Title: Mathematical oncology for the clinics: Predicting cancer’s behavior and optimizing treatments
Cancers are hundreds of diseases involving uncontrolled cell proliferation and invasion of normal tissues. Cancer is currently the second leading cause of death in Europe. In spite of the huge resources invested, cancer has not been beaten and improvements in overall survival are in the range of 1-2% per year.
In this talk I will present examples of how mechanistic mathematical models fed with human data can be used to provide answers to compelling clinical questions.
First, I will discuss examples of image-based biomarkers -quantitative variables- suggested from mathematical models provide relevant survival information in glioblastoma, the most lethal type of brain tumor, patients. Also biomarkers for lung and breast cancer will be described based on similar concepts. Next, I will show how simple mathematical concepts can help in solving a critical problem in the management of brain metastases. Finally, I will present a success story of how to improve the design of clinical trials and patient management in-silico using mathematical models. I will also discuss other examples of the use of mathematical models as computational test beds to find optimal treatment schedules/combinations in oncology with potential to provide substantial benefits both for patients and for public health systems.
Access to the streaming link is shared with the ESMTB subscription list a few days before the colloquium.
Recorded talk: https://youtu.be/OOnSvnemVNE
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