SBIR Phase I: Technical R&D for cloud-based high-information mass spectrometry data extraction commercialization

这个小企业创新研究（SBIR）项目的更广泛的影响/商业潜力是建立更快，更便宜，更准确的方法来确定生物样品的内容，从而产生新的医学诊断，新药和其他新产品，这些新产品超出了目前采用质谱法的科学方法的范围。该项目将开发技术，使更好的质谱软件，并将使基于质谱的样品分析更容易获得更广泛的学术和工业科学家，扰乱1亿美元的市场。需要先进的软件将原始实验数据转化为创造新药、发现疾病和增加粮食产量所需的分子和数量清单。该项目的成功完成将使下一代质谱软件的开发成为可能，提供基于先进的高信息算法的用户友好的快速云软件。SBIR第一阶段项目旨在开发用于质谱数据处理的新型高信息软件技术。第一阶段的拟议工作将为第二阶段的原型开发和测试提供概念验证。该研究将解决三个关键的技术障碍，这是原型开发的先决条件：1）足以处理来自典型研究中的数百个文件的显著更多的信息的质谱数据存储和检索架构，2）质谱信息提取算法的云优化版本，以及3）基于云的模型-视图控制器框架，其克服了质谱数据处理的网络特定挑战。其目标是在不增加成本的情况下，在相同的时间内进行更多的实验，从同一实验中识别出比现有方法更多的分子，并检测出含量较低和现有方法无法检测到的分子。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。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to establish faster, less expensive, more accurate ways of determining the contents of biological samples leading to novel medical diagnostics, new drugs, and other new products beyond the reach of the current scientific methods that employ mass spectrometry. The project will develop technology that enables better software for mass spectrometry, and will make mass spectrometry-based sample analysis more accessible to a broader segment of academic and industrial scientists, disrupting a $100M market. Advanced software is required to transform raw experimental data into the lists of molecules and quantities needed to create new drugs, discover diseases and increase food production. The successful completion of the aims of this proposal will enable the development of software built for the next generation of mass spectrometry, providing user-friendly, fast cloud software built on advanced, high-information algorithms.This SBIR Phase I project proposes to develop novel, high-information software technology for mass spectrometry data processing. The proposed work in Phase I will provide proof-of-concept for prototype development and testing in Phase II. The research will address three critical technical hurdles that are prerequisites to prototype development: 1) A mass spectrometry data storage and retrieval architecture sufficient to handle significantly more information from the hundreds of files in a typical study, 2) cloud-optimized versions of mass spectrometry information extraction algorithms, and 3) a cloud-based model-view controller framework that overcomes web-specific challenges for mass spectrometry data processing. The goal is to allow more experiments in the same amount of time without increasing costs, identifying more molecules than existing methods from the same experiment, and detecting molecules that are less abundant and go undetected by current methods.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.