About IPerglio

Glioblastoma (GBM) is a particularly aggressive form of brain tumour with an average survival time of less than 15 months. New treatment strategies to improve the care of GBM patients are urgently needed, as the standard therapy for GBM has not changed for over 15 years. Several clinical trials have investigated the benefits of immunotherapies that use the body’s own immune system to fight the cancer, and 10-20% of patients have been reported to survive long-term. However, as disease progression and progression varies greatly from patient to patient, we currently lack clear indicators (known as biomarkers) that could guide researchers and clinicians as to which approach is most appropriate for individual patients.

The project ‘Improving personalised glioblastoma care by intertwined immunomics and artificial intelligence approaches’ (IPerGlio) is an international research project that brings together researchers from Norway, Italy, Luxembourg, Spain and Germany to tackle this problem. The clinical centres in Norway and Italy collect patient data (including demographic and clinical data as well as data on a patient’s lifestyle and blood and tumour samples), which is then combined with data from public databases and analysed by the partners in Luxembourg and Spain. The analysis is carried out with the help of artificial intelligence (AI). With the help of AI, we hope to find patterns in the patient data that will enable us to improve GBM care.

In order to further improve international GBM research, we would like to publish our data so that other researchers can expand our knowledge of this disease. We are aware that this may raise difficult ethical questions regarding data security and privacy. For this reason, the German project partner is organising a Stakeholder Consensus Conference (SCC) on how a publicly accessible database should be implemented.

The IPerGlio project is divided into several work packages (WPs), each of which is led by one of the project partners. Further information on the tasks assigned to these work packages can be found here on the homepage.