Combination Chemotherapy Optimization with Discrete Dosing

Temitayo Ajayi (), Seyedmohammadhossein Hosseinian (), Andrew J. Schaefer () and Clifton D. Fuller ()
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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

INFORMS Journal on Computing, 2024, vol. 36, issue 2, 434-455

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.

Keywords: combination chemotherapy; differential equations; mixed-integer linear programming (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:36:y:2024:i:2:p:434-455

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