I-Corps: Metabolomics and Machine Learning Platform for Diagnostics

I-Corps:用于诊断的代谢组学和机器学习平台

基本信息

  • 批准号:
    2054157
  • 负责人:
  • 金额:
    $ 5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-03-15 至 2022-08-31
  • 项目状态:
    已结题

项目摘要

The broader impact/commercial potential of this I-Corps project is in developing a simple blood test that can recognize diseases like cancer, chronic heart and lung disorders, and diabetes. To diagnose these diseases faster, the proposed technology uses a specific panel of metabolites in the blood. Metabolites change as cells change their function because of disease and could serve as a specific pattern, "fingerprint" that reports the disease. These patterns can be recorded by mass spectrometry (MS) and recognized by artificial intelligence (AI). Unbiased identification of the patented "fingerprints" by MS and analysis using AI may produce a diagnosis. The proposed technology may not only reduce time-to-diagnosis from years to days but provide less-invasive tests for customers, replacing techniques such as biopsies, colonoscopies, and heart catheterizations. This method will not depend on the professional qualification of health care workers and can be used at primary care facilities, hospitals, or urgent care sites.This I-Corps project seeks to detect cancers and chronic lung and heart diseases. Initially, cancers and lung or heart diseases develop asymptomatically and so the patient does not seek professional help. Even after the onset of nonspecific symptoms, such as tiredness and fatigue, conditions often remain unrecognized for greater than two years. There is a significant need for novel diagnostic tools to shorten the time-to-diagnosis and initiate therapy at earlier stages of the disease. Cancers and lung and heart diseases are known to significantly alter the metabolic profile. The proposed technology shows that alterations in metabolites occur when diseases are mild and no symptoms are evident. Thus, profiling of circulating metabolites could become an efficient tool for tracing diseases at early and developed stages. The proposed patented technology detects specific changes in circulating metabolites that relate to discrete pulmonary hypertension from heart disease, colorectal cancer, and other chronic lung conditions. A mass spectrometry (MS) based platform is used for differential diagnosis to distinguish from diseases with similar, non-specific symptoms. Three preliminary metabolic panels have been developed. Each panel comprises of ten to twelve metabolites allowing separation of a specific group of diseases with current precision greater than 75-98%.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I-Corps项目更广泛的影响/商业潜力是开发一种简单的血液测试,可以识别癌症,慢性心脏和肺部疾病以及糖尿病等疾病。为了更快地诊断这些疾病,拟议中的技术使用血液中的特定代谢物。随着细胞因疾病而改变其功能,代谢物发生变化,并可作为报告疾病的特定模式,“指纹”。这些模式可以通过质谱(MS)记录并通过人工智能(AI)识别。 通过MS对专利“指纹”的无偏见识别和使用AI的分析可能会产生诊断。这项技术不仅可以将诊断时间从几年缩短到几天,还可以为客户提供侵入性更低的测试,取代活检、结肠镜检查和心脏导管插入术等技术。这种方法不依赖于卫生保健工作者的专业资格,可在初级保健设施、医院或紧急护理地点使用。最初,癌症和肺部或心脏病的发展是无症状的,因此患者不会寻求专业帮助。即使在出现非特异性症状(如疲倦和疲劳)后,病情往往在两年以上的时间内仍未被发现。对于新的诊断工具存在显著的需求,以缩短诊断时间并在疾病的早期阶段开始治疗。已知癌症、肺和心脏疾病会显著改变代谢特征。拟议的技术表明,当疾病轻微且没有明显症状时,代谢物会发生变化。因此,分析循环代谢物可成为在早期和发展阶段追踪疾病的有效工具。拟议的专利技术检测循环代谢物中的特定变化,这些变化与心脏病、结直肠癌和其他慢性肺部疾病引起的离散肺动脉高压有关。基于质谱(MS)的平台用于鉴别诊断,以区分具有相似非特异性症状的疾病。已经开发了三个初步的代谢组。每个小组由10到12种代谢物组成,可以分离特定疾病组,目前的精确度超过75- 98%。该奖项反映了NSF的法定使命,并被认为值得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来支持。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Ruslan Rafikov其他文献

Predictive modeling of ARDS mortality integrating biomarker/cytokine, clinical and metabolomic data
整合生物标志物/细胞因子、临床和代谢组学数据的急性呼吸窘迫综合征(ARDS)死亡率预测模型
  • DOI:
    10.1016/j.trsl.2025.05.005
  • 发表时间:
    2025-07-01
  • 期刊:
  • 影响因子:
    5.900
  • 作者:
    Ruslan Rafikov;Debrah M. Thompson;Olga Rafikova;Sara M. Camp;Roberto A. Ribas;Ramon C. Sun;Matthew S. Gentry;Nancy G. Casanova;Joe G N Garcia
  • 通讯作者:
    Joe G N Garcia
406 - Role of Carboxyl-Terminal Modulator Protein in the Nitration Mediated Activation of Akt1
  • DOI:
    10.1016/j.freeradbiomed.2014.10.055
  • 发表时间:
    2014-11-01
  • 期刊:
  • 影响因子:
  • 作者:
    Ruslan Rafikov;Xutong Sun;Olga Rafikova;Saurabh Aggarwal;Christine Gross;Yali Hou;Steve M Black
  • 通讯作者:
    Steve M Black
Post-Translational Regulation of RhoA and Rac1
  • DOI:
    10.1016/j.freeradbiomed.2011.10.357
  • 发表时间:
    2011-11-01
  • 期刊:
  • 影响因子:
  • 作者:
    Ruslan Rafikov;Saurabh Aggarwal;Christine Gross;Yali Hou;Connie Snead;John Catravas;David Fulton;Stephen M. Black
  • 通讯作者:
    Stephen M. Black
206 - Targeted Protein Protection from Oxidative/ Nitrosative Post-Translational Modifications Using Shielding Peptides
  • DOI:
    10.1016/j.freeradbiomed.2015.10.250
  • 发表时间:
    2015-10-01
  • 期刊:
  • 影响因子:
  • 作者:
    Olga Rafikova;Stephen M Black;Ruslan Rafikov
  • 通讯作者:
    Ruslan Rafikov
The Anti-Proliferative Effect of Bosentan in Occlusive Pulmonary Hypertension Involves a Reduction in Both Oxidative and Nitrosative Stress
  • DOI:
    10.1016/j.freeradbiomed.2011.10.358
  • 发表时间:
    2011-11-01
  • 期刊:
  • 影响因子:
  • 作者:
    Olga Rafikova;Ruslan Rafikov;Sanjiv Kumar;Shruti Sharma;Saurabh Aggarwal;Frank Schneider;Danny Jonigk;Stephen M. Black;Stevan Tofovic
  • 通讯作者:
    Stevan Tofovic

Ruslan Rafikov的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

相似海外基金

Next Generation Mass Spectrometry for Single-Cell Metabolomics
单细胞代谢组学的下一代质谱分析
  • 批准号:
    DE240100259
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Discovery Early Career Researcher Award
Blood metabolomics as a next-generation cancer diagnostic platform technology
血液代谢组学作为下一代癌症诊断平台技术
  • 批准号:
    10067218
  • 财政年份:
    2024
  • 资助金额:
    $ 5万
  • 项目类别:
    Collaborative R&D
High-Resolution Ion Mobility enabled LC-MS for metabolomics applications
高分辨率离子淌度 LC-MS 适用于代谢组学应用
  • 批准号:
    BB/X019608/1
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Research Grant
Transition: Metabolomics-driven understanding of rules that coordinate metabolic responses and adaptive evolution of synthetic biology chassis
转变:代谢组学驱动的对协调代谢反应和合成生物学底盘适应性进化的规则的理解
  • 批准号:
    2320104
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
EAGER: Metabolomics Analysis of Archival Marine Invertebrates
EAGER:档案海洋无脊椎动物的代谢组学分析
  • 批准号:
    2341344
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Prospective metabolomics investigation of gastric cancer risk in African Americans and European Whites with a low socioeconomic status
社会经济地位较低的非裔美国人和欧洲白人胃癌风险的前瞻性代谢组学调查
  • 批准号:
    10912190
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Spatial metabolomics with subcellular resolution to identify therapeutic targets
具有亚细胞分辨率的空间代谢组学以确定治疗靶点
  • 批准号:
    10714487
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Prenatal Longitudinal Metabolomics Profiling for Early Childhood Growth Trajectories and Obesity Risk in a US Biracial Birth Cohort
美国混血出生队列中儿童早期生长轨迹和肥胖风险的产前纵向代谢组学分析
  • 批准号:
    10580910
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
Characterizing metabolic variability during pregnancy to understand pathways of in-utero overnutrition: an integrative analysis of metabolomics and lifestyle data
表征妊娠期间的代谢变异性以了解子宫内营养过剩的途径:代谢组学和生活方式数据的综合分析
  • 批准号:
    10913646
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
CAREER: Open-Access, Real-Time High-Throughput Metabolomics for High-Field and Benchtop NMR for Biological Inquiry
职业:用于生物研究的高场和台式 NMR 的开放获取、实时高通量代谢组学
  • 批准号:
    2237314
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了