Combination Chemotherapy Optimization with Discrete Dosing

INFORMS J Comput. 2024 Mar-Apr;36(2):434-455. doi: 10.1287/ijoc.2022.0207. Epub 2023 Nov 9.

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.