Validating a Scalable, Open Science Framework for Collecting Laboratory-Grade Data Remotely in Specialized Populations

验证可扩展的开放科学框架，用于在特殊人群中远程收集实验室级数据

• 批准号: 10289016
• 负责人: Bridgette Lynne Kelleher
• 金额: $ 23.05万
• 依托单位: PURDUE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10289016
• 关键词: Acute; Address; Assessment tool; Attention; Behavioral; Biological Assay; COVID-19 pandemic; Calibration; Caregivers; Child; Clinic; Clinical; Clinical Research; Clinical Sciences; Clinical Trials; Cognitive; Computer software; Data; Data Collection; Development; E-learning; Ensure; Equipment; Failure; Floor; Fragile X Syndrome; Funding; Heart Rate; Human Resources; Individual; Intellectual functioning disability; Laboratories; Measures; Methods; Modeling; Monitor; Multi-Institutional Clinical Trial; Natural History; Outcome; Outcome Measure; Output; Parents; Participant; Patient Monitoring; Patients; Pharmaceutical Preparations; Population; Positioning Attribute; Procedures; Process; Protocols documentation; Psychophysiology; Publishing; Research; Research Personnel; Resources; Science; Signal Transduction; Site; Standardization; Symptoms; Techniques; Testing; Time; Training; Translating; Travel; United States National Institutes of Health; base; clinical outcome measures; cohort; cost; cost effective; data analysis pipeline; data standards; efficacy validation; graphical user interface; high risk population; improved; innovation; network models; open data; patient response; peer; programs; remote delivery; self-directed learning; skills; sustained attention; telehealth; tool; treatment trial; user friendly software; user-friendly; virtual

PROJECT SUMMARY The limited repertoire of clinical outcome measures suitable for children with intellectual and developmental disabilities (IDD) is compromising the promise of clinical trials. Non-standardized laboratory techniques that capture “spectral” signals – such as psychophysiological assays – are increasingly recognized as promising methods for monitoring patient responses over time. However these tools require specialized equipment and personnel to administer and are not easily deployed via telehealth, biasing spectral studies toward patients who are able and willing to travel to clinics. Thus, there is a significant gap in available telehealth-based protocols for collecting laboratory-grade data remotely in IDD populations. The present study addresses this gap by developing a comprehensive training protocol for PANDABox (Parent Assisted Neurodevelopmental Assessment), an open-science, telehealth-based assessment protocol that PI Kelleher developed for remotely collecting high quality, integrated clinical, behavioral, and spectral assays from participants with IDD. Published findings indicate that PANDABox is highly feasible and acceptable to caregivers and generates high quality, integrated, “laboratory-grade” data at low cost. Already, PANDABox is being deployed in a variety of treatment and natural history studies across IDD populations and is being translated to Spanish to promote accessibility. The present study aims to enhance the scalability of PANDABox by accomplishing two specific aims. First, we will develop and validate an open-science training protocol and peer-to-peer reliability network to facilitate standardized, cross-laboratory implementation of the PANDABox protocol in IDD. This protocol will include both a virtual training hub for self-paced training, as well as a reliability network to facilitate cross-site calibration. Second, we will create user-friendly software program to support users to efficiently process the PANDABox attention assay, which has produced promising outcomes in clinical trials but requires computational expertise to analyze, limiting its scalability. Addressing these gaps would shift the status quo of clinical science in IDD by (1) providing a scalable, accessible protocol for collecting laboratory- grade data remotely in IDD populations and (2) producing standardized data outputs necessary for large scale, multi-site, collaborative science.

项目摘要 临床结果指标的有限曲目适用于智力儿童和 发育障碍（IDD）损害了临床试验的承诺。非标准化 捕获“光谱”信号（例如心理生理测定法）的实验室技术 - 越来越多地被认为是随着时间的流逝监测患者反应的承诺方法。 但是，这些工具需要专门的设备和人员来管理，而不是 通过远程医疗轻松部署，将光谱研究偏向于能够和愿意的患者 去诊所旅行。这是，可用的基于远程医疗的协议存在很大的差距 在IDD人群中远程收集实验室级数据。本研究解决了这个问题 通过为Pandabox制定综合培训方案（父母协助）来差距 神经发育评估），一种开放科学，基于远程医疗的评估方案， Pi Kelleher开发用于远程收集高质量，综合临床，行为和 IDD参与者的光谱测定。已发表的发现表明Pandabox是高度的 可行的和可接受的护理人员，并产生高质量的集成，“实验室级” 低成本的数据。潘达博克斯已经部署在各种治疗和自然中 跨IDD人群的历史研究，并正在翻译成西班牙语以促进 可访问性。本研究旨在通过完成pandabox的可伸缩性 两个具体的目标。首先，我们将制定并验证开放科学培训方案，并 点对点可靠性网络，以促进标准化的跨劳动实施 IDD中的Pandabox协议。该协议将包括一个虚拟培训中心 培训以及可靠性网络，以促进跨站点校准。第二，我们将创建 用户友好的软件程序，以支持用户有效处理Pandabox的注意力 测定，在临床试验中产生了有希望的结果，但需要计算 分析的专业知识，限制其可扩展性。解决这些差距会改变 IDD中的临床科学（1）提供了可扩展的，可访问的方案，用于收集实验室 - 在IDD人群中远程数据和（2）产生必要的标准数据输出 大规模，多站点，协作科学。