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Combination Chemotherapy Optimization with Discrete Dosing

Author

Listed:
  • Temitayo Ajayi

    (Nature Source Improved Plants, Ithaca, New York 14850)

  • Seyedmohammadhossein Hosseinian

    (Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, Ohio 45221)

  • Andrew J. Schaefer

    (Department of Computational Applied Mathematics and Operations Research, Rice University, Houston, Texas 77005)

  • Clifton D. Fuller

    (Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030)

Abstract

Chemotherapy drug administration is a complex problem that often requires expensive clinical trials to evaluate potential regimens; one way to alleviate this burden and better inform future trials is to build reliable models for drug administration. This paper presents a mixed-integer program for combination chemotherapy (utilization of multiple drugs) optimization that incorporates various important operational constraints and, besides dose and concentration limits, controls treatment toxicity based on its effect on the count of white blood cells. To address the uncertainty of tumor heterogeneity, we also propose chance constraints that guarantee reaching an operable tumor size with a high probability in a neoadjuvant setting. We present analytical results pertinent to the accuracy of the model in representing biological processes of chemotherapy and establish its potential for clinical applications through a numerical study of breast cancer.

Suggested Citation

  • Temitayo Ajayi & Seyedmohammadhossein Hosseinian & Andrew J. Schaefer & Clifton D. Fuller, 2024. "Combination Chemotherapy Optimization with Discrete Dosing," INFORMS Journal on Computing, INFORMS, vol. 36(2), pages 434-455, March.
    • Handle: RePEc:inm:orijoc:v:36:y:2024:i:2:p:434-455
    DOI: 10.1287/ijoc.2022.0207
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    References listed on IDEAS

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