Chemotherapy Drug Scheduling: A Particle Swarm Optimization Approach

Abstract

This paper presents an investigation into a model of chemotherapy drug scheduling for cancer treatment using feedback control and a bioinspired optimization algorithm, called Particle Swarm Optimization (PSO). The main aim of chemotherapy treatment is to reduce the tumour size. Earlier a feedback control method, namely Integral-Proportional-Derivative (I-PD) was developed in [1] for non-phase specific tumour model to control the drug to be infused into the patient’s body by maintaining a tolerable level of drug concentration at tumour sites. In this work, PSO is used to devise an effective drug scheduling for a phase-specific tumour model by optimizing the parameters of earlier developed I-PD controller. The phase specific cancer tumour model is used to analyze the effects of drug on different cell populations, plasma drug concentration and toxic side effects. Results show that proposed method can reduce the tumour size up to 72% with relatively lower drug doses. Moreover, the method results very low toxic side effects throughout the whole period of treatment.