Novel Use of Emergent Technologies to Improve Efficiency of Animal Model Research

新兴技术的新用途提高动物模型研究的效率

• 批准号: 9354497
• 负责人: Charles J Donnelly
• 金额: $ 73.94万
• 依托单位: ROCKSTEP SOLUTIONS, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9354497
• 关键词: Address; Algorithms; Animal Experimentation; Animal Model; Animal Welfare; Animals; Biological Process; Biomedical Research; Clinical Laboratory Information Systems; Cloud Computing; Collaborations; Communication; Communication Tools; Communications Media; Complex; Computer software; Computers; Consumption; Cost Savings; Custom; Data; Data Analyses; Data Analytics; Data Security; Data Set; Data Storage and Retrieval; Databases; Development; Devices; Emerging Technologies; Ensure; Equipment; Equipment and supply inventories; Event; Feedback; Future; Goals; Health; Health system; Human; Industry; Information Management; Internet; Internet of Things; Investments; Laboratories; Laboratory Animals; Laboratory Research; Lead; Machine Learning; Management Information Systems; Methods; Modernization; Monitor; Motion; Multimedia; Notification; Paper; Performance; Phase; Procedures; Process; Production; Protocols documentation; Publishing; Research; Research Infrastructure; Research Personnel; Rest; Risk; Science; Secure; Services; Site; Stream; System; Techniques; Technology; Testing; The Jackson Laboratory; Time; Transact; United States National Institutes of Health; analytical tool; base; cloud based; commercialization; computerized data processing; cost; cost effective; data acquisition; data management; design; encryption; experimental study; good laboratory practice; graphical user interface; handheld mobile device; improved; innovation; laptop; member; novel; novel strategies; predictive modeling; programs; prototype; public health relevance; service learning; social media; software as a service; success; time interval; tool; trend; usability

 DESCRIPTION (provided by applicant): This Phase II project aims to continue development of a commercial quality, innovative cloud hosted information management system, called Climb 2.0(tm) that will increase laboratory efficiency and provide improved capabilities for research laboratories. Climb is designed to offer integrated laboratory process management modules that include mobile communications tools data monitoring and alert systems, and integrated access to Microsoft Azure Cloud(tm) Machine Learning and Stream Analytics services. Initially, Climb 2.0 will target animal model research laboratories; however, the core of the platform is designed to be adaptable to nearly any research type or related industry. Current research information management systems are primarily designed as record-keeping tools with little or no direct focus on laboratory efficiency or in enhancing value of the research data. They also do not leverage emergent mobile device technologies, social media frameworks, and data analysis and storage capabilities of cloud computing. Many laboratories still use paper as their primary recording system. Paper data logging is then followed by secondary data entry into a laboratory database. These systems are error prone, time consuming and lead to laboratory databases with significant time lags between data acquisition and data entry. Moreover, they do not recognized cumulative data relationships, which may identify important trends, and researchers often miss windows of opportunity to take action on time-sensitive events. In Phase I, RockStep Solutions demonstrated feasibility of an innovative Cloud Information Management Bundle system, Climb, which will increase efficiency and improve capabilities in animal model data management. During Phase I, a beta version of Climb was successfully developed and tested against strict performance metrics as a proof of concept. We successfully built a prototype with working interfaces that integrates real-time communication technologies with media capabilities of mobile devices. Phase II proposes four specific Aims: 1) Develop the technology infrastructure to support the secure and scalable Software as a Service (SaaS) deployment of Climb for enterprise commercial release; 2) Develop and extend the Phase-I prototype Data Monitoring and Messaging System (DMMS) into a platform ready for production use; 3) Extend Climb's DMMS adding a Stream Analytics engine to support Internet of Things (IoT) devices and streaming media; 4) Deploy a beta release of Climb at partner research labs, test and refine the product for final commercialization. To ensure Climb is developed with functionality and tools relevant to research organizations, RockStep Solutions has established collaborations with key beta sites to test all of the major functionality developed in this proposal. IMPACT: By leveraging emergent technologies and cloud computing, Climb offers several advantages: 1) enables real-time communications using familiar tools among members of research groups; 2) reduces the risk of experimental setbacks, and 3) enables complex experiments to be conducted efficiently.

 描述（由申请人提供）：该第二阶段项目旨在继续开发商业质量的创新云托管信息管理系统，称为 Climb 2.0(tm)，该系统将提高实验室效率并为研究实验室提供改进的功能。提供集成的实验室流程管理模块，包括移动通信工具、数据监控和警报系统，以及对 Microsoft Azure Cloud(tm) 机器学习和流分析服务的集成访问。最初，Climb 2.0 将针对动物模型研究。实验室；然而，该平台的核心旨在适应几乎任何研究类型或相关行业，当前的研究信息管理系统主要设计为记录保存工具，很少或没有直接关注实验室效率或提高实验室价值。他们也不利用新兴的移动设备技术、社交媒体框架以及云计算的数据分析和存储功能。许多实验室仍然使用纸张作为主要记录系统，然后进行辅助数据输入。这些系统很容易出错，耗时，导致实验室数据库在数据采集和数据输入之间存在显着的时间滞后。此外，它们无法识别可能识别重要趋势的累积数据关系，并且研究人员经常错过对时间敏感事件采取行动的机会。在第一阶段，RockStep Solutions 展示了创新的云信息管理捆绑系统 Climb，该系统将提高动物模型数据管理的效率和能力。在第一阶段，成功开发了 Climb 的测试版，并根据严格的性能指标进行了测试。作为概念证明。构建了一个工作界面原型，将实时通信技术与移动设备的媒体功能集成在一起，第二阶段提出了四个具体目标：1）开发技术基础设施以支持 Climb 的安全且可扩展的软件即服务 (SaaS) 部署。企业商业版本； 2) 开发第一阶段原型数据监控和消息传递系统 (DMMS) 并将其扩展为可供生产使用的平台； 3) 扩展 Climb 的 DMMS，添加流支持物联网 (IoT) 设备和流媒体的分析引擎；4) 在合作伙伴研究实验室部署 Climb 测试版，测试和完善产品以实现最终商业化。 RockStep Solutions 已与主要测试站点建立了合作，以测试本提案中开发的所有主要功能。 IMPACT：通过利用新兴技术和云计算，Climb 具有以下优势：1) 能够在成员之间使用熟悉的工具进行实时通信。研究小组；2) 降低实验失败的风险，3) 使复杂的实验能够有效地进行。