SBIR Phase I: Advanced Direct-To-Patient Data Aggregation Platform For Clinical Trial Recruitment.

SBIR 第一阶段：用于临床试验招募的先进的直接面向患者的数据聚合平台。

• 批准号: 1843917
• 负责人: Gerald Lee
• 金额: $ 22.5万
• 依托单位: SANGUINE BIOSCIENCES, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2020-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1843917&HistoricalAwards=false
• 关键词: SBIR; Phase; Advanced; Direct; Patient

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable researchers to recruit participants for clinical trials more quickly and reliably. A major problem in medical research is that a majority of clinical trials are delayed or canceled because of insufficient recruitment of eligible participants. By developing an independent (third-party) data aggregation platform for detailed electronic patient data through this project, researchers will be able to efficiently reach a large pool of potential participants for trials, and increase the likelihood of trial success. The resulting platform will create a much more efficient recruitment system, as the data is shared among the broader research community rather than managed by any individual research organization. With subscriptions and fees per enrolled patient, the platform will be able sustain itself while at the same time lowering recruitment costs for researchers. More broadly, the greater ability to design and execute successful clinical trials will be a huge benefit to the medical community and accelerate the pace of research and new product development. This Small Business Innovation Research (SBIR) Phase I project seeks to improve the speed, accuracy, and reliability of clinical trial design and recruitment. Research organizations like pharmaceutical companies and hospitals typically maintain isolated databases with limited, static patient data. This project focuses on building a third-party data platform that elegantly stores and organizes electronic patient data. The design of the platform enables ontological queries, allowing researchers to consult data when designing trials and quickly ?testing? specific inclusion/exclusion criteria to determine feasibility. When proceeding to execute the trial, the platform will rank individuals by likelihood to enroll, and facilitate contact with potential patients that have previously provide consent to be contacted. Initial objectives of the project include the development of a methodology to abstract patient data from medical records, and programming of the database structure. Later the work will focus on quality assurance software, and algorithms to translate free-text trial requirements into filters compatible with said database. The expected outcome is a platform storing accurate data of 200 patients, with filtering and ranking algorithms that match patients to trials with nearly the same accuracy of an experienced recruitment team.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.

这个小型企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是使研究人员能够更快，更可靠地招募临床试验的参与者。医学研究中的一个主要问题是，大多数临床试验因招募合格参与者不足而被推迟或取消。通过该项目为详细的电子患者数据开发一个独立的（第三方）数据聚合平台，研究人员将能够有效地接触到大量潜在的试验参与者，并增加试验成功的可能性。由此产生的平台将创建一个更有效的招聘系统，因为数据在更广泛的研究社区之间共享，而不是由任何单个研究组织管理。通过订阅和每位入组患者的费用，该平台将能够维持自身，同时降低研究人员的招募成本。更广泛地说，设计和执行成功的临床试验的能力更强，将给医学界带来巨大的好处，并加快研究和新产品开发的步伐。小型企业创新研究（SBIR）第一阶段项目旨在提高临床试验设计和招募的速度，准确性和可靠性。制药公司和医院等研究机构通常维护具有有限静态患者数据的隔离数据库。该项目的重点是建立一个第三方数据平台，优雅地存储和组织电子患者数据。该平台的设计使本体查询，使研究人员能够在设计试验时查阅数据，并迅速？测试？确定可行性的具体入选/排除标准。在继续执行试验时，平台将根据入组的可能性对个人进行排名，并促进与先前同意联系的潜在患者的联系。该项目的初步目标包括开发一种从病历中提取患者数据的方法，以及数据库结构的编程。之后的工作将集中在质量保证软件，以及将自由文本试验要求转换为与所述数据库兼容的过滤器的算法。预期成果是一个平台，存储200名患者的准确数据，过滤和排名算法，匹配患者的试验与一个经验丰富的招聘团队几乎相同的准确性。这个奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。