SBIR Phase II: Robust Medical Data Aggregation to Enable Advanced Approaches to Precision Medicine

SBIR 第二阶段：强大的医疗数据聚合，实现精准医疗的先进方法

• 批准号: 1831085
• 负责人: Ganapati Srinivasa
• 金额: $ 74.74万
• 依托单位: Omics Data Automation, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831085&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Robust; Medical

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to increase the impact of precision medicine by simultaneously addressing large-scale medical data aggregation and analytics. Patient medical information comes in many forms: DNA sequences, medical images, clinical observations, etc. Integration of these various data sources across large patient populations can reveal novel insights into clinical disease and inform new treatment options. There is a growing need for scalable data integration to support the delivery of precision medicine. This Small Business Innovation Research (SBIR) Phase II project will build on the data Framework that was created during Phase I work. This Framework supports the aggregation of different types of medical data into a single data core ?pool?, and computation on the pooled data in a scalable cloud environment. The Framework includes a custom database for genomic sequencing data. During Phase II of this project, this custom (sparse matrix) approach to data storage will be adapted to handle microscopy images of cancer and other diseased tissues. The Framework, with its integrated genomic and image databases, will be marketed to healthcare systems, biotechnology companies, and pharmaceutical companies interested in applying advanced analytics on large, complex datasets.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

小型企业创新研究(SBIR)第二阶段项目的更广泛影响/商业潜力是通过同时处理大规模医疗数据聚合和分析来增加精准医疗的影响。患者的医疗信息有多种形式：DNA序列、医学图像、临床观察等。在大量患者群体中整合这些不同的数据源可以揭示对临床疾病的新见解，并为新的治疗选择提供信息。越来越需要可扩展的数据集成来支持精准医疗的交付。该小型企业创新研究(SBIR)第二阶段项目将建立在第一阶段工作期间创建的数据框架之上。该框架支持将不同类型的医疗数据聚合到单个数据核心(池)中，并在可扩展的云环境中对池中的数据进行计算。该框架包括一个用于基因组测序数据的定制数据库。在这个项目的第二阶段，这种定制的(稀疏矩阵)数据存储方法将适用于处理癌症和其他疾病组织的显微图像。该框架及其集成的基因组和图像数据库将向医疗保健系统、生物技术公司和对在大型、复杂的数据集上应用先进分析感兴趣的制药公司销售。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。