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

背痛联盟​​ (BACPAC) 研究项目数据集成、算法开发和运营管理中心

• 批准号: 9898044
• 负责人: Kevin J Anstrom
• 金额: $ 5178.13万
• 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 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9898044
• 关键词: Adoption; Adult; Affect; Algorithms; Back Pain; Bioinformatics; Biological; Biological Markers; Biometry; Chronic; Chronic low back pain; Clinical; Clinical Medicine; Clinical Research; Clinical Trials; Clinical Trials Design; Collaborations; Communication; Conduct Clinical Trials; Consensus; Data; Data Analyses; Data Analytics; Data Collection; Data Security; Data Set; Data Storage and Retrieval; Database Management Systems; Development; Diagnostic; Disease; Effectiveness; Elements; Ensure; Evaluation; Foundations; Funding; Genomics; Gills; Goals; Health Care Costs; Image; Infrastructure; Intervention; Investigation; Knowledge; Lead; Leadership; Learning; Low Back Pain; Machine Learning; Manuscripts; Methodology; Methods; Modeling; Monitor; National Institute of Arthritis and Musculoskeletal and Skin Diseases; North Carolina; Online Systems; Operations Research; Opiate Addiction; Outcome; Overdose; Pain; Participant; Patient Preferences; Patients; Performance; Phase II Clinical Trials; Phenotype; Prediction of Response to Therapy; Preparation; Privatization; Procedures; Proteomics; Protocols documentation; Public Health; Publications; Quality Control; Reporting; Reproducibility; Research; Research Personnel; Research Support; Risk; Schools; Secure; Site; Solid; Statistical Data Interpretation; Strategic Planning; Structure; Surveys; Systems Integration; Technology; Technology Assessment; Therapeutic Intervention; TimeLine; United States National Institutes of Health; Universities; Vision; Writing; base; clinical application; cohesion; collaborative trial; computerized data processing; cost effective; data integration; data management; data portal; design; disability burden; experience; improved; individual patient; innovation; instrument; interoperability; meetings; neural network; novel; operation; organizational structure; patient oriented; patient population; patient stratification; personalized intervention; personalized medicine; phenotypic data; precision medicine; prediction algorithm; product development; programs; social media; sound; success; tool; translational medicine; trial design; user-friendly; web site

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.

摘要 此U24应用程序的目标是建立数据集成、算法开发和操作 NIAMS背痛联盟（BACPAC）研究计划的管理中心（DAC），以确保 达到了研究目标。BACPAC的目标包括（i）发现下背痛 通过专家应用临床和转化医学方法的机制;（二）确定 新的干预措施针对个别患者通过知识的建立和新发现的 （三）评价有希望的干预措施，以确定值得进一步研究的干预措施， 可能导致监管部门的批准。一个成功的BACPAC研究计划将基于切割 边缘技术，并反映了以患者为中心的重点，这对这一慢性疾病的任何研究都至关重要， 沉重的疾病这一成功的核心是一个创新、前瞻性和富有成效的发援会， 为参与的机械研究中心、技术研究中心、 研究中心和II期临床试验中心。DAC研究人员将分享他们的愿景，并提供 科学领导和组织支持BACPAC联盟。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的临床试验。精度 药物干预，重点是为个别患者确定最佳治疗方法，而不是最好的 对于大多数患者的治疗，可以改善这种异质性患者人群的总体结局。 发展援助委员会的关键要素，将加强合作和研究进展，包括经验丰富的 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），全面的研究运营支持，最先进的数据 管理和集成系统，以及上级行政支持。我们的通信基础设施 将提供公共和私人网站以及社交媒体，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- 友好的先进数据管理和集成系统，包括基于网络的调查访问，数据 研究管理（包括综合报告、生物样本跟踪和基于绩效的 报销工具）、与外部应用程序的集成以及质量控制。我们的研究业务和 管理团队将通过促进会议， 协作文档准备、跟踪法规遵从性以及支持摘要和出版 整个BACPAC联盟的准备工作。总之，这一综合结构将为 技术评估、征求患者意见和效用，以及评估高影响力 通过创新的设计和良好的临床试验执行干预，导致有效的 为慢性腰痛患者提供个性化治疗方法。