I-Corps: Metabolomics and Machine Learning Platform for Diagnostics

I-Corps项目的更广泛影响/商业潜力在于开发一种简单的血液检测方法，可以识别癌症、慢性心肺疾病和糖尿病等疾病。为了更快地诊断这些疾病，这项拟议中的技术使用了血液中特定的代谢物。随着细胞因疾病而改变其功能，代谢物也会发生变化，并可能作为一种特定模式，即报告疾病的“指纹”。这些模式可以通过质谱（MS）记录下来，并由人工智能（AI）识别。通过质谱和人工智能分析对专利“指纹”进行公正的识别可能会产生诊断。拟议中的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较小的测试，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，可在初级保健机构、医院或紧急护理地点使用。这个I-Corps项目旨在检测癌症、慢性肺病和心脏病。最初，癌症、肺部或心脏疾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（如疲劳和疲劳）后，病情往往在两年以上仍未被发现。迫切需要新的诊断工具来缩短诊断时间，并在疾病的早期阶段开始治疗。已知癌症、肺病和心脏病会显著改变代谢谱。提出的技术表明，当疾病较轻且无明显症状时，代谢物就会发生改变。因此，循环代谢物的分析可以成为在早期和发展阶段追踪疾病的有效工具。这项拟议的专利技术可以检测与心脏病、结直肠癌和其他慢性肺部疾病引起的肺动脉高压相关的循环代谢物的特定变化。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小组。每个组由10到12个代谢物组成，允许分离一组特定的疾病，目前的精度大于75-98%。该奖项反映了美国国家科学基金会的法定使命，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。

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.