Skip to main content
Log in

Global dynamics of target-mediated drug disposition models and their solutions by nonstandard finite difference method

  • Original Research
  • Published:
Journal of Applied Mathematics and Computing Aims and scope Submit manuscript

Abstract

The aim of this work is to study global dynamics of target-mediated drug disposition (TMDD) models and their solutions by nonstandard finite difference (NSFD) schemes. Firstly, we use comparison principles and the Lyapunov stability theory for ODEs to establish positivity, boundedness, local and global asymptotic stability of the TMDD models. Secondly, positivity-preserving NSFD schemes are proposed and their dynamical properties are analysed rigorously. Lastly, we perform a set of numerical simulations to support and illustrate the theoretical results and to show advantages of the NSFD schemes over standard ones. The results show that there is a good agreement between the numerical results and theoretical ones. In addition, the numerical simulations indicate that the constructed NSFD schemes are dynamically stable and efficient in replicating the complex dynamical properties of the continuous models.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Adekanye, O., Washington, T.: Nonstandard finite difference scheme for a Tacoma narrows bridge model. Appl. Math. Modell. 62, 223–236 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  2. Allen, J.L.S.: Introduction to Mathematical Biology. Pearson Education, Inc, Upper Saddle River (2007)

    Google Scholar 

  3. Anguelov, R., Lubuma, J.M.-S.: Nonstandard finite difference method by nonlocal approximations. Math. Comput. Simul. 61, 465–475 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  4. Anguelov, R., Dumont, Y., Lubuma, J.M.-S., Shillor, M.: Dynamically consistent nonstandard finite difference schemes for epidemiological models. J. Comput. Appl. Math. 255, 161–182 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  5. Arenas, A.J., González-Parra, G., Chen-Charpentier, B.M.: A nonstandard numerical scheme of predictor corrector type for epidemic models. Comput. Math. Appl. 59, 3740–3749 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  6. Aston, P.J., Derks, G., Raji, A., Agoram, B.M., van der Graaf, P.H.: Mathematical analysis of the pharmacokinetic-pharmacodynamic (PKPD) behaviour of monoclonal antibodies: predicting in vivo potency. J. Theor. Biol. 281, 113–121 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  7. Burden, R.L., Faires, J.D.: Numerical Analysis, 9th edn. Brooks/Cole, Cengage Learning, San Francisco

  8. Chapwanya, M., Lubuma, J.M.S., Mickens, R.E.: From enzyme kinetics to epidemiological models with Michaelis–Menten contact rate: design of nonstandard finite difference schemes. Comput. Math. Appl. 64, 201–213 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  9. Dang, Q.A., Hoang, M.T.: Dynamically consistent discrete metapopulation model. J. Differ. Equ. Appl. 22, 1325–1349 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  10. Dang, Q.A., Hoang, M.T.: Lyapunov direct method for investigating stability of nonstandard finite difference schemes for metapopulation models. J. Differ. Equ. Appl. 24, 15–47 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  11. Dang, Q.A., Hoang, M.T.: Complete global stability of a metapopulation model and its dynamically consistent discrete models. Qual. Theory Dyn. Syst. 18, 461–475 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  12. Dang, Q.A., Hoang, M.T.: Nonstandard finite difference schemes for a general predator–prey system. J. Comput. Sci. 36, 101015 (2019)

    Article  MathSciNet  Google Scholar 

  13. Dang, Q.A., Hoang, M.T.: Exact finite difference schemes for three-dimensional linear systems with constant coefficients. Vietnam J. Math. 46, 471–492 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  14. Dang, Q.A., Hoang, M.T., Dang, Q.L.: Nonstandard finite difference schemes for solving a modified epidemiological model for computer viruses. J. Comput. Sci. Cybern. 34, 171–185 (2018)

    Article  Google Scholar 

  15. Dang, Q.A., Hoang, M.T.: Positive and elementary stable explicit nonstandard Runge–Kutta methods for a class of autonomous dynamical systems. Int. J. Comput. Math. 97, 2036–2054 (2020). https://doi.org/10.1080/00207160.2019.1677895

  16. Dang, Q.A., Hoang, M.T.: Positivity and global stability preserving NSFD schemes for a mixing propagation model of computer viruses. J. Comput. Appl. Math. 374, 112753 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  17. Dua, P., Hwakins, E., van der Graaf, P.H.: A tutorial on target-mediated drug disposition (TMDD) models. CPT Pharmacometrics Syst. Pharmacol. 4, 324–337 (2015)

    Article  Google Scholar 

  18. Egbelowo, O.F.: Nonstandard finite difference approach for solving 3-compartment pharmacokinetic models. Int. J. Numer. Methods Biomed. Eng. 34, e3114 (2018). https://doi.org/10.1002/cnm.3114

    Article  MathSciNet  Google Scholar 

  19. Egbelowo, O.: Nonlinear elimination of drugs in one-compartment pharmacokinetic models: nonstandard finite difference approach for various routes of administration. Math. Comput. Appl. 23, 27 (2018)

    MathSciNet  Google Scholar 

  20. Egbelowo, O.F.: The nonstandard finite difference method applied to pharmacokinetic models. PhD Thesis, University of the Witwatersrand, Johannesburg, South Africa (2018)

  21. Egbelowo, O., Harley, C., Jacobs, B.: Nonstandard finite difference method applied to a linear pharmacokinetics model. Bioengineering 4, 40 (2017)

    Article  Google Scholar 

  22. Estep, D.: A posteriori error bounds and global error control for approximation of ordinary differential equations. SIAM J. Numer. Anal. 32, 1–48 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  23. González-Parra, G., Arenas, A.J., Chen-Charpentier, B.M.: Combination of nonstandard schemes and Richardson’s extrapolation to improve the numerical solution of population models. Math. Comput. Model. 52, 1030–1036 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  24. Hoang, M.T., Egbelowo, O.F.: Nonstandard finite difference schemes for solving an SIS epidemic model with standard incidence. Rend. Circolo Mat. Palermo Ser. 69, 753–769 (2019). https://doi.org/10.1007/s12215-019-00436-x

  25. Hoang, M.T., Egbelowo, O.F.: On the global asymptotic stability of a hepatitis B epidemic model and its solutions by nonstandard numerical schemes. Boletín de la Sociedad Matemáitica Mexicana 26, 1113–1134 (2020). https://doi.org/10.1007/s40590-020-00275-2

  26. Hoang, M.T., Nagy, A.M.: Uniform asymptotic stability of a logistic model with feedback control of fractional order and nonstandard finite difference schemes. Chaos Solitons Fractals 123, 24–34 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  27. Hoang, M.T., Egbelowo, O.F.: Numerical dynamics of nonstandard finite difference schemes for a Logistics model with feedback control. Ann. Univ. Ferrara 66, 51–65 (2020). https://doi.org/10.1007/s11565-020-00338-2

  28. Holm, B., Wihler, T.P.: Continuous and discontinuous Galerkin time stepping methods for nonlinear initial value problems with application to finite time blow-up. Numer. Math. 138(3), 767–799 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  29. Hulme, B.L.: One-step piecewise polynomial Galerkin methods for initial value problems. Math. Comput. 26, 415–426 (1972)

    Article  MathSciNet  MATH  Google Scholar 

  30. Khalil, H.K.: Nonlinear Systems, 3rd edn. Prentice Hall, Upper Saddle River (2002)

    MATH  Google Scholar 

  31. Korpusik, A.: A nonstandard finite difference scheme for a basic model of cellular immune response to viral infection. Commun. Nonlinear Sci. Numer. Simul. 43, 369–384 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  32. Levy, G.: General pharmacologic target-mediated drug disposition. Clin. Pharmacol. Ther. 56, 248–252 (1994)

    Article  Google Scholar 

  33. Mager, D.E., Jusko, W.J.: General pharmacokinetic model for drugs exhibiting target-mediated drug disposition. J. Pharmacokinet. Pharmacodyn. 28(6), 507–532 (2001)

    Article  Google Scholar 

  34. Mickens, R.E.: Nonstandard finite difference schemes for differential equations. J. Diff. Equ. Appl. 8, 823–847 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  35. Mickens, R.E.: Applications of Nonstandard Finite Difference Schemes. World Scientific, Singapore (2000)

    Book  MATH  Google Scholar 

  36. Mickens, R.E.: Advances in the Applications of Nonstandard Finite Difference Schemes. World Scientific, Singapore (2005)

    Book  MATH  Google Scholar 

  37. Mickens, R.E.: Nonstandard Finite Difference Models of Differential Equations. World Scientific, Singapore (1993)

    Book  Google Scholar 

  38. Peletier, L.A., Gabrielsson, J.: Dynamics of target-mediated drug disposition: characteristic profiles and parameter identification. J. Pharmacokinet. Pharmacodyn. 39, 429 (2012). https://doi.org/10.1007/s10928-012-9260-6

    Article  Google Scholar 

  39. Smith, H.L., Waltman, P.: The Theory of the Chemostat: Dynamics of Microbial Competition. Cambridge University Press, Cambridge (1995)

    Book  MATH  Google Scholar 

  40. Wihler, T.P.: An a priori error analysis of the hp-version of the continuous Galerkin FEM for nonlinear initial value problems. J. Sci. Comput. 25(3), 523–549 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  41. Wood, D.T., Kojouharov, H.V.: A class of nonstandard numerical methods for autonomous dynamical systems. Appl. Math. Lett. 50, 78–82 (2016)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

The authors thank the editors and anonymous referees for useful and valuable comments that led to a great improvement of the paper. Oluwaseun Egbelowo is particularly grateful to Charis Harley (University of Johannesburg) and Byron Jacobs (University of Johannesburg) for the useful discussion that led to this paper. The second author, Manh Tuan Hoang, is supported by Institute of Information Technology, Vietnam Academy of Science and Technology under the Grant Number CS 20.01.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Oluwaseun Francis Egbelowo.

Ethics declarations

Conflict of interest

The authors have no conflict of interest.

Author contributions

All authors contributed equally to the manuscript. All authors read and approved the final version of the manuscript.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix A: Convergence of the NSFD schemes

Appendix A: Convergence of the NSFD schemes

The following results on the convergence of the NSFD schemes are proved similarly to Theorem 5.9 in [7].

Proposition 1

The NSFD scheme (11) for the model (1) is convergent of order 1.

Proof

We rewrite the model (1) in the vector form

$$\begin{aligned} \dfrac{dy}{dt} = f(y), \end{aligned}$$

where \(y(t) = \big [L(t), R(t), P(t)\big ]^T\) and f denotes the right-hand side function of (1). It is easy to verify that (11) can be written in the form

$$\begin{aligned} y_{n + 1} = y_n + \varphi (h)F(y_n, h), \end{aligned}$$

where

$$\begin{aligned} F(y, 0) = f(y). \end{aligned}$$
(25)

Using the hypothesis \(\varphi (h) = h + \mathcal {O}(h^2)\) as \(h \rightarrow 0\) and (25) and repeating the proof of [7, Theorem 5.9], we obtain

$$\begin{aligned} \Vert y_{n} - y(t_n)\Vert = \mathcal {O}(h), \end{aligned}$$
(26)

for \(i = 0, 1, 2, \ldots \). Consequently, the proof is complete. \(\square \)

Similarly to Proposition 1, we obtain the convergence of the NSFD (20) as follows.

Proposition 2

The NSFD scheme (20) for the model (6) is convergent of order 1.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Egbelowo, O.F., Hoang, M.T. Global dynamics of target-mediated drug disposition models and their solutions by nonstandard finite difference method. J. Appl. Math. Comput. 66, 621–643 (2021). https://doi.org/10.1007/s12190-020-01452-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12190-020-01452-2

Keywords

Navigation