Drug Scheduling in Chemotherapeutic Treatment using Multi-objective Optimization based 2DOF PID Cascade Control Scheme

Chemotherapy Regimen Optimization Using a Two-Archive Multi-Objective Squirrel Search Algorithm

“…The multi-objective algorithms compared in this study include classic algorithms that have been widely used in optimizing chemotherapy doses in recent years, such as the Nondominated Sorting Genetic Algorithm II (NSGA-II) [4,13,22], the Multi-Objective Particle Swarm Optimization Algorithm (MOPSO) [13,16,38], as well as the improved Two Archive algorithm (Two_Arch2) [33], the Constrained Two-Archive Evolutionary Algorithm II (C-TAEA-II) [39] for constrained multi-objective optimization, and the original Multi-Objective Squirrel Search Algorithm (MOSSA) [37]. The latter three are included to illustrate the performance improvements of the TA-MOSSA.…”

“…Panjwani et al [12] used a two-degree-of-freedom fractional-order PID controller for closed-loop scheduling of chemotherapeutic drugs using an exponential tumor growth model, which produced a set of chemotherapeutic dosing regimens with varying trade-offs between tumor reduction and toxicity levels. Mondal et al [13] also conducted a study based on the exponential growth model and proposed a chemotherapy drug scheduling plan using a two-degree-of-freedom PID controller cascade model of chemotherapy drug scheduling; the obtained chemotherapy regimen had lower drug toxicity and tumor cell residues than the conventional PID controller, and it also used fewer drug doses. However, studies by Panjwani et al and Mondal et al have focused on single-agent chemotherapy, which often requires larger doses of drugs to achieve the same efficacy as compared to combination chemotherapy, with a consequent elevation in toxicity and resistance; this is therefore often preferred for the treatment of many types of cancers.…”

“…Considering the need to control toxicity levels while ensuring efficacy, the quantity of normal tissue cells and the concentration of drugs at tumor sites were constrained within specific ranges. Mondal et al [13] proposed a Proportional−Integral−Derivative controller (2DOF PID) in a cascaded drug scheduling model. They used NSGA-II to optimize design parameters, with the optimization objectives being the toxicity level and the absolute error of drug concentration compared to their respective desired values.…”