General information

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General information

Horizon 2020 Excellent Science


  • ERC-StG-2015

Proposal title:

  • Personalized Cancer Therapy by Model-based Optimal Robust Control Algorithm

Proposal number:

  • 679681

Proposal acronym:

  • Tamed Cancer

Duration in months:

  • 60

Project started:

  • 01.07.2016

Grant amount:

  • approximately EUR 1 million


  • Modern robust control
  • LPV model
  • model identification
  • targeted molecular therapy
  • antiangiogenic therapy

Host Institution:

  • Obuda University

Department(s) carrying out the proposed work in the Host Institution:

  • John von Neumann Faculty of Informatics

Principal Investigator:

  • Prof. Dr. Levente Kovács

Partner Organisation:

  • Semmelweis University

Department(s) carrying out the proposed work in the Partner Organisation:

  • 1st Dept. of Pathology and Experimental Cancer Research

Contact person of the Partner Organisation:

  • Prof. Dr. Zoltán Sápi


Prof. Dr. Levente Kovács, Principal Investigator
Address 1: Obuda University, John von Neumann Faculty of Informatics, Institute of Biomatics, H-1034 Budapest, Bécsi út 96/b. 4th floor
Phone 1: +36 1 666 5585
Address 2: Research and Innovation Center of Óbuda University, PhysCon Lab, Kiscelli utca 82, Budapest, H-1032
Phone 2: +36 1 666 5543

Krisztina Geresdi, research assistant
Address: Research and Innovation Center of Óbuda University, Kiscelli utca 80-82, Budapest, H-1032
Phone: +36 1 666 5585

Prof. Dr. Zoltán Sápi, medical coordinator
Address: Semmelweis University, 1st Department of Pathology and Experimental Cancer Research, H-1085 Budapest, Üllői út 26.
Phone: +36 1 459 1500/54457


Imagine if tumor growth would be reduced and then kept in a minimal and safe volume in an automated manner and in a personalized way, i.e. cancer drug would be injected using a continuous therapy improving the patient’s quality of life. By control engineering approaches it is possible to create model-based strategies for health problems. Artificial pancreas is an adequate example for this, where by continuous glucose measurement device and insulin pump it is possible to improve diabetes treatment. Gaining expertise from this problem, the current proposal focuses on taming the cancer by developing an engineering-based medical therapy. The interdisciplinary approach focuses on modern robust control algorithm development in order to stop the angiogenesis process (i.e. vascular system development) of the tumor; hence, to stop tumor growth, maintaining it in a minimal, “tamed” form. This breakthrough concept could revitalize cancer treatment. It is the right time to do it as some investigations regarding tumor growth modeling have been already done; now, it should be refined by model identification tools and validated on animal trials. The benefit of robust control was already demonstrated in artificial pancreas; hence, it could be adapted to cancer research. The result could end with a personalized healthcare approach for drug-delivery in cancer, improving quality of life, optimizing drug infusion and minimizing treatment costs. This interdisciplinary approach combines control engineering with mathematics, computer science and medical sciences. As a result, the model-based robust control approach envisage refining the currently existing tumor growth modeling aspects, design an optimal control algorithm and extend it by robust control theory to guarantee its general applicability. Based on our research background, validation will be done first in a manually controlled way, but then in an automatic mode to propose it for further human investigations.

Grant leaflet

Research Field – Medical & Engineering Interdisciplinary Research

  • The aim of antiangiogenic therapy is to stop the angiogenesis process (i.e. vascular system development) of the tumor; hence, to stop tumor growth
  • Modern robust control algorithms provides automated drug administration

Research Concept – Present & Future

  • In the present clinical practice there are general protocols for cancer therapies (like chemotherapy, radiotherapy)
    • these treatments have frequent and serious side effects
    • they are not cancer specific and not personalized for the patients
    • the treatment cost is low; however the usage is non-optimized
  • Our concept: controller-based individualized treatment
    • these treatments have virtually no side effect
    • it provides personalized administration of cancer specific (antiangiogenic) drugs
    • the treatment cost is duly low due to the optimal drug administration

Objectives of the Research – Model Identification & Controller Design

  • Create mathematical tumor growth model under angiogenic inhibition based on animal experiments
  • Create constant and variable quasi-continuous low-dosage therapy protocol
  • Design optimal robust control algorithms for continuous low-dosage therapy

Impact of the Research – Opening New Horizons in Cancer Treatment

  • Improve cancer therapy efficiency
  • Decrease treatment costs
  • Minimize side effects of the therapy
  • Improve the patient's quality of life (QoL)

Click here to download the grant leaflet in PDF form.

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