Modélisation de données pharmacologiques précliniques et cliniques d'efficacité des médicaments anti-angiogéniques en cancérologie

Aziz Ouerdani 1
1 NUMED - Numerical Medicine
UMPA-ENSL - Unité de Mathématiques Pures et Appliquées, Inria Grenoble - Rhône-Alpes
Abstract : Within the last 40 years, knowledge of tumor angiogenesis has literally exploded. In the seventies, Judah Folkman demonstrated that tumors need to be vascularized to continue to proliferate. Shortly after, the main protagonists of tumor angiogenesis have been discovered, as well as the mechanisms in which they are involved. The next decade is the beginning of the research on molecules with anti-angiogenic effects and in 2004 bevacizumab (Avastin, Roche), the first antiangiogenic drug used in oncology, was available for treating solid cancer patients. Along with this, the increasing interest of mixed-effects modeling coupled with advances in computer tools allowed developing more efficient methods of data analysis. In 2009, the regulatory agency FDA (Food and Drug Administration) in the United States has identified the central role of numerical modeling to better analyze the efficacy and toxicity preclinical and clinical oncology data. The aim of this project is to study the effects of different angiogenesis inhibitors on tumor dynamics, based on a population approach. The developed models are models based on ordinary differential equations and that integrate data and information from the literature. The objective of these models is to characterize the dynamics of tumor sizes in animals and patients in order to understand the effects of anti-angiogenic treatments and provide support for the development of these molecules, or to help clinicians for therapeutic decision making.
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Aziz Ouerdani. Modélisation de données pharmacologiques précliniques et cliniques d'efficacité des médicaments anti-angiogéniques en cancérologie. Modélisation et simulation. Université Grenoble Alpes, 2016. Français. ⟨NNT : 2016GREAM018⟩. ⟨tel-01496174⟩

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