Precision oncology means for a cancer patient, that he or she is treated with the best possible treatment, which is such exactly for him or her. It is not a standard treatment, but a treatment target to exactly the one patient who needs to be treated. One important instrument, to determine this personalised optimal treatment are mathematical models, which capture essential mechanisms of the disease, and statistics, which extracts individualised information from patient data. This project combines these two strengths: researchers from the University of Oslo (UiO) and the University of Minnesota (UMN), will teach and research at the interface between mathematics, cancer biology, clinical oncology, machine learning and statistics. Research will focus on estimating complex pictures of intra-tumour heterogeneity and on predicting optimal combined therapy for individual cancer patients. New methods for integrating patient data into mathematical models of cancer, can contribute to a better treatment of cancer patients. The project has access to unique data though an ample partnership with clinicians and biologists of the Oslo University Hospital. The project will develop new courses, at bachelor?s, master?s and PhD levels at UiO and UMN, in mathematical and statistical modelling of cancer. Together with the other students, postdocs and staff at UiO and UMN, this realises a new scientific community, who will benefit from across-the-Atlantic mobility, as soon as covid19 will allow it again. We will actively work for a better representation of female and under-represented-group scientist. This project strengthens internationalisation at UiO and UMN, with a new and long lasting alliance. Because of the travel restrictions due to Covid, in the first year we had weekly video meetings with staff and students, which leads us to be very well prepared to mobility, as soon as it will be possible.
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Precision oncology can greatly benefit from sharp mathematical models, which capture essential mechanisms, and statistics, which extracts individualised information from patient data. This project combines these two strengths: researchers from the University of Oslo (UiO) and the University of Minnesota (UMN), will teach and research at the interface between mathematics, cancer biology, clinical oncology, machine learning and statistics. Research will focus on estimating complex pictures of intra-tumour heterogeneity and on predicting optimal combined therapy for individual patients with blood or breast cancer. New methods for integrating patient data into mathematical models of cancer, can contribute to a better treatment of cancer patients. The project has access to unique data though an ample partnership with clinicians and biologists of the Oslo University Hospital. The project will develop new courses, at bachelor’s, master’s and PhD levels at UiO and UMN, in mathematical and statistical modelling of cancer. A course tailored to students in medicine and clinicians on opportunities and challenges of mathematics and algorithms will allow us to develop the needed language and communication skills. We shall jointly supervise of at least three PhD students and four master students. Together with the other students, postdocs and staff at UiO and UMN, this realises a new scientific community, who will benefit from across-the-Atlantic mobility and the participation to research kitchens, a new instrument to harvest the best and most ambitious ideas. Outreach will allow the project to communicate with patients and their organisation and with the general public. We will actively work for a better representation of female and under-represented-group scientist. This project strengthens internationalisation at UiO and UMN, with a new and long lasting alliance.