Core 1: Information Technology and Systems Integration

核心一：信息技术与系统集成

• 批准号: 10628614
• 负责人: Adam Asare
• 金额: $ 49.99万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-08 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10628614
• 关键词: Address; Adverse event; Architecture; Bioinformatics; Biological Markers; Case Report Form; Case Study; Clinical; Code; Collection; Common Terminology Criteria for Adverse Events; Data; Data Analyses; Data Sources; Databases; Development; Documentation; Electronic Health Record; Ensure; Feedback; Goals; Grant; Hybrids; Image; Immune; Individual; Information Systems; Information Technology; Infrastructure; Internet; Laboratories; Machine Learning; Magnetic Resonance Imaging; Maintenance; Nature; Outcome; Pathology; Physicians; Quality of life; Randomized; Reporting; Reproducibility of Results; Research; Research Personnel; Resources; Science; Secure; Sequential Treatment; Services; Source; Surveys; System; Systems Biology; Systems Integration; Technology; The Cancer Genome Atlas; Time; Toxic effect; Validation; Visualization; Work; bioinformatics infrastructure; clinical research site; cohort; data infrastructure; data sharing; design; electronic data; electronic data capture system; electronic patient reported outcomes; exome; experience; imaging biomarker; improved; innovation; malignant breast neoplasm; member; migration; molecular marker; personalized care; point of care; portability; programs; repository; response biomarker; shared repository; statistics; symposium; tool; transcriptome sequencing; treatment response; web services

The adaptive, platform nature of the I-SPY trials places a number of additional requirements on the collection of clinical and laboratory data and in the management and portability of the resulting data. In particular, the adaptive randomization engine relies upon near real-time access to MRI and pathology assessments. However, as I-SPY and the field have grown and evolved, so too have the requirements of the underlying data systems and architecture, particularly for the advanced designs of I-SPY2.2. The Information Technology and Systems Integration core seeks not only to provide high quality services to the projects, but also to engage in the development and validation of innovative tools that further the program project’s ability to meet and or exceed their research goals. In the past grant period, the core has also exceeded the aims laid out in the original proposal. We built out and deployed a robust electronic data capture (EDC) platform and successfully migrated 10 years of trial data into the new system. In a pilot implementation, we demonstrated the OneSource system that seamlessly permits data to be pulled directly from electronic health records into study case report forms (CRF), can improve data fidelity and timeliness of CRF completion, giving program project teams quicker access to higher quality data. We architected a biomarker repository platform on Amazon Web Services (AWS) that is fully integrated with Google Big Query and leverages the Institute for Systems Biology (ISB) biomarker management and visualization platform [ProBE]. Finally, we implemented systems for the collection and management of electronic Patient Reported Outcomes that have vastly improved completion rates for quality of life and adverse event reporting by program project investigators. The IT and Systems Integration Core will continue to provide functionality to the I-SPY2.2 trial in a number of ways. We will continue implementing OneSource across the majority of the 32+ clinical sites and integrate additional data types including pathology/immune multiplex, imaging, whole exome, ctDNA, RNA seq into our cloud repository. Over the course of the proposed work, we will develop a resource for investigators so they can interactively view and query all the various types data in an integrated fashion, and connect to external data sources such as TCGA, to allow comparisons between I-SPY and other breast cancer cohorts. This repository will be enhanced by integrating machine learning, contextual-level visualizations, and other external database tools.

I-SPY 试验的适应性、平台性质对临床数据的收集提出了许多额外的要求。 和实验室数据以及结果数据的管理和可移植性，特别是自适应随机化。 然而，随着 I-SPY 和该领域的发展，引擎依赖于近乎实时的 MRI 和病理学评估。 并且不断发展，底层数据系统和架构的要求也在不断变化，特别是对于先进的 I-SPY2.2 的设计不仅旨在提供高质量的信息技术和系统集成。 为项目提供服务，同时也参与创新工具的开发和验证，以进一步推进该计划 项目达到或超过其研究目标的能力在过去的资助期内，核心也超出了目标。 我们构建并部署了一个强大的电子数据采集（EDC）平台，并在最初的提案中提出了这一点。 成功地将 10 年的试验数据迁移到新系统中。 OneSource 系统可无缝地将数据直接从电子健康记录提取到研究病例报告中 表格 (CRF)，可以提高 CRF 完成的数据保真度和及时性，使计划项目团队能够更快地访问 我们在 Amazon Web Services (AWS) 上构建了一个完全完整的生物标记存储库平台。 与 Google Big Query 集成，并利用系统生物学研究所 (ISB) 生物标记管理和 最后，我们实现了电子患者收集和管理系统。 报告的成果大大提高了项目的生活质量和不良事件报告的完成率 项目调查员。 IT 和系统集成核心将继续以多种方式为 I-SPY2.2 试用版提供功能。 将继续在 32 个以上临床中心的大多数中实施 OneSource 并集成其他数据类型 包括病理/免疫多重、成像、全外显子组、ctDNA、RNA seq 到我们的云存储库中。 在拟议的工作过程中，我们将为调查人员开发资源，以便他们可以交互式地查看和查询所有 以集成的方式收集各种类型的数据，并连接到TCGA等外部数据源，以便进行比较 I-SPY 和其他乳腺癌队列之间的关系将通过整合机器学习得到增强， 上下文级可视化和其他外部数据库工具。