The PhD Programme in 'Network Oncology and Precision Medicine' offers cutting-edge training in the field of personalized oncology, to train a new profile of researchers characterized by the convergence of different skills capable of integrating clinical and biological parameters to optimize stratification and the therapeutic and prevention strategies of cancer patients in the context of network oncology.
The PhD Programme welcomes master's degree graduates with medical-biological and scientific-technological educational backgrounds.
The three-year training plan is divided into didactic-scientific activities that aim to provide skills necessary to integrate biological, clinical, and diagnostic data through computational analysis to formulate the best personalized therapeutic strategy.
The relevance of this training course is determined by the need to integrate the numerous bio-molecular, clinical, and "omics" data of each patient, to develop personalized therapies.
Currently, the clinical impact of 'omics' data is limited because there is a lack of technological tools to effectively integrate them with the data more traditionally used in clinical practice and of a communicative register between the various professionals involved in the cancer patient's journey.
The different types of data available today for each patient (clinical, molecular, immunological, anatomopathological and imaging data), due to their complexity and dynamics, require new analysis techniques (networks) to be processed and used by both the oncologist and the pharmaceutical industry.
Therefore, the training of professionals with skills from different disciplines is necessary to analyze and integrate these data effectively.
The PhD Programme offers a wide range of training activities (lectures and seminars) and research activities (bio-molecular and clinical-translational) conducted in the laboratories and facilities available at the structures belonging to the PhD Program.
In these research and assistance "hubs", PhD students will be able to develop new models and algorithms based on innovative computational approaches, such as network medicine, applied to oncology which will be necessary for the development of personalized therapies.
The research projects are characterized by their multidisciplinary and transdisciplinary nature, combining basic research with clinical/translational research. This approach will allow PhD students to develop innovative and competitive skills at a national and international level, facilitating the technological transfer of therapeutic targets and the creation of diagnostic methodologies and algorithms in the oncology field. Some of the College's professors and PhD students are involved in projects aimed at technological improvement and development.
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