The two-year research project, funded by the National Research, Development and Innovation Office (NRDIH), is a consortium project led by Innovitech Ltd., GE Healthcare Hungary Ltd. and Széchenyi István University of Győr. The Petz Aladár University Teaching Hospital of Győr-Moson-Sopron County as a regional haematology centre and the University of Debrecen, one of Europe’s outstanding centres of oncological knowledge, are participating as clinical partners in the research and development.
Early diagnosis and personalised therapy are the key to effective cancer treatment. A joint R&D project is being launched to develop an IT decision support solution for oncology. Based on bioinformatics, genomics and diagnostic imaging data, the artificial intelligence (AI)-based development will target early diagnosis and precision medicine. The collaboration will result in the identification of disease-causing regulatory elements that will help to detect tumours earlier and identify new therapeutic approaches.
In many cases, genetic, epigenetic distortions are behind cancers that are easily misdiagnosed. Early detection, personalised therapy and the time from diagnosis to treatment are the primary determinants of survival.
The collaboration of the consortium partners was prompted by the limited availability of biotechnology and IT solutions to support oncology diagnostics and the definition of personalised therapy. The project aims to investigate the genetic determinants of cancer and their functional significance using different epigenetic methods and information technology approaches.
The innovation potential of the project is further broadened by the common goal of spatial simulation of the genome. The new solution will allow the analysis of spatial and structural distortions of genomes from different cellular states, the analysis of identified functional genomic mutational variations and the correlations between oncological and clinical data. This new technology will provide physicians with a better understanding of the underlying causes and mechanisms of disease, allowing them to choose a more informed and targeted therapy and to predict more accurately the likely outcome of the disease.