SBIR Phase II: A Cryo-EM Automation and Intelligence Platform for Drug Discovery

SBIR 第二阶段：用于药物发现的冷冻电镜自动化和智能平台

• 批准号: 2135832
• 负责人: Narasimha Kumar
• 金额: $ 100万
• 依托单位: Health Technology Innovations, Inc.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135832&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Cryo; EM

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve disease research and drug discovery. Cryogenic Electron Microscopy (cryo-EM) is one of the most impactful and vital tools of biological structure analysis today. The proposed project improves the current methods to achieve better accuracy and productivity, with faster user training.The proposed project improves imaging by cryo-EM. The images currently generated by cryo-EM are highly noisy and thus requires extensive processing to build recognizable structures (proteins and others). Single-particle cryo-EM is a method that produces images of individual particles and can potentially analyze biological structures at the single-molecule level. This project uses Artificial Intelligence/Machine Learning (AI/ML) techniques to mitigate the issues. AI/ML algorithms can automate the workflow, facilitating quality data and the development of 3D models.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）第二阶段项目的更广泛的影响/商业潜力是改善疾病研究和药物发现。低温电子显微镜（cryo-EM）是当今生物结构分析中最具影响力和最重要的工具之一。 该项目改进了当前的方法，以实现更好的准确性和生产力，更快的用户培训。目前由cryo-EM生成的图像噪声很大，因此需要大量的处理来构建可识别的结构（蛋白质和其他）。单粒子冷冻EM是一种产生单个粒子图像的方法，可以在单分子水平上分析生物结构。 该项目使用人工智能/机器学习（AI/ML）技术来缓解这些问题。 AI/ML算法可以自动化工作流程，促进高质量数据和3D模型的开发。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。