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

In medical practice, the effectiveness of fighting cancer is not only determined by the composition of the used drug, but determ ined by the administration method as well. As a result, having drugs with a suitable action profile is just a promising beginning, but without appropriate delivery method s , the therapy still can be ineffective. Finding the optimal biologic dose is an empir ical process in medical practice; however, using controllers, an automated optimal administration can be determined . In this paper , we evaluate the effectiveness of different drug delivery protocols; using in silico simulations (like bolus dose s, low - dose metron omic regimen and continuous infusion therapy ). In addition, we compare these results with discrete - time controller - based treatments containing state feedback, setpoint control, actual state observer and load estimation

Model-based Angiogenic Inhibition of Tumor Growth using Modern Robust Control Method

Cancer is one of the most destructive and lethal illnesses of the modern civilization. In the last decades, clinical cancer research shifted towards molecular targeted therapies which have limited side e�ects in comparison to conventional chemotherapy and radiation therapy. Anti-angiogenic therapy is one of the most promising cancer treatment methods. The dynamical model for tumor growth under angiogenic stimulator/inhibitor control was posed by Hahnfeldt et al. (1999), and it was investigated and partly modi�ed many times. In this paper, a modi�ed version of the originally published model is used in order to describe a continuous infusion therapy. To generalize individualized therapies a robust control method is proposed using H 1 methodology. Uncertainty weighting functions are determined based on the real pathophysiological case and simulations are performed on di�erent tumor volumes to demonstrate the robustness of the proposed method

Parameter optimization of H∞ controller designed for tumor growth in the light of physiological aspects

According to the fact that cancer diseases are leading causes of death all around the world, development of cancer fighting therapies is necessary. Beside the medical knowledge, there is an extra need for engineering approach to solve this complex problem. The aim of this paper is to design controller for tumor growth under angiogenic inhibition, which on the one hand minimizes the input signal as far as possible (in order to have less side effects and greater cost-effectiveness) and on the other hand results in appropriately low tumor volume. Since the model contains uncertainties and measurement noise, the controller was designed using modern robust control methodology. Choosing of the ideal system and the weighting functions were done in the light of physiological aspects