Affiliations 

  • 1 Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia
  • 2 Mechanical Engineering Department, College of Engineering, King Khalid University, Abha, Saudi Arabia
  • 3 Department of Chemistry, Faculty of Science, King Khalid University, Abha, Saudi Arabia
  • 4 Department of Mechanical Engineering, CMR Technical Campus, Hyderabad, Telangana, India
  • 5 Department of Mathematics, Faculty of Science, University of Tabuk, Tabuk, Saudi Arabia
Biomed Mater Eng, 2023 Dec 28.
PMID: 38189746 DOI: 10.3233/BME-230150

Abstract

BACKGROUND: The scientific revolution in the treatment of many illnesses has been significantly aided by stem cells. This paper presents an optimal control on a mathematical model of chemotherapy and stem cell therapy for cancer treatment.

OBJECTIVE: To develop effective hybrid techniques that combine the optimal control theory (OCT) with the evolutionary algorithm and multi-objective swarm algorithm. The developed technique is aimed to reduce the number of cancerous cells while utilizing the minimum necessary chemotherapy medications and minimizing toxicity to protect patients' health.

METHODS: Two hybrid techniques are proposed in this paper. Both techniques combined OCT with the evolutionary algorithm and multi-objective swarm algorithm which included MOEA/D, MOPSO, SPEA II and PESA II. This study evaluates the performance of two hybrid techniques in terms of reducing cancer cells and drug concentrations, as well as computational time consumption.

RESULTS: In both techniques, MOEA/D emerges as the most effective algorithm due to its superior capability in minimizing tumour size and cancer drug concentration.

CONCLUSION: This study highlights the importance of integrating OCT and evolutionary algorithms as a robust approach for optimizing cancer chemotherapy treatment.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.