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

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的质量、耐心遵守和统计分析。传统的纸笔数据采集方式劳动强度大、使用不便，容易造成遗漏、噪声或无效录入。监测患者的服药依从性总是一个挑战。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。鉴于无线技术在制药行业的广泛应用，以及云计算和贝叶斯自适应统计在制药行业的迅速崛起，我们提出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、远程患者监控和贝叶斯自适应临床试验设计。PDSC使临床研究更快、更便宜、更有效。该项目的第一阶段非常成功。开发了一个原型系统，并进行了潜在用户的测试。业务概念对于使用网络电话架构的个性化数据收集和分析是高度可接受的。充分验证了将体域传感器网络与3G无线网络相结合用于收集行为、心理社会、地理空间和生理数据的可行性。开发了iPhone与Web应用程序之间的协议，研究了高性能的云端贝叶斯计算方法。这项第二阶段的建议旨在全面发展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护。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，以访问用于贝叶斯自适应设计和中期分析的其他软件工具。技术的发展将使我们能够形成一个签约研究组织(CRO)。它将提供符合成本效益的数据服务，完全符合FDA的指导方针，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目标。 公共卫生相关性：数据和分析的质量对于任何临床研究的成功都至关重要。提出的基于无线和互联网技术以及贝叶斯自适应方法的解决方案将极大地扩大医药产品开发中数据解决方案的容量和成本效益。它具有巨大的潜力，可以满足个性化医疗、以患者为中心的服务和以预防为导向的护理的下一代临床研究和医疗保健服务的需求。

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. PUBLIC HEALTH RELEVANCE: Quality of data and analysis is crucial for the success of any clinical research. The proposed solution based on wireless and Internet technologies and Bayesian adaptive methods will greatly enlarge the capacity and cost-effectiveness of data solutions in developing pharmaceutical products. It has great potential to meet the needs of next generation clinical research and healthcare delivery featured by personalized medicine, patient-centered service, and prevention-oriented care.