Precision Mass Spec Imaging Based Structure-Function Signatures of Diabetic Glomerulopathy

基于精密质谱成像的糖尿病肾小球病的结构功能特征

• 批准号: 10596057
• 负责人: Leila Hejazi
• 金额: $ 0.65万
• 依托单位: SYGNAMAP, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-08 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10596057
• 关键词: Address; Adopted; Biological Markers; Biopsy; Biotechnology; Coupled; Data; Diabetic Nephropathy; Dialysis procedure; Disease; End stage renal failure; Image; Kidney; Kidney Diseases; Life; Link; Medicare; Pathology; Pathway interactions; Patients; Phase; Pre-Clinical Model; Precision therapeutics; Process; Renal glomerular disease; Reproducibility; Small Business Innovation Research Grant; Structure; System; Technology; Therapeutic; Tissues; United States; base; computational platform; cost; diabetic; drug development; insight; kidney biopsy; novel therapeutics; programs

Project Summary/Abstract There are currently >450,000 patients on dialysis and ~120,000 patients will have to begin dialysis each year in the United States. Along with a marked reduction in quality of patient life, the cost to the US Medicare system is in excess of $114B per year. Therefore, there is an urgent need for developing new platforms that will enhance the drug development process for new therapies to reduce the rate of progression to end-stage kidney disease. Non-invasive biomarkers may be useful but do not directly identify the pathways linked to pathology in the kidney. An approach that integrates tissue structure with functional readouts in a kidney biopsy would be a major advance. We are developing a computational platform that leverages mass spec imaging data coupled with computational pathology for kidney tissue as a technology that will address this unmet need. With our computational platform we can identify signatures linked to normal and abnormal pathology on the same tissue section. This is a powerful approach to understand kidney pathology and will be of great value for drug development for kidney disease. Parameters related to reproducibility across pre-clinical models of diabetic kidney disease interpretation will be optimized during Phase I. Upon completion of the SBIR Phase I project we will have rigorous data to determine consistency of diseased glomerular signatures in diabetic nephropathy. This proof of concept data will make it attractive to pharma and biotech to adopt this platform for application for their therapeutic programs for diabetic kidney disease.

项目摘要/摘要 目前有45万名患者正在接受透析，约12万名患者将不得不开始透析 每年在美国。随着患者生活质量的显著下降， 美国的医疗保险系统每年超过1140亿美元。因此，迫切需要 开发新平台，以加强新疗法的药物开发过程 降低进展为终末期肾病的比率。非侵入性生物标志物可能是 有用，但不能直接确定与肾脏病理有关的途径。一种方法 在肾脏活检中将组织结构与功能读数相结合将是一大进步。 我们正在开发一个计算平台，它利用质量谱成像数据与 肾组织的计算病理学作为一项技术将解决这一未得到满足的需求。使用 我们的计算平台我们可以识别与正常和异常病理有关的特征 在相同的组织切片上。这是了解肾脏病理和意志的有力途径。 对肾脏疾病的药物开发具有重要价值。与重复性相关的参数 在糖尿病肾病的临床前模型中，解释将在阶段进行优化 I.在SBIR第一阶段项目完成后，我们将有严格的数据来确定 糖尿病肾病中病变肾小球征象的一致性。此概念验证数据 将吸引制药公司和生物技术公司采用此平台应用于其 糖尿病肾病的治疗方案。