SBIR Phase I: Computational platform to infer putative causative pathways of pathology using spatial omics data

SBIR 第一阶段：使用空间组学数据推断病理学假定致病途径的计算平台

• 批准号: 2136649
• 负责人: Shoba Sharma
• 金额: $ 25.6万
• 依托单位: SYGNAMAP, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-15 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2136649&HistoricalAwards=false
• 关键词: SBIR; Phase; Computational; platform; infer

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to improve clinical outcomes and quality of life for kidney disease. This technology will help identify biomarkers and enable new personalized treatments to improve efficacy and reduce harmful side effects. The innovation will leverage new enhancements in visualizing molecules in biological samples and will improve scientific understanding of complex diseases. The proposed project will leverage the power of the emerging field of spatial omics to build a novel computational platform. Multi-omics technology at a spatial level is changing our understanding of complex conditions, such as cancer and metabolic diseases. These technologies are important to better understand heterogeneity of normal organ structure and changes during the development of complex chronic metabolic diseases and cancers. Mass spectrometry-based platforms have led multi-omic spatial applications, but quantifying the output of mass spectrometry imaging remains a challenge. The research objectives are to correlate and optimize localization of molecules with pathologic features and identify key biochemical pathways that drive disease development. The methods will include computational pathology, mass spectrometry imaging, and artificial intelligence/ machine learning approaches. The anticipated technical results will be development of technologies that convert semi-quantitative output to rigorous, quantitative results for identification of pathways driving disease development.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.

这项小型企业创新研究（SBIR）I期项目的更广泛影响将是改善肾脏疾病的临床结局和生活质量。 这项技术将有助于识别生物标志物，并实现新的个性化治疗，以提高疗效并减少有害的副作用。这项创新将利用生物样品中分子可视化的新增强功能，并将提高对复杂疾病的科学理解。拟议的项目将利用空间组学的新兴领域的力量，建立一个新的计算平台。空间层面的多组学技术正在改变我们对癌症和代谢性疾病等复杂疾病的理解。这些技术对于更好地了解复杂慢性代谢疾病和癌症发展过程中正常器官结构的异质性和变化非常重要。基于质谱的平台已经引领了多组学空间应用，但是量化质谱成像的输出仍然是一个挑战。研究目标是关联和优化分子与病理特征的定位，并确定驱动疾病发展的关键生化途径。这些方法将包括计算病理学，质谱成像和人工智能/机器学习方法。预期的技术成果将是开发将半定量输出转换为严格的定量结果的技术，以识别疾病发展的途径。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。