IDEAS home Printed from https://ideas.repec.org/a/taf/nmcmxx/v25y2019i1p63-89.html
   My bibliography  Save this article

A cellular automata model of chemotherapy effects on tumour growth: targeting cancer and immune cells

Author

Listed:
  • Fateme Pourhasanzade
  • S. H. Sabzpoushan

Abstract

The effects of therapy on avascular cancer development based on a stochastic cellular automata model are considered. Making the model more compatible with the biology of cancer, the following features are implemented: intrinsic resistance of cancerous cells along with drug-induced resistance, drug-sensitive cells, immune system. Results are reported for no treatment, discontinued treatment after only one cycle of chemotherapy, and periodic drug administration therapy modes. Growth fraction, necrotic fraction, and tumour volume are used as output parameters beside a 2-D graphical growth presentation. Periodic drug administration is more effective to inhibit the growth of tumours. The model has been validated by the verification of the simulation results using in vivo literature data. Considering immune cells makes the model more compatible with the biological realities. Beside targeting cancer cells, the model can also simulate the activation of the immune system to fight against cancer.Abbreviations CA: cellular automata; DSC: drug sensitive cell; DRC: drug resistant cell; GF: growth fraction; NF: necrotic fraction; ODE: ordinary differential equation; PDE: partial differential equation; SCAM: The proposed stochastic cellular automata model

Suggested Citation

  • Fateme Pourhasanzade & S. H. Sabzpoushan, 2019. "A cellular automata model of chemotherapy effects on tumour growth: targeting cancer and immune cells," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 25(1), pages 63-89, January.
  • Handle: RePEc:taf:nmcmxx:v:25:y:2019:i:1:p:63-89
    DOI: 10.1080/13873954.2019.1571515
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13873954.2019.1571515
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13873954.2019.1571515?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Moghari, Somaye & Ghorani, Maryam, 2022. "A symbiosis between cellular automata and dynamic weighted multigraph with application on virus spread modeling," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:nmcmxx:v:25:y:2019:i:1:p:63-89. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/NMCM20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.