IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i5p1192-d1083648.html
   My bibliography  Save this article

Scheduling BCG and IL-2 Injections for Bladder Cancer Immunotherapy Treatment

Author

Listed:
  • Amit Yaniv-Rosenfeld

    (Shalvata Mental Health Care Center, Hod Hasharon 45100, Israel
    Department of Management, Bar-Ilan University, Ramat-Gan 52900, Israel
    These authors contributed equally to this work.)

  • Elizaveta Savchenko

    (Independent Researcher, Ramat-Gan 52900, Israel
    These authors contributed equally to this work.)

  • Ariel Rosenfeld

    (Department of Information Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel)

  • Teddy Lazebnik

    (Department of Cancer Biology, Cancer Institute, University College London, London WC1E 6DD, UK)

Abstract

Cancer is one of the most common families of diseases today with millions of new patients every year around the world. Bladder cancer (BC) is one of the most prevalent types of cancer affecting both genders, and it is not known to be associated with a specific group in the population. The current treatment standard for BC follows a standard weekly Bacillus Calmette–Guérin (BCG) immunotherapy-based therapy protocol which includes BCG and IL-2 injections. Unfortunately, due to the biological and clinical complexity of the interactions between the immune system, treatment, and cancer cells, clinical outcomes vary significantly among patients. Unfortunately, existing models are commonly developed for a non-existing average patient or pose strict, unrealistic, expectations on the treatment process. In this work, we propose the most extensive ordinary differential equation-based biological model of BCG treatment to date and a deep learning-based scheduling approach to obtain a personalized treatment schedule. Our results show that resulting treatment schedules favorably compare with the current standard practices and the current state-of-the-art scheduling approach.

Suggested Citation

  • Amit Yaniv-Rosenfeld & Elizaveta Savchenko & Ariel Rosenfeld & Teddy Lazebnik, 2023. "Scheduling BCG and IL-2 Injections for Bladder Cancer Immunotherapy Treatment," Mathematics, MDPI, vol. 11(5), pages 1-13, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:5:p:1192-:d:1083648
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/5/1192/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/5/1192/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jason Poulos & Shuxi Zeng, 2021. "RNN‐based counterfactual prediction, with an application to homestead policy and public schooling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1124-1139, August.
    2. Jason Poulos & Shuxi Zeng, 2017. "RNN-based counterfactual prediction, with an application to homestead policy and public schooling," Papers 1712.03553, arXiv.org, revised May 2021.
    3. Cyrill A Rentsch & Claire Biot & Joël R Gsponer & Alexander Bachmann & Matthew L Albert & Romulus Breban, 2013. "BCG-Mediated Bladder Cancer Immunotherapy: Identifying Determinants of Treatment Response Using a Calibrated Mathematical Model," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-6, February.
    4. Nazila Bazrafshan & M. M. Lotfi, 2020. "A finite-horizon Markov decision process model for cancer chemotherapy treatment planning: an application to sequential treatment decision making in clinical trials," Annals of Operations Research, Springer, vol. 295(1), pages 483-502, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jacob Goldin & Julian Nyarko & Justin Young, 2022. "Forecasting Algorithms for Causal Inference with Panel Data," Papers 2208.03489, arXiv.org, revised Apr 2024.
    2. Najmeddine Dhieb & Ismail Abdulrashid & Hakim Ghazzai & Yehia Massoud, 2023. "Optimized drug regimen and chemotherapy scheduling for cancer treatment using swarm intelligence," Annals of Operations Research, Springer, vol. 320(2), pages 757-770, January.

    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:gam:jmathe:v:11:y:2023:i:5:p:1192-:d:1083648. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.