Robust Automated Platform for Immunophenotyping Diagnostics (RAPID)

强大的免疫表型诊断自动化平台 (RAPID)

• 批准号: 570709-2021
• 负责人: Jackson, HartlandHW
• 金额: $ 29.87万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=761494
• 关键词: Robust; Automated; Platform; Immunophenotyping; Diagnostics

Through the standardization and augmentation of Canadian invented and manufactured biotechnology, this multi-disciplinary and collaborative academic-industry partnership aims to overcome a biomedical challenge faced by scientists and clinicians across Canada. By facilitating the use of high-dimension histopathology imaging for immune cell profiling in small tissue biopsies across a network of Canadian hospitals, this project has the potential to elevate the Canadian healthcare environment in order to attract international clinical trials and biopharmaceutical investment and improve the health outcomes of all Canadians. The combined efforts of world experts in high dimension histopathology imaging biotechnology methods, probabilistic machine-learning methods for single cell analysis, and the clinical application of immune profiling will create of a robust automated pipeline for immune diagnostics which will be shared nationwide. This tool will be benchmarked in retrospective, observational and harmonization studies using multiplexed immune cell biomarkers. In concert with the manufacturer of imaging mass cytometry, the standardization and dissemination of image acquisition, processing, and machine learning analysis methods will create a multi-center network capable of providing access to cutting edge diagnostics in Canada.

通过加拿大发明和制造的生物技术的标准化和增强，这种多学科和协作的学术-工业伙伴关系旨在克服加拿大科学家和临床医生面临的生物医学挑战。通过促进在加拿大医院网络中使用高维度组织病理学成像进行小组织活检中的免疫细胞分析，该项目有可能提升加拿大的医疗保健环境，以吸引国际临床试验和生物制药投资，并改善所有加拿大人的健康结果。世界专家在高维组织病理学成像生物技术方法、单细胞分析的概率机器学习方法以及免疫分析的临床应用方面的共同努力，将为免疫诊断创建一个强大的自动化管道，并将在全国范围内共享。该工具将在使用多重免疫细胞生物标志物的回顾性、观察性和协调性研究中进行基准测试。与成像质谱细胞仪制造商合作，图像采集、处理和机器学习分析方法的标准化和传播将创建一个多中心网络，能够在加拿大提供最先进的诊断服务。