The EU funded project IASiS tried to pave the way for precision medicine approaches by utilising insights from patient data. It aimed to combine information from medical records, imaging databases and genomics data to enable more personalised diagnosis and treatment approaches in two disease areas – lung cancer and Alzheimer’s disease.
After three years of fruitful collaboration between 10 partners from 5 countries and important scientific breakthroughs in the field of precision medicine, the iASiS project, coordinated by NCSR Demokritos, was completed in June 2020.
Analysis of Big Data in healthcare, including patient information, omics data, as well as images, still poses a major challenge. Although the technology to obtain Big Data has advanced, the infrastructure to integrate and mine the data lags behind. To improve healthcare decisions and policy making, there is a need to turn Big Data into actionable information.
iASiS researchers developed an artificial intelligence (AI) platform that integrates and analyses heterogeneous data from different sources, such as hospital patient records, genetic databases, and literature, to support researchers and policy makers in assessing interesting hypothesis or unveil completely novel associations. For instance, the combined administration of drugs for cancer patients having a specific mutation may be associated with disease prognosis, suggesting the personalisation of treatment.
During the project, the iASiS technology was applied and tested for two major diseases, lung cancer and dementia, where personalised therapy is essential.