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Modeling And Control The Growth Of Cancer Tumors By Combining Antiangiogenic and Chemotherapy Treatments

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Amir Feizizadeh

on 17 September 2012

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Transcript of Modeling And Control The Growth Of Cancer Tumors By Combining Antiangiogenic and Chemotherapy Treatments

Modeling And Control The Growth Of Cancer Tumors By Combining Antiangiogenic and Chemotherapy Treatments By : Amir Feizizadeh Supervisor : Dr.Sadjad Ozgoli Dar in sal Erae Shod Moarefi Modele Ertegha Yafte Che Maziyat Haei Darad What's Cancer?

The Importance Of Modeling

Proposed Model Index: 1 2 3 4 Mathematical models of Mono and multi-therapy treatment

Introduction of improved models

Simulations results Genes in the nucleus control
the cell proliferation and cell death.
Disruption in normal cell proliferation or death Cancer is a genetic disease Uncontrolled proliferation of cells Tumor The Uncontrolled growth of cells Disruption of cell cycle replication

Interfere in cell death

Changes in cell death and
proliferation of others Cell Cycle کمبود اکسیژن Lack Of Oxygen Secretes Vascular Endothelial Growth Factor Opening of Capillary
Network Walls Growth of The Capillary Network Towards Tumor Development of capillary networks (Angiogenesis) Overview: Cancer is a genetic disorder disease

The cause: The change in the natural cell death and proliferation Failure of cancer treatments Lack of appropriate therapies







Lack of sufficient knowledgeabout cancer generating agents. The Benefits of Cancer Cells Modeling Predicting of treatment response

Predicting tumor growth in a risky conditions

Providing Training and consulting for
young doctors Classification of cancer
treatments Chemotherapy

Anti-angiogenic factors

Factors influencing cell cycle

Modern methods of therapy Anti-angiogenesis Model Hanfeldt 1999 Ergun 2003 Ledzewich 2005 Ledzewich 2009 Elementary Formulation Optimal Control Formulation The combination of radiation therapy
with antiangiogenic approach The combination of chemotherapy
with anti-angiogenic approach Mathematical model of
monotherapy: Tumor growth rate: The rate of Vascular
endothelial cells change: The result: A thorough optimal control analysis
was carried out on the model, for example, continuing treatment to the most effective moment till reaching the least amount of cell size. Mathematical Models of
Multi-therapy: The introduction of two control variables u and v, respectively,indicating the generation of chemotherapy and Anti-angiogenic agents. The initial results of optimal method showed that first Anti-angiogenic mustbe prescribed and at the end of the treatment period, a maximum dose of the chemotherapeutic agents be used. Determining the precise dose of medicine have always been a very important and notable issue for many researchers and practitioners More recent methods have fewer side effects. Result: Criticism of Ledzewich model Continuous injection of therapy agents Ignoring the rate of therapeutic agent loss in the body The role of the immune system in modelling Improved Model Chemotherapeutic agent in the
improved model: Regardless of the role of the immune system Improved Model Ledzewich Model Considering The Role Of Immune System Designing Continious PI Controller Designing Continious D Controller Simulation from clinical perspective Simulation With Controller PI Simulation With Controller D Secondary Lab Test P=13000

q=10000

Dose=110 Simulation from clinical perspective Simulation With Controller PI Simulation With Controller D Comparison Future Work Conclusion Thank you
for your
Attention! summer 2012 2 8/41 9/41 11/41 12/41 16/41 32 35 31/41 67 1. A practical experiment be performed in vitro 2. several chemotherapy drugs used to prevent the emergence of drug resistance 3. optimal controller designing 64 1. Highliting the role of clinical approach in modeling 2. Discrete Injection of therapeutic agents based on the existing practical treatment 3. Considering the role of the immune system in model 4.treatment Comparison via designed controllers based on clinical and therapeutic approach Designing Impulse PI Controller Designing Impulse D Controller 1/41 2/41 3/41 4/41 5/41 6/41 7/41 13/41 14/41 15/41 17/41 18/41 19/41 20/41 21/41 22/41 23/41 24/41 25/41 26/41 27/41 28/41 29/41 30/41 32/41 33/41 34/41 35/41 36/41 37/41 38/41 39/41 40/41
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