Combination Chemotherapy Optimization with Discrete Dosing.
Temitayo AjayiSeyedmohammadhossein HosseinianAndrew J SchaeferClifton David FullerPublished in: INFORMS journal on computing (2023)
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.
Keyphrases
- drug administration
- locally advanced
- clinical trial
- rectal cancer
- squamous cell carcinoma
- induced apoptosis
- radiation therapy
- oxidative stress
- chemotherapy induced
- lymph node
- single cell
- quality improvement
- risk factors
- cell cycle arrest
- young adults
- randomized controlled trial
- signaling pathway
- open label
- climate change
- study protocol