Potential Benefits of Discrete-Time Controller-based Treatments over Protocol-based Cancer Therapies

Sápi, Johanna; Drexler, Dániel András; Kovács, Levente

doi:10.12700/aph.14.1.2017.1.2

Cited by 10 publications

(2 citation statements)

References 15 publications

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“…Personalized therapies are gaining more interest in clinical practice due to their many advantages, like greater efficiency and fewer side effects. An efficient approach is to use mathematical models to describe specific physiological problems [1][2][3][4][5] and use control theory to generate therapies [6][7][8][9][10]. Mathematical optimization and personalization of cancer chemotherapies may also decrease the chance of drug resistance development during the treatment [11].…”

Section: Introductionmentioning

confidence: 99%

Stability analysis of the singular points and Hopf bifurcations of a tumor growth control model

Drexler,

Nagy,

Romanovski

2024

Math Methods in App Sciences

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We carry out qualitative analysis of a fourth‐order tumor growth control model using ordinary differential equations. We show that the system has one positive equilibrium point, and its stability is independent of the feedback gain. Using a Lyapunov function method, we prove that there exist realistic parameter values for which the systems admit limit cycle oscillations due to a supercritical Hopf bifurcation. The time evolution of the state variables is also represented.

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Section: Introductionmentioning

confidence: 99%

Stability analysis of the singular points and Hopf bifurcations of a tumor growth control model

Drexler,

Nagy,

Romanovski

2024

Math Methods in App Sciences

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“…positive or negative), so these methods cannot enforce the constraints imposed on the system input. The majority of physiological systems, such as blood glucose control systems [ 2 , 3 , 4 , 5 ], tumour growth modelling systems [ 6 , 7 , 8 , 9 , 10 , 11 ], chemical reaction systems [ 12 ] are positive input.…”

Section: Introductionmentioning

confidence: 99%

Robust positive control of tumour growth using angiogenic inhibition

Homayounzade,

Homayounzadeh,

Khooban

2023

IET Systems Biology

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In practice, many physical systems, including physiological ones, can be considered whose input can take only positive quantities. However, most of the conventional control methods do not support the positivity of the main input data to the system. Furthermore, the parameters of these systems, similar to other non‐linear systems, are either not accurately identified or may change over time. Therefore, it is reasonable to design a controller that is robust against system uncertainties. A robust positive‐input control method is proposed for the automatic treatment of targeted anti‐angiogenic therapy implementing a recently published tumour growth model based on experiments conducted on mouse models. The backstepping (BS) approach is applied to design the positive input controller using sensory data of tumour volume as feedback. Unlike previous studies, the proposed controller only requires the measurement of tumour volume and does not require the measurement of inhibitor level. The exponential stability of the controlled system is proved mathematically using the Lyapunov theorem. As a result, the convergence rate of the tumour volume can be controlled, which is an important issue in cancer treatment. Moreover, the robustness of the system against parametric uncertainties is verified mathematically using the Lyapunov theorem. The real‐time simulation results‐based (OPAL‐RT) and comparisons with previous studies confirm the theoretical findings and effectiveness of the proposed method.

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Model-Based Simulation and Comparison of Open-Loop and Closed-Loop Combined Therapies for Tumor Treatment

Csercsik

Sápi²,

Kovács³

2018

2018 IEEE Conference on Control Technology and Applications (CCTA)

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Targeted molecular therapies opened new ways and increased the efficiency of cancer therapies. Antiangiogenic therapy focuses against the growth of tumor by blocking the blood vessel formation of it. Its control engineering perspective has been presented several times, but its key point represents modeling the tumor growth. The purpose of our research is to go beyond the already published minimalistic approach and set up a bi-compartmental (vasculature-dependent tumor growth and angiogenesis) model. The aim of the current paper is to extend our recently published dynamical bicompartmetal model to include the effect of not only for antiangiogenic, but also cytotoxic drugs as well as input. We compare the effect of the two different inputs on the model dynamics in the context of final tumor volume, which can be used as a measure of therapy effectiveness. According to the model prediction, the combination of drugs is more efficient compared to either monotherapy. Furthermore, we compare an optimized open-loop protocol with a very simple intuitive feedback therapy solution.

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Potential Benefits of Discrete-Time Controller-based Treatments over Protocol-based Cancer Therapies

Cited by 10 publications

References 15 publications

Stability analysis of the singular points and Hopf bifurcations of a tumor growth control model

Stability analysis of the singular points and Hopf bifurcations of a tumor growth control model

Robust positive control of tumour growth using angiogenic inhibition

Model-Based Simulation and Comparison of Open-Loop and Closed-Loop Combined Therapies for Tumor Treatment

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