute myeloblastic leukemia: an investigation of a relevant kinetic parameters,, Cell Tissue Kinet., 18 (1985), 307. Google Scholar |
[10] |
M. Engelhart, D. Lebiedz and S. Sager, Optimal control for selected cancer chemotherapy ODE models: A view on the potential of optimal schedules and choice of objective function,, Mathematical Biosciences, 229 (2011), 123.
doi: 10.1016/j.mbs.2010.11.007. |
[11] |
A. F. Filippov, "Differential Equations with Discontinuous Righthand Sides,", Springer, (1988).
|
[12] |
K. R. Fister and J. C. Panetta, Optimal control applied to competing chemotherapeutic cell-kill strategies,, SIAM Journal on Applied Mathematics, 63 (2003), 1954.
doi: 10.1137/S0036139902413489. |
[13] |
K. R. Fister and J. C. Panetta, Optimal control applied to cell-cycle-specific cancer chemotherapy,, SIAM Journal on Applied Mathematics, 60 (2000), 1059.
doi: 10.1137/S0036139998338509. |
[14] |
C. L. Frenzen and J. D. Murray:, A cell kinetics justification for Gompertz equation,, SIAM J. Appl. Math., 46 (1986), 614.
doi: 10.1137/0146042. |
[15] |
C. Guiot, P. G. Degiorgis, P. P. Delsanto, P. Gabriele and T. S. Deisboeck, Does tumour growth follow a universal law?,, J. Theor. Biol., 225 (2003), 147.
doi: 10.1016/S0022-5193(03)00221-2. |
[16] |
"Handbook of Cancer Models with Applications," (W.-Y. Tan, L. Hanin Eds.), Ser. Math. Biology and Medicine;, World Scientific. Vol. 9, (2008). Google Scholar |
[17] |
N. H. G. Holford and L. B. Sheiner, Understanding the dose-effect relationship-clinical application of pharmacokinetic-pharmacodynamic models,, Clin. Pharmacokin, 6 (1981), 429.
doi: 10.2165/00003088-198106060-00002. |
[18] |
D. E. Kirk, "Optimal Contol Theory: An Introduction,", Prentice-Hall, (1970). Google Scholar |
[19] |
U. Ledzewicz, A. d'Onofrio, H. Maurer and H. Schaettler, On optimal delivery of combination therapy for tumors,, Mathematical Biosciences, 222 (2009), 13.
doi: 10.1016/j.mbs.2009.08.004. |
[20] |
U. Ledzewicz and H. Schaettler, Optimal controls for a model with pharmacokinetics maximizing bone marrow in cancer chemotherapy,, Mathematical Biosciences, 206 (2007), 320.
doi: 10.1016/j.mbs.2005.03.013. |
[21] |
A. S. Matveev and A. V. Savkin, Optimal control regimens: influence of tumours on normal cells and several toxicity constraints,, IMA J. Math. Appl. Med. Biol., 18 (2001), 25.
doi: 10.1093/imammb/18.1.25. |
[22] |
L. Norton and R. Simon, The Norton-Simon Hypothesis: designing more effective and less toxic chemotherapeutic regimens,, Nature Clinical Practice, 3 (2006). Google Scholar |
[23] |
L. Norton and R. Simon, Tumor size, sensitivity to therapy, and design of treatment schedules,, Cancer Treat Rep., 61 (1977), 1307. Google Scholar |
[24] |
J. C. Panetta, A mathematical model of breast and ovarian cancer treated with paclitaxel,, Mathematical Biosciences, 146 (1997), 89.
doi: 10.1016/S0025-5564(97)00077-1. |
[25] |
S. I. Rubinow and J. L. Lebowitz, A mathematical model of the acute myeloblastic leukemic state in man,, Biophys. J., 16 (1976), 897.
doi: 10.1016/S0006-3495(76)85740-2. |
[26] |
F. Schabel, Jr., H. Skipper and W. Wilcox, Experimental evaluation of potential anti-cancer agents. XIII. On the criteria and kinetics associated with curability of experimental leukemia,, Cancer Chemo. Rep., 25 (1964), 1. Google Scholar |
[27] |
L. B. Sheiner and N. H. G. Holford, Determination of maximum effect,, Clin. Pharmacology & Therapeutics, 71 (2002).
doi: 10.1067/mcp.2002.122277. |
[28] |
G. W. Swan and T. L. Vincent, Optimal control analysis in the chemotherapy of IgG multiple myeloma,, Bull. Math. Biol., 39 (1977), 317. Google Scholar |
[29] |
Y. Todorov, E. Fimmel, A. S. Bratus, Y. S. Semenov and F. Nürnberg, An optimal strategy for leukemia therapy: A multi-objective approach,, Russian Journal of Numerical Analysis and Mathematical Modelling, 26 (2011), 589.
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