Use Mobile Devices and Cloud Computing Platforms for Real-time Data Solutions in

使用移动设备和云计算平台实现实时数据解决方案

• 批准号: 8530198
• 负责人: Edward Lin
• 金额: $ 61.69万
• 依托单位: BAYESSOFT, INC.
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-03-15 至 2014-12-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8530198
• 关键词: Adverse event; Architecture; Area; Behavioral; Blinded; Businesses; Caring; Case Report Form; Client; Clinical Research; Clinical Trials Design; Cohort Studies; Comb animal structure; Computer software; Conduct Clinical Trials; Data; Data Analyses; Data Base Management; Data Collection; Data Quality; Data Storage and Retrieval; Databases; Development; Devices; Drug Combinations; Drug Industry; Electronics; Feedback; Glosso-Sterandryl; Goals; Guidelines; Home environment; Industry; Information Systems; Intention; International; Internet; Marketing; Medical; Medical Research; Medicine; Methods; Modeling; Outsourcing; Paper; Patient Monitoring; Patient Self-Report; Patient-Centered Care; Patients; Performance; Pharmacologic Substance; Phase; Physiological; Policies; Procedures; Process; Productivity; Protocols documentation; Questionnaires; Reporting; Research; Research Contracts; Running; Secure; Security; Services; Signal Transduction; Software Tools; Solutions; Speed; Statistical Methods; Surveys; System; Tablets; Technology; Telephone; Testing; Time; Travel; Wireless Technology; base; commercialization; compliance behavior; cost; cost effective; cost effectiveness; data management; design; drug development; electronic data; epidemiology study; experience; flexibility; health care delivery; improved; innovation; medication compliance; meetings; next generation; novel therapeutics; patient oriented; pressure; prevention service; prototype; psychologic; psychosocial; research and development; sensor; statistics; success; translational medicine; wireless network

DESCRIPTION (provided by applicant): The success of drug development and clinical research is heavily dependent on the quality of data, patience compliance, and statistical analysis. Traditional data collection via paper-pencil is labor- intensive and inconvenient, often leading to missing, noisy or invalid entries. There is always a challenge to monitor patients' medication compliance. When conducting analyses, traditional statistical methods lack of flexibility to make faster decisions. Seeing the ubiquitous application of wireless technologies and the quick emergence of Cloud Computing and Bayesian adaptive statistics in the pharmaceutical industry, we propose to develop a system called 'portable-devices based Data Solutions over the Cloud' (pDSC) for real-time data collection, scalable data storage, remote patient monitoring, and Bayesian adaptive clinical trial design. pDSC enables faster, cheaper, and effective clinical studies. Phase I of this project was highly successful. A prototype system was developed and tested by potential users. The business concept was highly acceptable for personalized data collection and analysis using the web-phone architecture. The feasibility of combing body area sensor networks with 3G wireless networks for collecting behavioral, psychosocial, geo-spatial and physiological data was fully verified. The protocols between iPhone and the web applications were developed and the method of high-performance Bayesian computation in the cloud was investigated. This Phase II proposal aims to fully develop the pDSC system to use smart phones and other portable devices for real-time data collection and patient monitoring. pDSC will be developed over the Windows Azure cloud platform with secure and scalable data storage mechanisms and interfaces to access other software tools for Bayesian adaptive design and interim analysis. The technical development will enable us to form a contracted research organization (CRO). It will offer cost-effective data services, fully complying with FDA guidelines, to help academic and pharmaceutical industry clients develop medicines to meet the goal of personalized treatment and patient-centered care.

描述（由申请人提供）：药物开发和临床研究的成功在很大程度上取决于数据质量、耐心依从性和统计分析。通过纸笔进行的传统数据收集既费力又不方便，常常导致条目丢失、有噪音或无效。监测患者的用药依从性始终是一个挑战。在进行分析时，传统的统计方法缺乏灵活性，无法更快地做出决策。看到无线技术的普遍应用以及云计算和贝叶斯自适应统计在制药行业的快速出现，我们建议开发一种名为“基于便携式设备的云数据解决方案”（pDSC）的系统，用于实时数据收集、可扩展的数据存储、远程患者监测和贝叶斯自适应临床试验设计。 pDSC 能够实现更快、更便宜且有效的临床研究。 该项目第一阶段非常成功。潜在用户开发并测试了原型系统。使用网络电话架构进行个性化数据收集和分析的业务概念非常容易被接受。将身体区域传感器网络与3G无线网络相结合来收集行为、心理社会、地理空间和生理数据的可行性得到了充分验证。开发了iPhone和Web应用程序之间的协议，并研究了云中高性能贝叶斯计算的方法。 该第二阶段提案旨在全面开发 pDSC 系统，以使用智能手机和其他便携式设备进行实时数据收集和患者监测。 pDSC 将在 Windows Azure 云平台上开发，具有安全且可扩展的数据存储机制和接口，用于访问其他软件工具以进行贝叶斯自适应设计和中期分析。技术开发将使我们能够组建一个合同研究组织（CRO）。它将提供经济高效的数据服务，完全符合 FDA 指南，帮助学术和制药行业客户开发药物，以实现个性化治疗和以患者为中心的护理的目标。