A multi-objective multi-drug model for cancer chemotherapy treatment planning: A cost-effective approach to designing clinical trials

• A multi-objective multi-drug optimization model for cancer chemotherapy treatment planning is developed.
• The proposed optimization strategy provides a reasonable trade-off between the survival time and treatment costs.
• The proposed multi-objective optimization approach can generate the most promising low cost drug combinations.
• The proposed approach gives an efficient tool to the oncologists for designing the clinical trials.

One of the important areas of concentration in medical sciences is the development of the treatment regimens in chronic diseases like cancer. This paper provides insights on how to design new clinical trials for gastric and gastroesophageal cancers which can discover the optimal and cost-effective chemotherapy treatment regimens. First, we extract data from the previously published clinical trials for the mentioned cancers to develop statistical models being capable of predicting trial outcomes. Then, using the statistical models, we present a multi-objective multi-drug model for cancer chemotherapy treatment planning. The proposed model yields a wide range of solutions establishing a reasonable tradeoff between patient's survival and treatment costs while satisfying some prevailing limitations on toxicities and the feasibility of treatment regimens. Results show that the proposed approach needs much less time and cost than the trial-and-error manipulation of cancer treatment. It also takes the advantage of saving and improving the quality of patients’ lives by suggesting the new drug regimens which improve the survival time of patients and have reasonable treatment costs compared to the current practice trials.