Innovative Infrastructure to Enhance the California Teachers Study

 描述(申请人提供)：癌症流行病学队列(CEC)为癌症研究做出独特的贡献，并将在未来发挥更大的作用，因为新的发现，特别是在基因组学领域，继续推动科学和改善健康。CEC的基础设施应该使其能够最大限度地发挥其数据和生物样本的价值，但当前CEC基础设施的许多常见组件--例如如何收集、管理、分析、集成和共享数据--如果CEC要保持可持续和高效，就需要改进，因为大数据改变了生物医学研究的日益增长的机遇和挑战。在加州教师研究(CTS)中，我们的新型生物库项目证明，现有的CEC可以成功地利用现有的云计算和集成的移动技术来更快、更安全、更经济地收集数千种高质量的带注释的生物标本。这项申请的目的是a)将我们的创新办法推广到所有其他CTS基础设施活动，b)记录这一办法的效率收益，以制定其他研究可以考虑的实际蓝图。该项目有四个具体目标1)我们将创建一个全面、安全的云数据管理和分析系统，将所有CTS数据集成到一个基于云的专用数据集市中，使CTS调查人员能够按需访问所有现有和未来的CTS数据、分析和研究信息。这将使CTS数据管理现代化，显著改善我们存储、使用和共享大量CTS数据的方式。2)我们将实施新的数据收集模式，以参与者选择的格式(Web、平板电脑、智能手机或纸质)向他们发送个性化调查问卷，并实时接收干净、可供分析的数据。这将使参与者更容易提供数据，使我们更容易收集更多和更好的数据。3)我们将建立安全门户，允许参与者更新他们的数据，查看研究信息，并与他们的同行和CTS团队进行交流。这将改变CTS与我们参与者的互动方式。4)我们将公开和广泛地与正在考虑对其独特的基础设施采用类似方法的其他CEC分享我们的进展。在这个5年的项目中，我们将用这个新的互联环境取代我们以前的数据基础设施；我们将继续从CTS参与者那里收集新的风险暴露和终端数据，但会以更好的方式这样做；我们将完成一系列概念验证分析项目，以展示这种新方法的优势。研究企业的关键部分，如大规模基因组学和复杂的索赔数据，越来越多地基于云，具有前瞻性的CEC应该定位自己，以便与这些环境连接并在这些环境中运营。CTS是首批成功采用云计算和移动技术的大型CEC之一。本申请描述了我们详细、数据驱动且实用的计划，以扩展我们的新成就以改进CTS核心基础设施，并为希望采用类似创新基础设施的其他CEC提供示范。

 DESCRIPTION (provided by applicant): Cancer epidemiology cohorts (CECs) uniquely contribute to cancer research and will play an even larger role in the future as new discoveries, especially in the area of genomics, continue to advance science and improve health. A CEC's infrastructure should enable it to maximize the value of its data and biospecimens, but many common components of current CEC infrastructure-such as how data are collected, managed, analyzed, integrated, and shared-need to improve if CECs are to remain sustainable and productive as the growing opportunities and challenges of Big Data transform biomedical research. In the California Teachers Study (CTS), an ongoing prospective CEC of 133,479 female public school professionals, our novel biobanking project proves that an established CEC can successfully leverage existing cloud computing and integrated mobile technology to collect thousands of high-quality annotated biospecimens more quickly, securely, and cost-effectively. The objectives of this application are to a) extend our innovative approaches to all other CTS infrastructure activities and b) document the efficiency gains of this approach to create a practical blueprint that other studies could consider. This project has four specific aims 1) We will create a comprehensive, secure, cloud data management and analysis system that integrates all CTS data in one cloud-based dedicated Data Mart that gives CTS investigators on-demand access to all existing and future CTS data, analyses, and study information in real-time. This will modernize CTS data management to markedly improve how we store, use, and share the extensive CTS data. 2) We will implement a new data collection model that sends participants personalized questionnaires in the format they choose-web, tablet, smartphone, or paper-and receives clean, analysis-ready data in real-time. This will make it easier for participants to provide data and for us to collect more and better data. 3) We will establish secure portals that permit participants to update their data, view study information, and communicate with their peers and the CTS team. This will transform how the CTS interacts with our participants. 4) We will openly and broadly share our progress with other CECs that are considering adopting similar approaches for their unique infrastructures. During this 5-year project, we will replace our previous data infrastructure with this new, connected environment; we will continue to collect new exposure and endpoint data from CTS participants but do so in better ways; and we will complete a series of proof-of-concept analytic projects that demonstrate the advantages of this novel approach. Key parts of the research enterprise, such as large-scale genomics and complex claims data, are increasingly cloud-based, and forward-looking CECs should position themselves to connect with and operate in those environments. The CTS is one of the first large-scale CECs to successfully adopt cloud computing and mobile. This application describes our detailed, data-driven, and practical plan to extend our novel achievements to improve CTS core infrastructure and serve as a model for other CECs that wish to adopt similarly innovative infrastructure.