The prediction and early diagnosis research area aims to understand the disease-specific and common molecular mechanisms underlying neurodegenerative diseases and epilepsy, and to identify novel biomarkers and therapeutic targets for the prevention and cure by merging computational and biological neurosciences. Machine learning-based prediction tools will be integrated with high-level legal and social science expertise on patient rights, and neuro-ethics. Co-creative collaboration processes and innovation outcomes will be studied holistically from management and organization, as well as socio-legal perspectives.
The prevention and treatment research area aims to promote collaborative innovation across networks and ecosystems where novel therapies are developed, tested, and launched for treating neurodegenerative diseases and epilepsy. Together with the key intersectoral partners, such as companies, patient organizations and hospitals, the research will focus on new drug candidates, multi-domain lifestyle-based interventions and personalised medicine-based treatments. For high-level outcomes, machine learning approaches will be used to identify asymptomatic individuals at high risk and patients for specific treatments and predict therapy response. Intersectoral co-innovation processes will be studied, and research designs will be guided by legal expertise on law and neuro-ethics, as well as stakeholder and patient-oriented research approaches.
The technologies, methods and models research area aims to understand and improve knowledge transfer across research teams and from university to industry. Research in this area focuses on emerging technologies, such as artificial intelligence (AI) -based data analyses, multiomics, experimental MRI techniques and multiscale imaging. These approaches will be applied to different patient and population-based cohorts, biological samples, genetically modified animal models as well as the humanized disease models. Algorithms and competence on inverse problems will be utilised, together with legal expertise on privacy, data protection and data-sharing policies. Entrepreneurial innovation processes will be studied to achieve success in research commercialisation.