New Mathematical Models of Antimalarial Drug Action to Improve Drug Dosing Regimens

  • James M. McCaw
  • Pengxing Cao
  • Sophie Zaloumis
  • Julie A. Simpson
Conference paper
Part of the Mathematics for Industry book series (MFI, volume 28)

Abstract

Plasmodium falciparum malaria remains a major threat to global public health. Artemisinin-based combination therapies—a critical component of current control strategies—are at risk of failure due to the emergence of artemisinin resistance. To extend the life of artemisinin-based therapies, it is crucial that we develop a better understanding of how they act to reduce parasitemia in the host. Recent laboratory-based experiments have demonstrated that parasites respond to the cumulative, rather than instantaneous, drug concentration. This observation directly challenges the standard paradigm of pharmacokinetic–pharmacodynamic (PK–PD) modelling. Here, we introduce a generalisation to the PK–PD model which accounts for cumulative exposure. Parasites accumulate ‘stress’, which translates into an effective killing rate which can vary with both drug concentration and exposure time. Our model indicates how drug-resistant parasites may avoid killing. Through simulation, we explore alternative drug dosing strategies that may overcome drug resistance.

Keywords

Mathematics for Industry Biological modelling Malaria Antimalarial drugs 

Notes

Acknowledgements

We thank Leann Tilley and her team (Bio21, The University of Melbourne) for access to data. Pengxing Cao and Sophie Zaloumis were supported by National Health and Medical Research Council project and Centre for Research Excellence funding.

References

  1. 1.
    R.T. Eastman, Fidock Da, Artemisinin-based combination therapies: a vital tool in efforts to eliminate malaria. Nat. Rev. Microbiol. 7, 864–874 (2009)CrossRefGoogle Scholar
  2. 2.
    A.M. Dondorp, R.M. Fairhurst, L. Slutsker, J.R. Macarthur, J.G. Breman et al., The threat of artemisinin-resistant malaria. N. Engl. J. Med. 365, 1073–1075 (2011)CrossRefGoogle Scholar
  3. 3.
    J.A. Simpson, S. Zaloumis, A.M. DeLivera, R.N. Price, J.M. McCaw, Making the most of clinical data: reviewing the role of pharmacokinetic-pharmacodynamic models of anti-malarial drugs. AAPS J (2014)Google Scholar
  4. 4.
    N. Klonis, S.C. Xie, J.M. McCaw, M.P. Crespo-Ortiz, S.G. Zaloumis et al., Altered temporal response of malaria parasites determines differential sensitivity to artemisinin. Proc. Natl. Acad. Sci. U.S.A. 110, 5157–5162 (2013)CrossRefGoogle Scholar
  5. 5.
    C. Dogovski, S.C. Xie, G. Burgio, J. Bridgford, S. Mok et al., Targeting the cell stress response of Plasmodium falciparum to overcome artemisinin resistance. PLoS Biol. 13, e1002132 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • James M. McCaw
    • 1
  • Pengxing Cao
    • 1
  • Sophie Zaloumis
    • 2
  • Julie A. Simpson
    • 2
  1. 1.School of Mathematics and StatisticsThe University of MelbourneMelbourneAustralia
  2. 2.Melbourne School of Population and Global HealthThe University of MelbourneMelbourneAustralia

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