Innovative Infrastructure to Enhance the California Teachers Study

 描述（由申请人提供）：癌症流行病学队列（CEC）为癌症研究做出了独特的贡献，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，将继续推动科学和改善健康。CEC的基础设施应使其能够最大限度地发挥其数据和生物标本的价值，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-需要改进，如果CEC要保持可持续性和生产力，因为大数据带来的机遇和挑战不断增长，改变生物医学研究。在加州教师研究（CTS），一个正在进行的前瞻性CEC的133，479名女性公立学校专业人员，我们的新的生物库项目证明，一个既定的CEC可以成功地利用现有的云计算和集成的移动的技术，以收集数以千计的高质量的注释生物标本更快，更安全，更具有成本效益。本应用程序的目标是a）将我们的创新方法扩展到所有其他CTS基础设施活动，以及B）记录此方法的效率增益，以创建其他研究可以考虑的实用蓝图。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调查人员能够实时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，从而显著改善我们存储、使用和共享大量CTS数据的方式。2)我们将实施一种新的数据收集模式，以参与者喜欢的格式（网络、平板电脑、智能手机或纸张）向他们发送个性化的调查问卷，并实时接收干净的、可供分析的数据。这将使参与者更容易提供数据，也使我们更容易收集更多更好的数据。3)我们将建立安全的门户网站，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团队进行沟通。这将改变CTS与参与者的互动方式。4)我们将公开和广泛地与其他正在考虑为其独特的基础设施采用类似方法的CEC分享我们的进展。在这个为期5年的项目中，我们将用这个新的互联环境取代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曝光和端点数据，但要以更好的方式进行;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，前瞻性的CEC应该定位自己，以连接并在这些环境中运行。CTS是首批成功采用云计算和移动的的大型CEC之一。该应用程序描述了我们详细的、数据驱动的和实用的计划，以扩展我们的新成就，改善CTS核心基础设施，并作为希望采用类似创新基础设施的其他CEC的模型。

 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.