Using real-world big data from ehealth, biobanks and national registries, integrated with clinical trial data to improve outcome of severe mental disorders
Mental disorders represent one of the largest burdens for the European Health Care system, due to large number of patients and a lack of efficient treatment options. Today, drug treatment of mental disorders is characterized by severe adverse effects and suboptimal response in more than a third of the patients. Optimizing treatment is based on a trial-and-error approach, which combined with frequent multi-morbidities, often leads to polypharmacy and poor outcome. Due to limited understanding of the disease mechanisms that underlie mental disorders, new drugs with novel therapeutic targets are lacking, and existing treatments are ineffective for many people. It is therefore urgent that cutting-edge research approaches are deployed to develop innovative tools to individualize treatments using available psychiatric medication, and thus improve clinical outcomes and reduce costs for health care systems. The main goal of the multidisciplinary REALMENT project is to optimize treatment of mental disorders through novel precision medicine strategies based on current pharmaceutical options. REALMENT includes world leading research institutes and pharmaceutical industry at the very forefront of mental disorder research. REALMENT will achieve its objectives by exploiting population-scale Real-World Data (RWD) in combination with Randomized Clinical Trial (RCT) data available to the partners. Big data from populations (Nordic registries), cohorts (European biobanks), and eHealth samples (medical records), including whole genome genotypes (n=1.9 million), will be analysed in an EU-wide sustainable infrastructure using artificial intelligence and machine learning to develop prediction and stratification tools (precision psychiatry). These algorithms will be validated in large RCT data (n=10k) and re-phenotyping projects, and implemented in a clinical management platform (4MENT), which will be made available to provide decision support to clinicians to optimize therapeutic effects.