Metameric representations on optimization of nano particle cancer treatment

• Autorzy: Tsompanas Michail-Antisthenis , Bull Larry , Adamatzky Andrew , Balaz Igor

Identyfikatory

DOI

10.1016/j.bbe.2021.02.002

• Języki publikacji: EN

Abstrakty

EN

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 opensource 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.

Słowa kluczowe

EN

metameric genetic algorithm; variable-length genetic algorithm; cancer treatment; nanoparticles; PhysiCell

PL

algorytm genetyczny; leczenie nowotworu; nanocząstki; PhysiCell

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2021
• Tom: Vol. 41, no. 2
• Strony: 352--361
• Opis fizyczny: Bibliogr. 54 poz., rys., wykr.

Twórcy

autor

Tsompanas Michail-Antisthenis

• Unconventional Computing Laboratory, University of the West of England, Bristol BS16 1QY, UK

autor

Bull Larry

• Department of Computer Science and Creative Technologies, University of the West of England, Bristol BS16 1QY, UK

autor

Adamatzky Andrew

• Unconventional Computing Laboratory, University of the West of England, Bristol BS16 1QY, UK

autor

Balaz Igor

• Laboratory for Meteorology, Physics and Biophysics, Faculty of Agriculture, Trg Dositeja Obradovica 8, University of Novi Sad, 21000 Novi Sad, Serbia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).