Metameric representations on optimization of nano particle cancer treatment

Tsompanas, Michail Antisthenis; Bull, Larry; Adamatzky, Andrew; Balaz, Igor

Abstract

In silico evolutionary optimization of cancer treatment based on multiple nano-particle (NP) assisted drug delivery systems was investigated in this study. The use of multiple types of NPs is expected to increase the robustness of the treatment, due to imposing higher complexity on the solution tackling a problem of high complexity, namely the physiology of a tumor. Thus, the utilization of metameric representations in the evolutionary optimization method was examined, along with suitable crossover and mutation operators. An open-source physics-based simulator was utilized, namely PhysiCell, after appropriate modifications, to test the fitness of possible treatments with multiple types of NPs. The possible treatments could be comprised of up to ten types of NPs, simultaneously injected in an area close to the cancerous tumour. Initial results seem to suffer from bloat, namely the best solutions discovered are converging towards the maximum amount of different types of NPs, however, without providing a significant return in fitness when compared with solutions of fewer types of NPs. As the large diversity of NPs will most probably prove to be quite toxic in lab experiments, we opted for methods to reduce the bloat, thus, resolve to therapies with fewer types of NPs. Namely, the bloat control methods studied here were removing types of NPs from the optimization genome as part of the mutation operator and applying parsimony pressure in the replacement operator. By utilizing these techniques, the treatments discovered are composed of fewer types of NPs, while their fitness is not significantly smaller.

• Journal Article Type: Article
• Acceptance Date: Feb 16, 2021
• Online Publication Date: Mar 6, 2021
• Publication Date: 2021-04
• Deposit Date: Feb 25, 2022
• Publicly Available Date: Feb 25, 2022
• Journal: Biocybernetics and Biomedical Engineering
• Print ISSN: 0208-5216
• Electronic ISSN: 0208-5216
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 41
• Issue: 2
• Pages: 352-361
• DOI: https://doi.org/10.1016/j.bbe.2021.02.002
• Keywords: Biomedical Engineering
• Public URL: https://uwe-repository.worktribe.com/output/8581336
• Additional Information: This article is maintained by: Elsevier; Article Title: Metameric representations on optimization of nano particle cancer treatment; Journal Title: Biocybernetics and Biomedical Engineering; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.bbe.2021.02.002; Content Type: article; Copyright: © 2021 The Author(s). Published by Elsevier B.V. on behalf of Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences.