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Metameric representations on optimization of nano particle cancer treatment

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

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 2

352--361

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.

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A numerical investigation into the magnetic nanoparticles hyperthermia cancer treatment injection strategies

Dahaghin Ali, Emadiyanrazavi Seyedhamidreza, Salimibani Milad, Bahreinizad Hossein, Haghpanahi Mohammad, Eivazzadeh-Keihan Reza, Maleki Ali

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 2

516--526

EN

Magnetic nanoparticles hyperthermia is a new and promising cancer treatment method. Injection strategies are one of the determining factors in the success of the treatment. This study is a numerical investigation into the injection methods of MNPs hyperthermia. In order to have a realistic tumor morphology and vascularity, a model of Lower Limb tumor was constructed from the CT images. The finite element method was used to solve the problem. This study includes fluid flow in capillaries and inside the porous tissue of the tumor, mass transfer from the capillaries into the tumor tissue, inside the tumor tissue, and from the tumor tissue into the capillaries, and finally heat transfer across the tumor. Finally, tissue damage was calculated in order to evaluate the performance of each method. Results of intravenous injection with single point intratumoral injections were compared here. The results of this study show that intravenous injection yields more homogenous MNPs concentration and temperature distribution, while MNPs concentration and temperature increase in direct injection was limited in a small area around the injection point. Results of the current research suggest that damage to tissue from the hyperthermia with intravenous injection is much more significant compared to direct injection.

3

Optimal strategy in cancer chemotherapy for exponential model of cell population growth

Maroński R.

Zeszyty Naukowe Katedry Mechaniki Stosowanej / Politechnika Śląska

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2006

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z. 26

231-234

EN

The problem of optimal cancer chemotherapy is reconsidered. The cumulative negative toxic effect of the drug is minimized for the assumed destruction result at the end of the therapy. The control function to be optimized is time-dependent dose of the drug. A exponential model of growth of the cancer cell population is employed. It is known that for constant intrinsic rate the solution of the problem is ununique - different strategies give the same result of the therapy. If intrinsic rate is a variable monotonic function of time the solution of the problem is unique and it is of "bang-bang" type with one switching point. The method of extremization of linear integrals via Green's theorem is applied.