Next Generation Tools For Genome-Centric Multimodal Data Integration In Personalised Cardiovascular Medicine

个性化心血管医学中以基因组为中心的多模式数据集成的下一代工具

• 批准号: 10104323
• 金额: $ 215.27万
• 依托单位: QUEEN MARY UNIVERSITY OF LONDON
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10104323
• 关键词: Next; Generation; Tools; Genome; Centric

Healthcare is the fasted growing EU27 expenditure. Personalised medicine, comprising tailored approaches for prevention, diagnosis, monitoring and treatment is essential to reduce the burden of disease and improve the quality of life. Integration of multiple data types (multimodal data) into artificial intelligence models is required for the development of accurate and personalised interventions. This is particularly true for the inclusion of genomic data, which is information-rich and individual-specific, and more routinely available as the cost of sequencing continues to fall. Multimodal data integration is complex due to privacy & governance requirements, thepresence of multiple standards, distinct data formats, and underlying data complexity and volume. NextGen tools will remove barriers in data integration several cardiovascular use cases. NextGen deliverables 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; improved clinical efficiency of variant prioritisation; scalable genomic data curation; and improved data discoverability and data management. A comprehensive gap analysis of the existinglandscape, factoring ongoing initiatives will ensure NextGen deliverables are forward-looking and complementary. NextGen embedded governance framework and robust regulatory processes will ensure secure multi-jurisdictional multiomic multimodal data access aligned with initiatives including “1+ Million Genomes” and the European Health Data Space. Several real-world pilots will demonstrate the effectiveness of NextGen tools and will be integrated in the NextGen Pathfinder network of five collaborating clinical sites as a selfcontained data ecosystem and comprehensive proof of concept.

医疗保健是禁食的EU27支出。个性化医学，完成预防，诊断，监测和治疗的量身定制方法对于减少疾病的燃烧和改善生活质量至关重要。开发准确和个性化的干预措施需要将多种数据类型（多模式数据）集成到人工智能模型中。对于包含信息丰富且特定于个人特定的基因组数据而言，尤其如此，并且随着测序的成本继续下降而更常规地获得。由于隐私和治理要求，多个标准的说明，不同的数据格式以及潜在的数据复杂性和音量，因此多模式数据集成是复杂的。 NextGen工具将消除数据集成的障碍，几个心血管用例。 NextGen交付成果将包括用于多模式数据集成和研究可移植性的工具，将安全联合分析扩展到基因组计算，对分布式基础架构的更有效的联合学习，更有效，更有效的基因组数据分析工具；提高了变异优先级的临床效率；可扩展的基因组数据策展；并改善了数据可发现性和数据管理。对现有景观的全面差距分析，进行了持续的计划，将确保NextGen Exavilables具有前瞻性和完整。 NextGen嵌入式治理框架和强大的监管流程将确保安全的多界多模式数据访问与包括“ 1+百万个基因组”和欧洲健康数据空间在内的计划相符。几支实际钢琴将展示NextGen工具的有效性，并将集成到NextGen Pathfinder网络中，该网络由五个合作的临床站点作为一个独立的数据生态系统和全面的概念证明。