WELD: Integrated Cyber-Infrastructure for Scalable Data-Driven Research into COVID-19

该项目将实施基于自动化机器可操作政策的统一网络基础设施，这将使四个国家的数据驱动临床和医学研究成为可能，并为英国应对COVID-19疫情的快速决策提供必要的证据。该研究探索了综合计算、建模、仿真和信息技术的发展，作为研究COVID-19和SARS-CoV-2的合作团队跨学科研究的基础。该应用程序将实现一个“云原生”软件基础设施，用于跨可信研究环境联合分布式医疗保健数据，并包括处理集成数据集合的方法。该结果将量化地改进现有的基于模型和统计的方法，用于评估疫苗效力和在临床研究环境中使用NHS实时数据进行风险预测。一个独特的贡献将是“基于政策的”数据联合技术，它允许每个下放的国家或可信研究环境控制其对共享的全英国范围的数据收集的使用，跨越监管边界，同时防止数据泄露。这一从未得到解决的能力，对于在全英国范围内为有效的数据分析和科学发现COVID-19提供安全的证据基础至关重要。该方法借鉴了最先进的数据抽象和虚拟化水平，为整个生命周期的自动化和重用提供了更大的灵活性，并满足了对数据和元数据的更系统化、基于社区的方法作为共享解决方案的一部分的需求。该架构模型将指导HDR-UK应对COVID-19和未来需要提高技术准备水平的流行病的战略决策。

The project will implement a unifying cyberinfrastructure based on automated machine-actionable policies that will enable data-driven clinical and medical research across the four nations and produce evidence essential for making rapid decisions on the UK's response to the COVID-19 outbreak. The research explores the development of integrated computing, modelling, simulation, and information technologies as the basis of cross-disciplinary research for collaborating teams investigating COVID-19 and SARS-CoV-2. The application will implement a "cloud native" software infrastructure for federating distributed healthcare data across the Trusted Research Environments and include methods for working with ensemble collections of data. The result will quantifiably improve existing model- and statistically- based methodologies for evaluating vaccine efficacy and risk prediction using live NHS data in clinical research environments. A unique contribution will be "policy-based" data federation techniques that allow each devolved nation or Trusted Research Environment to control its use of a shared UK-wide data collection, across regulatory boundaries, while guarding against data exfiltration. This capability, which has never been addressed, is fundamental to providing a secure evidence base for effective data analysis and scientific discovery of COVID-19 at UK-wide levels. The methodology draws on state-of-the-art in data abstractions and virtualisation levels, provides greater flexibility for automation and re-use across the lifecycle, and addresses the need for a more systematic, community-based approach to data and metadata as part of a shared solution. The architectural model will instruct HDR-UK strategic decision-making responding to COVID-19 and future pandemics that require an improved technology readiness level.