SBIR Phase I: An Online Peer-to-Peer Resource for Oncologists to Improve Clinical Trial Knowledge and Enrollment

SBIR 第一阶段：为肿瘤学家提供在线点对点资源，以提高临床试验知识和入组率

• 批准号: 1843270
• 负责人: Nadine Housri
• 金额: $ 22.5万
• 依托单位: MEDNET, 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 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1843270&HistoricalAwards=false
• 关键词: SBIR; Phase; Online; Peer; Resource

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to put forth a solution to the critical problem of clinical trial enrollment, by improving awareness of clinical trials with physicians through technology that matches physician questions to relevant clinical trials via an online interactive social decision support platform. Patient enrollment is a significant weak link in the development pipeline and a significant pain point for organizations that sponsor clinical trials. More than two-thirds of trial sites fail to meet enrollment goals for a given trial, and up to 45% of study delays are caused by enrollment difficulties. This can result in lost revenues up to $1 million/day. Clinical trials are a critical link between scientific discovery and changes in clinical practice that advance prevention, treatments, and cures for diseases and disability. Increasing awareness of trials among physicians is key in increasing clinical trial enrollment, which in turn is essential in advancing health care practice as well as patient health and quality of life. While the area of cancer is an initial target for improved enrollment, ultimately the proposed solution can be applied to other medical specialties and be scaled globally using the same platform. This Small Business Innovation Research (SBIR) Phase I project seeks to drive clinical trial accrual by changing how physicians learn about clinical trials. The major innovation is combining a credible online social platform with powerful natural language processing technology and machine learning techniques to deliver customized clinical trial information to physicians in their decision-making process. For this Phase I project, the key objectives are: 1) To build out a prototype to match clinical trial information to relevant physician questions. Natural language processing (NLP) technology will be created to match clinical questions to related clinical trials so that physicians learn about clinical trials at the time they are seeking information on how to best treat their patients. 2) To conduct a pilot assessment of clinical trial knowledge pre- and post-use. A small subset of users of the social network platform will engage in a comparative assessment, pre- and post-exposure to the clinical trial component, to determine the technology?s impact on clinical trial knowledge. Successful completion of Phase I will result in a user-friendly platform that matches clinical questions to oncologists and relevant, open clinical trials, and will establish the technical and commercial feasibility of the proposed concept.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/商业潜力是提出一个解决方案，临床试验招募的关键问题，通过提高临床试验的认识与医生通过技术，匹配医生的问题，通过在线互动的社会决策支持平台相关的临床试验。患者入组是开发管道中的一个重要薄弱环节，也是赞助临床试验的组织的一个重要痛点。超过三分之二的试验中心未能达到特定试验的招募目标，高达45%的研究延迟是由招募困难造成的。这可能导致高达100万美元/天的收入损失。临床试验是科学发现与临床实践变化之间的关键环节，可促进疾病和残疾的预防、治疗和治愈。提高医生对试验的认识是增加临床试验入组的关键，而这反过来又是推进医疗保健实践以及患者健康和生活质量的关键。虽然癌症领域是提高入学率的初始目标，但最终提出的解决方案可以应用于其他医学专业，并使用同一平台在全球范围内扩展。这个小型企业创新研究（SBIR）第一阶段项目旨在通过改变医生了解临床试验的方式来推动临床试验的增长。主要创新是将可靠的在线社交平台与强大的自然语言处理技术和机器学习技术相结合，为医生的决策过程提供定制的临床试验信息。对于这个I期项目，主要目标是：1）建立一个原型，将临床试验信息与相关的医生问题相匹配。将创建自然语言处理（NLP）技术，以将临床问题与相关的临床试验相匹配，以便医生在寻求如何最好地治疗患者的信息时了解临床试验。2)对使用前和使用后的临床试验知识进行试点评估。社交网络平台的一小部分用户将在接触临床试验组件之前和之后进行比较评估，以确定技术？对临床试验知识的影响。 第一阶段的成功完成将产生一个用户友好的平台，将临床问题与肿瘤学家和相关的开放式临床试验相匹配，并将建立拟议概念的技术和商业可行性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。