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Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain

Email: miguel.sanjuan@urjc.es

Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email: aluo@siue.edu


An Optimal Immunotherapeutic Treatment of HIV Infections to Regain the Targeted CD4$^+$T Cell Count: A Boundary Value Problem Approach

Journal of Applied Nonlinear Dynamics 12(1) (2023) 39--51 | DOI:10.5890/JAND.2023.03.003

Uzzwal Kumar Mallick$^{1}$, Ashrafur Rahman$^{2}$, Md. Haider Ali Biswas$^{1}$, Md. Samsuzzoha$^{3}$, Sankar Kumar Roy$^{4}$

$^{1}$ Mathematics Discipline, Khulna University, Bangladesh

$^{2}$ Department of Mathematics and Statistics, Oakland University, USA

$^{3}$ Department of Mathematics, Swinburne University of Technology, Australia

$^{4}$ Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, India

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Abstract

While cure is rare, a systemic and proper treatment can prolong the lives of HIV positive individuals and keep them healthy. To reduce toxicity and minimize treatment costs an optimal treatment program is critically important. Here we present and study a mathematical model to find an optimal treatment strategy, target-oriented-treatent (TOT), against HIV infections. We highlight the optimization case when a given CD4$^+$ T cells are required in a treatment period. The model demonstrates the viral dynamics in the presence of an immune boosting nutrition and an antiretroviral drug. It is found that the infected virus particles can be made negligible if the label of CD4$^+$T cells remains non-decreasing via treatment. Unlike other studies, boundary conditions are applied on the state variables to find the optimal solution in these regard. The results are confirmed by maximizing the objective functional via Pontryagin's Maximum Principle.

References

  1. [1]  De Cock, K.M. (2001), Epidemiology and the emergence of human immunodeficiency virus and acquired immune deficiency syndrome, Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 356(1410), 795-798.
  2. [2]  Cribb, J. (2001), The origin of acquired immune deficiency syndrome: can science afford to ignore it?, Philosophical Transactions of the Royal Society of London: B, 356, 935-938.
  3. [3]  Martin, B. (2001), The burden of proof and the origin of acquired immune deficiency syndrome, Philosophical Transactions of the Royal Society of London: B, 356(1410), 939-944.
  4. [4]  Lv, R., Li, G., Wu, J., Zhu, Y., Qin, X., and Li, S. (2016), Research on AIDS patients' survival time after highly active antiretroviral therapy, treatment effect and treatment modes, Saudi Pharmaceutical Journal, 24(3), p318-321.
  5. [5]  World Health Organization. (2007), Laboratory Guidelines for enumerating CD4$^+$T Lymphocytes in the context of HIV/AIDS. Retrieved from \\ https://www.who.int/hiv/amds/LaboratoryGuideEnumeratingCD4TLymphocytes.pdf.
  6. [6]  Garcia, F. (2012), Functional cure of HIV infection: the role of immunotherapy, Immunotherapy, 4(3), 245-248.
  7. [7]  Joshi, H.R. (2002), Optimal control of an HIV immunology model, Optimal Control Applications and Methods, 23(4), 199-213.
  8. [8]  Orellana, J.M. (2011), Optimal drug scheduling for HIV therapy efficiency improvement, Biomedical Signal Processing and Control, 6, 379-386.
  9. [9]  Kirschner, D., Lenhart, S., and Serbin, S. (1997), Optimal control of the chemotherapy of HIV, Journal of Mathematical Biology, 35(7), 775-792.
  10. [10]  Perelson, A.S., Kirschner, D.E., and De Boer, R. (1993), Dynamics of HIV infection of CD4$^+$T cells, Mathematical Biosciences, 114(1), 81-125.
  11. [11]  Guo, B. and Sun, B. (2014), Dynamic programming approach to the numerical solution of optimal control with paradigm by a mathematical model for drug therapies of HIV/AIDS, Optimization and Engineering, 15(1), 119-136.
  12. [12]  Nowak, M.A. and May, R.M. (2000), Virus dynamics: mathematical principle of immunology and virology. Oxford University Press, Oxford.
  13. [13]  De Souza, J.F., Caetano, M.A.L., and Yoneyama, T. (2000), Optimal control theory applied to the anti-viral treatment of AIDS, In: Proceedings of the 39th IEEE conference on decision and control, Sydney, Australia, 4839-4844.
  14. [14]  Wein, L.M., Zenios, S.A., and Nowak, M. (1997), Dynamic multidrug therapies for HIV: a control theoretic approach, Journal of Theoretical Biology, 185, 15-29.
  15. [15]  Fatemi, A. and Mahmoodian, H. (2020), Error dynamic shaping in HIV optimized drug delivery control, Evolving Systems, 12(4), 861-874.
  16. [16]  Fleming, W.H. and Rishel, R.W. (1975), Deterministic and stochastic optimal control, Applications of Mathematics, Springer Verlag, New York.
  17. [17]  Pontryagin, L.S., Boltyanskii, V.G., Gamkrelidze, R.V., and Mischenko, E.F. (1962), The Mathematical Theory of Optimal Processes, John Wiley, New York.
  18. [18]  Vinter, R.B. (2000), Optimal Control, Birkhauser, Boston.
  19. [19]  Lenhart, S. and Workman, J.T. (2007), Optimal Control Applied to Biological Models, CRC Press, Taylor and Francis Group, London, UK.
  20. [20]  Biswas, M.H.A., Haque, M.M., and Mallick, U.K. (2019), Optimal control strategy for the immunotherapeutic treatment of HIV infection with state constraint, Optimal Control Applications and Methods, John Wiley $\&$ Sons Limited, 40(4), 807-818.
  21. [21]  HIV Treatment, FDA-Approved HIV Medicines, https://aidsinfo.nih.gov/understanding-hiv-aids/fact-sheets/21/58/fda-approved-hiv-medicines, accessed by June 27, 2020.
  22. [22]  Eisinger, R.W., Folkers, G.K., and Fauci, A.S. (2019), Ending the human immunodeficiency virus pandemic: optimizing the prevention and treatment toolkits, Clinical Infectious Diseases, 69(12), 2212-2227.
  23. [23]  Kirschner, D. and Webb, G.F. (1998), Immunotherapy of HIV-1 infection, Journal of Biological Systems, 6(1), 71-83.
  24. [24]  Fister, K.R., Lenhart, S., and McNally, J.S. (1998), Optimizing chemotherapy in an HIV model, Electronic Journal Differential Equations, 32, 1-12.