Skip to main content
SpringerLink
Log in
Book cover

International Workshop on Hybrid Systems Biology

HSB 2014: Hybrid Systems Biology pp 1–26Cite as

Immune Response Enhancement Strategy via Hybrid Control Perspective

  • Conference paper
  • First Online:

  • 355 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7699))

Abstract

We investigate a control method for disease dynamics, such as HIV and malaria, to boost the immune response using a model-based approach. In particular we apply the control method to select the appropriate immune response between Th1 and Th2 responses. The idea of state jump is introduced and discussed based on hybrid control systems. To implement the control idea we propose physically available methods for each biological system. The studies on malaria model and HIV model are supported by experimental data.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   44.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    This mechanism is also used for the treatment of chronic myeloid leukaemia (CML) in [6].

  2. 2.

    Human malaria is caused by four species of Plasmodium: P. falciparum, P. malariae, P. ovale, and P. vivax [22]. Model 1-5 includes the dynamics between P. vivax, P. falciparum and the immune system.

  3. 3.

    The model parameters are based on clinical data, so the state variables in this section represent actual data.

  4. 4.

    Besides immunotherapy, bee venom are currently used in clinical cases. Experimental results of [20] are one example.

  5. 5.

    Th stands for T-helper. Th1 and Th2 are two types of T-helper cells.

  6. 6.

    Immune response to intracellular pathogens tends to induce Th1 dominance and resultant cellular cytolytic activity, although immune response to extracellular infection is often dominated by Th2 response, which lead to high levels of pathogen-specific immunoglobulins [2].

  7. 7.

    The reason why the switch Th1-Th2 is guaranteed but the switch Th2-Th1 is not with the current parameters will be discussed in Sect. 5.

  8. 8.

    The model parameters are normalised, so the state variables in this section do not represent actual data.

  9. 9.

    In [5, 7, 33] control of the drug dose is exploited so that the inequality is achieved.

  10. 10.

    Alternatively impulsive input can be modeled by a Dirac delta function as in [28].

References

  1. Adams, B.M., Banks, H.T., Kwon, H., Tran, H.T.: Dynamic multidrug therapies for HIV: optimal and STI control approaches. Math. Biosci. Eng. 1, 223–241 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  2. Bergmann, C., van Hemmen, J.L., Segel, L.E.: Th1 or Th2: How an appropriate T helper response can be made. Bull. Math. Biol. 63, 405–430 (2001)

    Article  MATH  Google Scholar 

  3. Bergmann, C., van Hemmen, J.L., Segel, L.E.: How instruction and feedback can select the appropriate T helper response. Bull. Math. Biol. 64, 425–446 (2002)

    Article  MATH  Google Scholar 

  4. Brandt, M.E., Chen, G.: Feedback control of a biodynamical model of HIV-1. IEEE Trans. Biomed. Eng. 48(7), 754–759 (2001)

    Article  Google Scholar 

  5. Chang, H., Astolfi, A.: Activation of immune response in disease dynamics via controlled drug scheduling. IEEE Trans. Autom. Sci. Eng. 6, 248–255 (2009)

    Article  Google Scholar 

  6. Chang, H., Astolfi, A.: Enhancement of the immune response to chronic myeloid leukaemia via controlled treatment scheduling. In: Proceedings of the of 31st Annual EMBS International Conference, pp. 3889–3892 (2009)

    Google Scholar 

  7. Chang, H., Astolfi, A.: Control of HIV infection dynamics: Approximating high-order dynamics by adapting reduced-order model parameters. IEEE Control Syst. Mag. 28, 28–39 (2008)

    Article  MathSciNet  Google Scholar 

  8. Chang, H., Astolfi, A., Shim, H.: A control theoretic approach to venom immunotherapy with state jumps. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 742–745, August 2010

    Google Scholar 

  9. Chang, H., Astolfi, A., Shim, H.: A control theoretic approach to malaria immunotherapy with state jumps. Automatica 47(6), 1271–1277 (2011). Special Issue on Systems Biology

    Article  MathSciNet  MATH  Google Scholar 

  10. Chang, H., Moog, C.H., Astolfi, A., Rivadeneira, P.S.: A control systems analysis of HIV prevention model using impulsive input. Biomed. Sign. Process. Control 13, 123–131 (2014)

    Article  Google Scholar 

  11. Ge, S.S., Tian, Z., Lee, T.H.: Nonlinear control of a dynamic model of HIV-1. IEEE Trans. Biomed. Eng. 52(3), 353–361 (2005)

    Article  Google Scholar 

  12. Gibaldi, M., Perrier, D.: Drugs and the Pharmaceutical Sciences, vol. 1: Pharmacokinetics. Marcel Dekker Inc, New York (1975)

    Google Scholar 

  13. Gilead Sciences Ltd., Truvada\(^{\textregistered }\) Full Prescribing Information, 4 Dec 2011. Available at http://www.truvada.com/pdf/fpi.pdf. (2011)

  14. David, B.K.: Golden. Insect sting allergy and venom immunotherapy: A model and a mystery. J. Allergy Clin. Immunol. 115(3), 439–447 (2005)

    Article  Google Scholar 

  15. Grant, R.M., Lama, J.R., Anderson, P.L., McMahan, V., Liu, A.Y., Vargas, L., Goicochea, P., et al.: Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. New Engl. J. Med. 363(27), 2587–2599 (2010)

    Article  Google Scholar 

  16. Gurarie, D., McKenzie, F.E.: Dynamics of immune response and drug resistance in malaria infection. Malaria J. 5(1), 86 (2006)

    Article  Google Scholar 

  17. Gurarie, D., Zimmerman, P.A., King, C.H.: Dynamic regulation of single-and mixed-species malaria infection: insights to specific and non-specific mechanisms of control. J. Theor. Biol. 240(2), 185–199 (2006)

    Article  MathSciNet  Google Scholar 

  18. Jackson, A., Moyle, G., Watson, V., Tjia, J., Ammara, A., Back, D., Mohabeer, M., Gazzard, B., Boffito, M.: Tenofovir, emtricitabine intracellular and plasma, and efavirenz plasma concentration decay following drug intake cessation: implications for HIV treatment and prevention. JAIDS, Publish Ahead of Print (2013)

    Google Scholar 

  19. Jilek, B.L., Zarr, M., Sampah, M.E., Rabi, S.A., Bullen, C.K., Lai, J., Shen, L., Siliciano, R.F.: A quantitative basis for antiretroviral therapy for HIV-1 infection. Nature Med. 18, 446–451 (2012)

    Article  Google Scholar 

  20. Kim, K.-W., Shin, Y.-S., Kim, K.-S., Chang, Y.-C., Park, K.-K., Park, J.-B., Choe, J.-Y., Lee, K.-G., Kang, M.-S., Park, Y.-G., Kim, C.-H.: Suppressive effects of bee venom on the immune responses in collagen-induced arthritis in rats. Phytomedicine 15(12), 1099–1107 (2008)

    Article  Google Scholar 

  21. Mason, D.P., McKenzie, F.E.: Blood-stage dynamics and clinical implications of mixed Plasmodium vivax-Plasmodium falciparum infections. Am. J. Trop Med. Hyg. 61(3), 367–374 (1999)

    Article  Google Scholar 

  22. Mason, D.P., McKenzie, F.E., Bossert, W.H.: The blood-stage dynamics of mixed Plasmodium malariae-Plasmodium falciparum infections. J. Theor. Biol. 198(4), 549–566 (1999)

    Article  Google Scholar 

  23. McQueen, P.G., McKenzie, F.E.: Host control of malaria infections: Constraints on immune and erythropoeitic response kinetics. PLoS Comput. Biol. 4, e1000149 (2008)

    Article  MathSciNet  Google Scholar 

  24. Mhawej, M., Moog, C.H., Biafore, F., Brunet-François, C.: Control of the HIV infection and drug dosage. Biomed. Sign. Process. Control 5(1), 45–52 (2010)

    Article  Google Scholar 

  25. Nowak, M.A., May, R.M.: Virus Dynamics. Oxford University Press, New York (2000)

    MATH  Google Scholar 

  26. Recker, M., Nee, S., Bull, P.C., Kinyanjui, S., Marsh, K., Newbold, C., Gupta, S.: Transient cross-reactive immune responses can orchestrate antigenic variation in malaria. Nature 429(6991), 555–558 (2004)

    Article  Google Scholar 

  27. Richter, J., Metzner, G., Behn, U.: Mathematical modelling of venom immunotherapy. J. Theor. Med. 4, 119–132 (2002)

    Article  MATH  Google Scholar 

  28. Rivadeneira, P.S., Moog, C.H.: Impulsive control of single-input nonlinear systems with application to HIV dynamics. Appl. Math. Comput. 218(17), 8462–8474 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  29. Roestenberg, M., McCall, M., Hopman, J., et al.: Protection against a malaria challenge by sporozoite inoculation. N. Engl. J. Med. 361(5), 468–477 (2009)

    Article  Google Scholar 

  30. Rowland, M., Tozer, T.: Clinical Pharmacokinetics: Concepts and Applications. Lea & Febiger, Philadelphia (1980)

    Google Scholar 

  31. Sampah, M.E.S., Shen, L., Jilek, B.L., Siliciano, R.F.: Dose-response curve slope is a missing dimension in the analysis of HIV-1 drug resistance. Proc. Natl. Acad. Sci. 108(18), 7613–7618 (2011)

    Article  Google Scholar 

  32. Shen, L., Peterson, S., Sedaghat, A.R., McMahon, M.A., Callender, M., Zhang, H., Zhou, Y., Pitt, E., Anderson, K.S., Acosta, E.P., Siliciano, R.F.: Dose-response curve slope sets class-specific limits on inhibitory potential of anti-HIV drugs. Nature Med. 14, 762–766 (2008)

    Article  Google Scholar 

  33. Shim, H., Jo, N.H., Chang, H., Seo, J.H.: A system theoretic study on a treatment of AIDS patient by achieving long-term non-progressor. Automatica 45, 611–622 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  34. UNAIDS, T.W.H. Organization. AIDS epidemic update: 2010. UNAIDS, Geneva (2010)

    Google Scholar 

  35. Wodarz, D.: Helper-dependent vs. helper-independent CTL responses in HIV infection. J. Theor. Biol. 213, 447–459 (2001)

    Article  Google Scholar 

  36. Wodarz, D., Nowak, M.A.: Specific therapy regimes could lead to long-term immunological control of HIV. Proc. Natl. Acad. Sci. 96(25), 14464–14469 (1999)

    Article  Google Scholar 

  37. Wodarz, D., May, R.M., Nowak, M.A.: The role of antigen-independent persistence of memory cytotoxic T lymphocytes. Int. Immunol. 12(4), 467–477 (2000)

    Article  Google Scholar 

  38. World Health Organization Expert Committee on Malaria. 20th Report. WHO Regional Office for Africa (2003)

    Google Scholar 

  39. Zurakowski, R., Teel, A.R.: A model predictive control based scheduling method for HIV therapy. J. Theor. Biol. 238, 368–382 (2006)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical Engineering, Kookmin University, Seoul, 136-702, Republic of Korea

    Hyuk-Jun Chang

  2. Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, UK

    Alessandro Astolfi

  3. DICII, Università di Roma Tor Vergata, Via del Politecnico 1, 00133, Roma, Italy

    Alessandro Astolfi

Authors
  1. Hyuk-Jun Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alessandro Astolfi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hyuk-Jun Chang .

Editor information

Editors and Affiliations

  1. "CNRS-VERIMAG, University of Grenoble-Alpes (UGA), Grenoble, France

    Oded Maler

  2. West Virginia University, Morgantown, West Virginia, USA

    Ádám Halász

  3. VERIMAG, Gieres, France

    Thao Dang

  4. University of Udine, Udine, Italy

    Carla Piazza

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Chang, HJ., Astolfi, A. (2015). Immune Response Enhancement Strategy via Hybrid Control Perspective. In: Maler, O., Halász, Á., Dang, T., Piazza, C. (eds) Hybrid Systems Biology. HSB 2014. Lecture Notes in Computer Science(), vol 7699. Springer, Cham. https://doi.org/10.1007/978-3-319-27656-4_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27656-4_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27655-7

  • Online ISBN: 978-3-319-27656-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation