Finite duration HIV treatment using mixed antiretroviral therapy and immunotherapy

Nazari, Mostafa; Sharifnia, Mahnaz; Ahmadi, Habib

doi:10.22060/ajme.2020.17988.5880

دانشگاه صنعتی امیرکبیر

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	Finite duration HIV treatment using mixed antiretroviral therapy and immunotherapy
AUT Journal of Mechanical Engineering
مقاله 4، دوره 5، شماره 2، شهریور 2021، صفحه 239-254 اصل مقاله (1.64 M)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/ajme.2020.17988.5880
نویسندگان
Mostafa Nazari^* ¹؛ Mahnaz Sharifnia²؛ Habib Ahmadi²
¹Department of Mechanical Engineering, Shahrood University of Technology, Shahrood, Iran.
²Faculty of mechanical and mechatronics engineering, Shahrood University of Technology
چکیده
Proposing a finite duration HIV treatment strategy is the main goal of the presented paper. Long-term treatments cause many problems, such as drug resistance. Latently infected cells have an important role in HIV dynamics. The used HIV model not only consists of target cells and infected cells and viruses but also includes latently infected cells. It is shown that the initial population of latently infected cells affects the final population of viruses. The dynamics of the model are examined by extracting equilibrium points and their stability. Two types of equilibrium points are derived, virus-free and viral equilibrium points. It is proved that the existence of a stable virus-free equilibrium point is essential for finite duration treatment. Also, the effect of immune system ability in HIV treatment is explored by considering the effect of changing the parameters of the system in its dynamics. It is shown that in some immune system abilities, HIV is cured without any external treatment. The number of equilibrium points of the system changes with changes in the immune system ability. Based on this fact, a novel mixed antiretroviral therapy and immunotherapy are presented. Antiretroviral therapy affects the states of the system, and immunotherapy affects the parameters of the system. The simulation results show the effectiveness of the novel presented treatment strategy.
کلیدواژه‌ها
HIV treatment؛ Antiretroviral therapy؛ Immunotherapy؛ Mathematical model؛ Bifurcation

مراجع
[1] World Health Organization, http://www.who.int, (2017). [2] A.S. Perelson, R.M. Ribeiro, Modeling the within-host dynamics of HIV infection, BMC biology, 11(1) (2013) 96. [3] I.K. Craig, X. Xia, J.W. Venter, Introducing HIV/AIDS education into the electrical engineering curriculum at the University of Pretoria, IEEE Transactions on Education, 47(1) (2004) 65-73. [4] M. Bofill, G. Janossy, C. Lee, D. MacDonald‐Burns, A. Phillips, C. Sabin, A. Timms, M. Johnson, P. Kernoff, Laboratory control values for CD4 and CD8 T lymphocytes. Implications for HIV‐1 diagnosis, Clinical & Experimental Immunology, 88(2) (1992) 243-252. [5] H. Mohri, S. Bonhoeffer, S. Monard, A.S. Perelson, D.D. Ho, Rapid turnover of T lymphocytes in SIV-infected rhesus macaques, Science, 279(5354) (1998) 1223-1227. [6] X. Wei, S.K. Ghosh, M.E. Taylor, V.A. Johnson, E.A. Emini, P. Deutsch, J.D. Lifson, S. Bonhoeffer, M.A. Nowak, B.H. Hahn, Viral dynamics in human immunodeficiency virus type 1 infection, Nature, 373(6510) (1995) 117. [7] A.S. Perelson, P.W. Nelson, Mathematical analysis of HIV-1 dynamics in vivo, SIAM review, 41(1) (1999) 3-44. [8] I. Craig, X. Xia, Can HIV/AIDS be controlled? Applying control engineering concepts outside traditional fields, IEEE Control Systems Magazine, 25(1) (2005) 80-83. [9] H. Wu, Y. Huang, E.P. Acosta, J.-G. Park, S. Yu, S.L. Rosenkranz, D.R. Kuritzkes, J.J. Eron, A.S. Perelson, J.G. Gerber, Pharmacodynamics of antiretroviral agents in HIV-1 infected patients: using viral dynamic models that incorporate drug susceptibility and adherence, Journal of pharmacokinetics and pharmacodynamics, 33(4) (2006) 399-419. [10] M. Barão, J.M. Lemos, Nonlinear control of HIV-1 infection with a singular perturbation model, Biomedical Signal Processing and Control, 2(3) (2007) 248-257. [11] M.-J. Mhawej, C.H. Moog, F. Biafore, C. Brunet-François, Control of the HIV infection and drug dosage, Biomedical signal processing and control, 5(1) (2010) 45-52. [12] K.W. Cherono Pela, Adicka Daniel, Modelling the Effects of Immune Response and Time Delay on HIV-1 in Vivo Dynamics in the Presence of Chemotherapy, Mathematical Modelling and Applications (2019) 15-21. [13] S.N. Vardayani Ratti, Susan K. Eszterhas, Alexandra L. Howell, Dorothy I. Wallace, A mathematical model of HIV dynamics treated with a population of gene-edited haematopoietic progenitor cells exhibiting threshold phenomenon, Mathematical Medicine and Biology, (2019) 1–31. [14] R. Hogg, V. Lima, J. Sterne, S. Grabar, M. Battegay, M. Bonarek, A. D'Arminio Monforte, A. Esteve, M. Gill, R. Harris, Antiretroviral therapy cohort collaboration: life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies, Lancet, 372 (2008) 293-299. [15] A. Sáez-Cirión, C. Bacchus, L. Hocqueloux, V. Avettand-Fenoel, I. Girault, C. Lecuroux, V. Potard, P. Versmisse, A. Melard, T. Prazuck, Post-treatment HIV-1 controllers with a long-term virological remission after the interruption of early initiated antiretroviral therapy ANRS VISCONTI Study, PLoS pathogens, 9(3) (2013) e1003211. [16] O. Lambotte, F. Boufassa, Y. Madec, A. Nguyen, C. Goujard, L. Meyer, C. Rouzioux, A. Venet, J.-F. Delfraissy, S.-H.S. Group, HIV controllers: a homogeneous group of HIV-1—infected patients with spontaneous control of viral replication, Clinical Infectious Diseases, 41(7) (2005) 1053-1056. [17] K.A. O’Connell, J.R. Bailey, J.N. Blankson, Elucidating the elite: mechanisms of control in HIV-1 infection, Trends in pharmacological sciences, 30(12) (2009) 631-637. [18] J.N. Blankson, Effector mechanisms in HIV-1 infected elite controllers: highly active immune responses?, Antiviral research, 85(1) (2010) 295-302. [19] B.D. Walker, Elite control of HIV Infection: implications for vaccines and treatment, Topics in HIV medicine: a publication of the International AIDS Society, USA, 15(4) (2007) 134-136. [20] C. Goujard, I. Girault, C. Rouzioux, C. Lécuroux, C. Deveau, M.-L. Chaix, C. Jacomet, A. Talamali, J.-F. Delfraissy, A. Venet, HIV-1 control after transient antiretroviral treatment initiated in primary infection: role of patient characteristics and effect of therapy, Antiviral therapy, 17(6) (2012) 1001. [21] D.D. Richman, D.M. Margolis, M. Delaney, W.C. Greene, D. Hazuda, R.J. Pomerantz, The challenge of finding a cure for HIV infection, Science, 323(5919) (2009) 1304-1307. [22] N. Chomont, M. El-Far, P. Ancuta, L. Trautmann, F.A. Procopio, B. Yassine-Diab, G. Boucher, M.-R. Boulassel, G. Ghattas, J.M. Brenchley, HIV reservoir size and persistence are driven by T cell survival and homeostatic proliferation, Nature medicine, 15(8) (2009) 893. [23] J. Ananworanich, A. Schuetz, C. Vandergeeten, I. Sereti, M. De Souza, R. Rerknimitr, R. Dewar, M. Marovich, F. Van Griensven, R. Sekaly, Impact of multi-targeted antiretroviral treatment on gut T cell depletion and HIV reservoir seeding during acute HIV infection, PloS one, 7(3) (2012) e33948. [24] J.B. Whitney, A.L. Hill, S. Sanisetty, P. Penaloza-MacMaster, J. Liu, M. Shetty, L. Parenteau, C. Cabral, J. Shields, S. Blackmore, Rapid seeding of the viral reservoir prior to SIV viraemia in rhesus monkeys, Nature, 512(7512) (2014) 74. [25] J. Karrakchou, M. Rachik, S. Gourari, Optimal control and infectiology: application to an HIV/AIDS model, Applied mathematics and computation, 177(2) (2006) 807-818. [26] V. Costanza, P.S. Rivadeneira, F.L. Biafore, C.E. D’Attellis, A closed-loop approach to antiretroviral therapies for HIV infection, Biomedical Signal Processing and Control, 4(2) (2009) 139-148. [27] H. Chang, C.H. Moog, A. Astolfi, P.S. Rivadeneira, A control systems analysis of HIV prevention model using impulsive input, Biomedical Signal Processing and Control, 13 (2014) 123-131. [28] K.R. Fister, S. Lenhart, J.S. McNally, OPTIMIZING CHEMOTHERAPY IN AN HIV MODEL, Electronic Journal of Diﬀerential Equations, 23(4) (2002) 199-213. [29] P. Alan S. , Denise E. , Kirschner , Rob De Boer, Dynamics of HIV infection of CD4+ T cells, Mathematical Biosciences, 114(1) (1993) 81-125. [30] H.R. Joshi, Optimal control of an HIV immunology model, OPTIMAL CONTROL APPLICATIONS AND METHODS, 23 (2002) 199–213. [31] H. Zarei, A.V. Kamyad, A.A. Heydari, Fuzzy modeling and control of HIV infection, Computational and mathematical methods in medicine, 2012 (2012). [32] S.V. Jean Yves Semegni, Nizar Marcus, Kazeem Oare Okosun, Peter Joseph Witbooik,Gbenga Jacob Abiodun∗∗, Sensitivity And Optimal Control Analysis Of HIV/AIDS Model∗, (2019) 606-620. [33] H.M. Cristiana J. Silva, Optimal control of HIV treatment and immunotherapy combination with state and control delays, (2019). [34] A. Sáez-Cirión, C. Bacchus, L. Hocqueloux, V. Avettand-Fenoel, I. Girault, C. Lecuroux, V. Potard, P. Versmisse, A. Melard, T. Prazuck, Post-treatment HIV-1 controllers with a long-term virological remission after the interruption of early initiated antiretroviral therapy ANRS VISCONTI Study, PLoS Pathog, 9(3) (2013) e1003211. [35] A.S. Perelson, A.U. Neumann, M. Markowitz, J.M. Leonard, D.D. Ho, HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time, Science, 271(5255) (1996) 1582-1586. [36] A.S. Perelson, P. Essunger, Y. Cao, M. Vesanen, A. Hurley, K. Saksela, M. Markowitz, D.D. Ho, Decay characteristics of HIV-1-infected compartments during combination therapy, Nature, 387(6629) (1997) 188. [37] B. Adams, H. Banks, M. Davidian, E. Rosenberg, Estimation and prediction with HIV-treatment interruption data, Bulletin of mathematical biology, 69(2) (2007) 563-584. [38] S. Bonhoeffer, M. Rembiszewski, G.M. Ortiz, D.F. Nixon, Risks and benefits of structured antiretroviral drug therapy interruptions in HIV-1 infection, Aids, 14(15) (2000) 2313-2322. [39] B.M. Adams, H.T. Banks, M. Davidian, E.S. Rosenberg, Estimation and prediction with HIV-treatment interruption data, Bulletin of mathematical biology, 69(2) (2007) 563-584. [40] A. Khaitan, D. Unutmaz, Revisiting immune exhaustion during HIV infection, Current HIV/AIDS Reports, 8(1) (2011) 4-11. [41] M.A. Stafford, L. Corey, Y. Cao, E.S. Daar, D.D. Ho, A.S. Perelson, Modeling plasma virus concentration during primary HIV infection, Journal of theoretical biology, 203(3) (2000) 285-301. [42] M. Markowitz, M. Louie, A. Hurley, E. Sun, M. Di Mascio, A.S. Perelson, D.D. Ho, A novel antiviral intervention results in more accurate assessment of human immunodeficiency virus type 1 replication dynamics and T-cell decay in vivo, Journal of virology, 77(8) (2003) 5037-5038. [43] A.T. Haase, K. Henry, M. Zupancic, G. Sedgewick, R.A. Faust, H. Melroe, W. Cavert, K. Gebhard, K. Staskus, Z.-Q. Zhang, Quantitative image analysis of HIV-1 infection in lymphoid tissue, Science, 274(5289) (1996) 985-989. [44] B. Ramratnam, S. Bonhoeffer, J. Binley, A. Hurley, L. Zhang, J.E. Mittler, M. Markowitz, J.P. Moore, A.S. Perelson, D.D. Ho, Rapid production and clearance of HIV-1 and hepatitis C virus assessed by large volume plasma apheresis, The Lancet, 354(9192) (1999) 1782-1785. [45] J.M. Conway, A.S. Perelson, Post-treatment control of HIV infection, Proceedings of the National Academy of Sciences, 112(17) (2015) 5467-5472. [46] L. Rong, A.S. Perelson, Asymmetric division of activated latently infected cells may explain the decay kinetics of the HIV-1 latent reservoir and intermittent viral blips, Mathematical biosciences, 217(1) (2009) 77-87. [47] J.M. Conway, D. Coombs, A stochastic model of latently infected cell reactivation and viral blip generation in treated HIV patients, PLoS Comput Biol, 7(4) (2011) e1002033. [48] M.P. Davenport, R.M. Ribeiro, A.S. Perelson, Kinetics of virus-specific CD8+ T cells and the control of human immunodeficiency virus infection, Journal of Virology, 78(18) (2004) 10096-10103. [49] P.L. Johnson, B.F. Kochin, M.S. McAfee, I.M. Stromnes, R.R. Regoes, R. Ahmed, J.N. Blattman, R. Antia, Vaccination alters the balance between protective immunity, exhaustion, escape, and death in chronic infections, Journal of virology, 85(11) (2011) 5565-5570. [50] A. Ghaffari, M. Nazari, F. Arab, Suboptimal mixed vaccine and chemotherapy in finite duration cancer treatment: state-dependent Riccati equation control, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 37(1) (2015) 45-56. [51] L.G. De Pillis, W. Gu, A.E. Radunskaya, Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations, Journal of Theoretical Biology, 238 (2006) 841–862. [52] A. Ghaffari, M. Khazaee, Cancer dynamics for identical twin brothers, Theoretical Biology and Medical Modeling, 9(4) (2012) 1-13.
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Finite duration HIV treatment using mixed antiretroviral therapy and immunotherapy