Back Pain Consortium (BACPAC) Research Program Data Integration, Algorithm Development and Operations Management Center

背痛联盟​​ (BACPAC) 研究计划数据集成、算法开发和运营管理中心

• 批准号: 10396871
• 负责人: Kevin J Anstrom
• 金额: $ 400万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-26 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10396871
• 关键词: Back; Pain; Consortium; BACPAC; Research

ABSTRACT The goal of this U24 application is to establish the Data Integration, Algorithm Development and Operations Management Center (DAC) for NIAMS' Back Pain Consortium (BACPAC) Research Program to ensure that the research objectives are met. The objectives of BACPAC include (i) discovery of lower back pain mechanisms through expert application of clinical and translational medicine methodologies; (ii) identification of new interventions targeted to individual patients through knowledge of established and newly discovered mechanisms; and (iii) evaluation of promising interventions to determine those that warrant further study, potentially leading to regulatory approval. A successful BACPAC research program will be based on cutting edge technologies and reflect the patient-centric focus that is critical to any investigation in this chronic and burdensome disease. Central to this success will be an innovative, forward-looking, and productive DAC that brings cohesion to research performed by the participating Mechanistic Research Centers, Technology Research Sites, and Phase 2 Clinical Trials Centers. DAC Investigators will share their vision and provide scientific leadership and organizational support to the BACPAC Consortium. Our research plan consists of designing and conducting clinical trials with precision interventions in stratified patient populations. Precision medicine interventions that focus on identifying the best treatments for individual patients, instead of the best treatments for the most patients, could improve overall outcomes among this heterogenous patient population. Key elements of the DAC that will enhance collaboration and research progress include experienced leadership, innovative design and analysis methodologies (e.g., sequential adaptive designs, machine learning, neural networks, Q-learning), comprehensive research operations support, a state-of-the-art data management and integration system, and superior administrative support. Our communications infrastructure will provide both public and private websites and a social media presence to effectively disseminate appropriate information to BACPAC investigators, participants, and the public. We will develop a secure, user- friendly advanced data management and integration system that includes web-based access for surveys, data entry, research management (including comprehensive reporting, biosample tracking and performance-based reimbursement tools), integration with external applications, and quality control. Our research operations and administration teams will provide a solid foundation to the BACPAC Research Program by facilitating meetings, collaborative document preparation, tracking of regulatory compliance, and support for abstract and publication preparation across the BACPAC Consortium. Together, this integrated structure will set the stage for technology assessments, solicitation of patient input and utilities, and the evaluation of high-impact interventions through the innovative design and sound execution of clinical trials, leading to effective personalized treatment approaches for patients with chronic lower back pain.

抽象的 该U24应用程序的目的是建立数据集成，算法开发和操作 NIAMS背痛财团（BACPAC）研究计划的管理中心（DAC），以确保 实现了研究目标。 BACPAC的目标包括（i）发现下背部疼痛 通过临床和转化医学方法的专家应用机制； （ii）识别 通过了解已建立和新发现的针对个别患者的新干预措施 机制； （iii）评估有前途的干预措施，以确定那些需要进一步研究的干预措施， 有可能导致监管批准。成功的BACPAC研究计划将基于切割 边缘技术并反映以患者为中心的重点，这对于此慢性和 繁重的疾病。这一成功的核心将是创新，前瞻性和富有成效的DAC 为参与机械研究中心进行的研究带来了凝聚力 研究地点和2阶段临床试验中心。 DAC调查人员将分享他们的愿景并提供 科学领导力和对BACPAC财团的组织支持。我们的研究计划包括 在分层的患者人群中设计和进行精确干预措施的临床试验。精确 药物干预措施着重于确定个别患者的最佳治疗方法，而不是最好的治疗方法 大多数患者的治疗方法可以改善该异质患者人群的总体预后。 DAC的关键要素将增强协作和研究进度包括经验丰富 领导力，创新设计和分析方法（例如，顺序自适应设计，机器 学习，神经网络，Q学习），全面的研究操作支持，最先进的数据 管理和集成系统以及卓越的行政支持。我们的通信基础架构 将提供公共和私人网站以及社交媒体的存在，以有效传播 向BACPAC调查人员，参与者和公众提供适当的信息。我们将开发一个安全的，用户 - 友好的高级数据管理和集成系统，包括基于Web的调查访问，数据 进入，研究管理（包括全面报告，生物样品跟踪和基于绩效 报销工具），与外部应用程序集成以及质量控制。我们的研究行动和 行政团队将通过促进会议，为BACPAC研究计划提供坚实的基础， 协作文件准备，跟踪监管合规性以及对摘要和出版物的支持 整个BACPAC财团的准备。这种集成结构将共同为 技术评估，对患者投入和公用事业的招标以及高影响力的评估 通过创新设计和临床试验的良好执行的干预措施，导致有效 慢性下背部疼痛患者的个性化治疗方法。