权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

SBIR Phase I: SAAS-based Mass Spectrometry Data Processing for Antibody Therapeutics for COVID-19 and Other Diseases

SBIR 第一阶段：基于 SAAS 的质谱数据处理，用于 COVID-19 和其他疾病的抗体治疗

基本信息

批准号：
2029972
负责人：
Robert Smith
金额：
$ 25.6万
依托单位：
Prime Labs Inc
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2022-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029972&HistoricalAwards=false
关键词：
SBIR Phase SAAS based Mass

项目摘要

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the increased likelihood of effective and affordable new antibody therapy development for COVID-19 and other diseases. Current software is time-intensive to advance antibody therapy development. The proposed software will provide rapid, accurate information about the function and safety of putative therapies, enabling faster deployment. This SBIR Phase I project will develop novel algorithms and interfaces for enhancing antibody analysis via mass spectrometry. The research will expand capacity and accuracy for detecting, characterizing, and quantifying antibody glycans, disulfide bonds, and impurities by capturing information from experimental metadata, sample preparation, instrument parameters, and instrument output and creating models for prediction of possible structures supported by the data. The proposed project aims to increase the quantity of antibody subunits that can be accurately detected and quantified. This process will take tenfold less time than current methods through the use of novel algorithms, customizable automatable processes, and integrated reporting tools.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.

这一小型企业创新研究（SBIR）第一阶段项目的更广泛影响/商业潜力将是为COVID-19和其他疾病开发有效和负担得起的新抗体疗法的可能性增加。目前的软件是时间密集型的，以推进抗体治疗的发展。拟议的软件将提供有关假定疗法的功能和安全性的快速，准确的信息，从而实现更快的部署。该SBIR第一阶段项目将开发新的算法和接口，用于通过质谱法增强抗体分析。该研究将通过从实验元数据、样品制备、仪器参数和仪器输出中捕获信息，并创建模型来预测数据支持的可能结构，从而扩大检测、表征和定量抗体聚糖、二硫键和杂质的能力和准确性。拟议项目旨在增加可以准确检测和定量的抗体亚单位的数量。通过使用新颖的算法、可定制的自动化流程和集成的报告工具，该过程所需时间将比现有方法缩短10倍。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。