Model Driven Computation of Treatments for Infertility Related Endocrinological...
Model Driven Computation of Treatments for Infertility Related Endocrinological Diseases
Infertility affects 12% to 15% of reproductive age couples in Europe, costs approximately 1 billion Euros per year, and experts agree that these figures will double in a decade. In about 50% of such couples, infertility is caused...
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Descripción del proyecto
Infertility affects 12% to 15% of reproductive age couples in Europe, costs approximately 1 billion Euros per year, and experts agree that these figures will double in a decade. In about 50% of such couples, infertility is caused by female health problems, more than 40% of which are related to endocrinological diseases impairing women's health independently from fertility. Such considerations motivate our three-pillar project focusing on quantitative models for Infertility Related Endocrinological Diseases (IREDs).<br/>Our first pillar (modelling) will develop patient-specific computer-based models for IRED. Such models will account for the physiological and pathophysiological mechanisms regulating the menstrual cycle and how this is influenced by external (e.g., drugs) as well as environmental (e.g., obesity) factors. Our model will enable a quantitative understanding of the mechanisms behind endocrine disorders such as Polycystic Ovarian Syndrome (PCOS), hyperprolactinemia or endometriosis.<br/>Our second pillar (computation) will develop general purpose methods and tools to support effective exploitation of patient-specific models to reliably predict the outcome of a treatment on a specific patient and to support individualisation of a treatment for a specific patient.<br/>Our third pillar (clinical trial) will gather data (e.g. hormonal secretion patterns in different physiological and pathophysiological settings) to enable validation of the models and tools developed in our project and will carry out such a validation thereby providing feedback to the previous pillars. Such a feedback loop will drive the iterative refinement approach foreseen in our project.<br/>Our multidisciplinary consortium consists of highly qualified research institutions (HSLU, URM1, ZIB), and hospitals (MHH, UZH). The resulting synergies will enable successful completion all project objectives as well as wide dissemination and effective exploitation of the project results.