Abstract
A mathematical model of leukaemia therapy based on the Gompertzian law of cell growth is investigated. The effect of the medicine on the leukaemia and normal cells is described in terms of therapy functions. A feedback control problem with the purpose of minimizing the number of the leukaemia cells while retaining as much as possible the number of normal cells is considered. This problem is reduced to solving the nonlinear Hamilton–Jacobi–Bellman partial differential equation. The feedback control synthesis is obtained by constructing an exact analytical solution to the corresponding Hamilton–Jacobi–Bellman equation.
Similar content being viewed by others
References
Aranjo, R.P., Mcelwain, D.G.: A history of the study of solid tumour growth: the contribution of mathematical modelling. Bull. Math. Biol. 66, 1039–1091 (2004)
Afenya, E.K.: Mathematical models of cancer and their relevant insights. In: Tan, W.-Y., Hanin, L. (eds.) Handbook of Cancer Models with Applications. Ser. Math. Biology and Medicine, vol. 9, pp. 173–223. World Scientific, Singapore (2008)
Rubinow, S.I., Lebowitz, J.L.: A mathematical model of neutrophil production and control in normal man. J. Math. Biol. 1, 187–225 (1975)
Rubinow, S.I., Lebowitz, J.L.: A mathematical model of the acute myeloblastic leukemic state in man. Biophys. J. 16, 897–910 (1976)
Rubinow, S.I., Lebowitz, J.L.: A mathematical model of the chemotherapeutic treatment of acute myeloblastic leukemia. Biophys. J. 16, 1257–1271 (1976)
Swan, G.W., Vincent, T.L.: Optimal control analysis in the chemotherapy of IgG multiple myeloma. Bull. Math. Biol. 39, 317–337 (1977)
Afenya, E.K., Calderón, C.P.: A brief look at a normal cell decline and inhibition in acute leukemia. J. Can. Det. Prev. 20(3), 171–179 (1996)
Frenzen, C.L., Murray, J.D.: A cell kinetics justification for Gompertz equation. SIAM J. Appl. Math. 46, 614–624 (1986)
Gyllenberg, M., Webb, G.F.: Quiescence as an explanation of Gompertzian tumor growth. Growth Dev. Aging 53, 25–33 (1989)
Kendal, W.S.: Gompertzian growth as a consequence of tumor heterogeneity. Math. Biosci. 73, 103–107 (1985)
Laird, A.K.: Dynamics of tumor growth: comparison of growth and cell population dynamics. Math. Biosci. 185, 153–167 (2003)
Guiot, C., Degiorgis, P.G., Delsanto, P.P., Gabriele, P., Deisboeck, T.S.: Does tumour growth follow a universal law? J. Theor. Biol. 225, 147–151 (2003)
Afenya, E.K.: Acute leukemia and chemotherapy: a modeling viewpoint. Math. Biosci. 138, 79–100 (1996)
Antipov, A.V., Bratus, A.S.: Mathematical model of optimal chemotherapy strategy with allowance for cell population dynamics in a heterogenous tumor. Comput. Math. Math. Phys. 49(11), 1825–1836 (2009)
Afenya, E.K., Bentil, D.E.: Models of acute myeloblastic leukemia and its chemotherapy. In: Computational Medicine. Public Health and Biotechnology, Part I, p. 397. World Scientific, New Jersey (1995)
Zietz, S., Nicolini, C.: Mathematical approaches to optimization of cancer chemotherapy. Bull. Math. Biol. 41, 305–324 (1979)
Costa, S.M.I., Boldrini, J.L., Bassanezi, R.C.: Chemotherapeutic treatments involving drug resistance and level of normal cells as criterion of toxicity. Math. Biosci. 125, 211–228 (1995)
Engelhart, M., Lebiedz, D., Sager, S.: Optimal control for selected cancer chemotherapy ODE models: a view on the potential of optimal schedules and choice of objective function. Math. Biosci. 229, 123–134 (2001)
Ledzewicz, U., Schaettler, H., Marriot, J., Maurer, H.: Realizable protocols for optimal administration of drugs in mathematical models for anti-angiogenic treatment. Math. Med. Biol. 27, 159–179 (2010)
Pontryagin, L.S., Boltyanskii, V.G., Gamkrelidze, R.V., Mishchenko, E.F.: The Mathematical Theory of Optimal Processes. Wiley, New York (1962)
Iourtchenko, D.V.: Solution to a class of stochastic LQ problems with bounded control. Automatica 45, 1439–1442 (2009)
Iourtchenko, D.V., Menaldi, J., Bratus, A.S.: On the LQG theory with bounded control. Nonlinear Differ. Equ. Appl. 17(5), 527–534 (2010)
Bratus, A.S., Chumerina, E.S.: Optimal control synthesis in therapy of solid tumor growth. Comput. Math. Math. Phys. 48(6), 892–911 (2008)
Chumerina, E.S.: Choice of optimal strategy of tumor chemotherapy in Gompertz model. J. Comput. Syst. Sci. Int. 48(2), 325–331 (2009)
Bratus, A.S., Zaychic, S.Y.: Smooth solution of the Hamilton–Jacobi–Bellman equation in mathematical model of optimal treatment of viral infection. Differ. Equ. 46(11), 1571–1583 (2010)
Bratus, A.S., Volosov, K.A.: Exact solution to the Hamilton–Jacobi–Bellman equation for optimal correction with an integral constraint on the total resource of control. Dokl. Math. 66(1), 148–151 (2002)
Bratus, A.S., Fimmel, E., Todorov, Y., Semenov, Y.S., Nuernberg, F.: On strategies on a mathematical model for leukemia therapy. Nonlinear Anal., Real World Appl. 13, 1044–1059 (2012)
Todorov, Y., Fimmel, E., Bratus, A.S., Semenov, Y.S., Nuernberg, F.: An optimal strategy for leukemia therapy: a multi-objective approach. Russ. J. Numer. Anal. Math. Model. 26(6), 589–604 (2011)
Melikyan, A.A.: Singular characteristics of Hamilton–Jacobi–BellmanI equation in state constraint optimal control problems. In: Preprints of IFAC Symposium: Modeling and Control of Economic System, Klagenfert, Austria, vol. 68, pp. 155–156 (2001)
Fleming, W.H., Soner, H.M.: Controlled Markov Processes and Viscosity Solutions. Springer, Berlin (2006)
Subbotina, N.N.: The method of characteristics for Hamilton–Jacobi equations and applications to dynamical optimization. J. Math. Sci. 135(3), 2955–3091 (2006)
Afenya, E.K.: Acute leukemia and chemotherapy: a modeling viewpoint. Math. Biosci. 138, 79–100 (1996)
Acknowledgements
The first author contributed to this paper while visiting Heriot-Watt University as a Distinguished Visiting Professor of the Royal Academy of Engineers. This support is highly appreciated.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bratus, A., Todorov, Y., Yegorov, I. et al. Solution of the Feedback Control Problem in the Mathematical Model of Leukaemia Therapy. J Optim Theory Appl 159, 590–605 (2013). https://doi.org/10.1007/s10957-013-0324-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10957-013-0324-6