Genomic Data for Personalised Medicine
Personalised medicine is one of the main approaches to address the issues of increasing demand for healthcare and the economic burden on health, driven by demographic evolution, the aging population, the chronicisation of diseases.
Personalised medicine uses unique environmental, genetic, and medical information to individualise the prevention, diagnosis, monitoring, and treatment of disease. By doing so, the quality of care is improved, quality of life enhanced, and the societal burden of disease reduced. To develop personalised medicine, many different types of information (multimodal) need to be integrated and used together in a meaningful way, which is challenging, and many obstacles stand in the way. In particular, ensuring the effective use of information from our genes and how they function (multiomic) is essential and is an area with many unsolved challenges.
In NextGen, the consortium is building novel and synergistic tools to enable portable multimodal, multiomic and clinically oriented research in high-impact areas of cardiovascular medicine. NextGen tools will benefit researchers, innovators and healthcare professionals by identifying and overcoming health data linkage barriers in exemplar use cases which are complex or intractable with existing technology. Consequently, it will benefit patients, providing faster diagnosis, and better treatments (including personal medicine).
A comprehensive gap analysis of the existing landscape, factoring in ongoing initiatives will ensure NextGen deliverables are forward-looking and complementary.
In particular, the NextGen embedded governance framework and robust regulatory processes will ensure secure multi-jurisdictional phenotype and genomic data access aligned with initiatives including “1+ Million Genomes” and European Health Data Space.
The NextGen tools approach
NextGen tools focuses its genomics-founded approach on the data integration of a wide range of cardiovascular use cases and using the relevant datasets to construct a thematic dataspace and its operational and technological management functions, working out solutions for data integration. These will overcome the hurdles of privacy & governance requirements, the presence of multiple standards, distinct data formats, and underlying data complexity and volume of multimodal data.
The research action of NextGen starts with an initial comprehensive gap analysis of the existing landscape, and, based on this developing specific solutions, with the factoring of ongoing initiatives and embedding a governance framework and robust regulatory processes, which will not only act as an enabler for the dataspace, but also ensure forward-looking and complementary solutions.
The practical outcomes of NextGen Tools will include
- tooling for multimodal data integration and research portability, extension of secure federated analytics to genomic computation, more effective federated learning over distributed infrastructures, more effective and accessible tools for genomic data analysis;
- approaches providing improved clinical efficiency of variant prioritisation;
- scalable genomic data curation;
- and improved data discoverability and data management.
