PFI-TT: A Rapid Multiplexed Diagnostic Tool for Serology of Tick-Borne Diseases

这一创新-技术转化伙伴关系(PFI-TT)项目旨在通过一种创新的、多元化的血清学护理点(POC)检测来改进基于血液的扁虱传播疾病(TBD)的检测。该项目将解决当前待定疾病诊断方法中的一个关键空白，开发一个针对莱姆病、巴贝斯病、无浆体和复发性发热的综合平台。通过涵盖共同位于相似地理区域的不同TBD，该平台提供了单一测试解决方案，以确定暴露于多个TBD，从而占据了可用市场的很大一部分。该工具的简单性和可负担性使其对资源有限和受待定疾病影响最大的农村地区有利。此外，该平台预计将具有显著的社会和医疗保健效益，使患者和医生能够进行及时的测试，以衡量对多个TBD的免疫反应，这在确定患者护理和治疗方案方面至关重要。该项目的商业潜力在于满足对全面和经济高效的待定疾病诊断的巨大市场需求，有望在包括诊所和野外站在内的各种医疗保健环境中广泛采用。通过加强医疗诊断领域的科学理解和技术，该项目与改善全球健康的更广泛目标保持一致。该项目专注于开发一种能够同时检测多个TBD的POC、多路复用的血清学检测方法。这项技术解决了当前血清学检测中的交叉反应、不同结核病在流行地区的共同感染以及有限的敏感性和特异性的挑战。通过将不同TBD的特定抗原表位整合到单一的多路测试中，并采用先进的机器学习算法，该解决方案旨在显著提高血清诊断的准确性。该研究涉及迭代表位选择和包含多路复用板的纸基免疫反应平台的优化。这项技术还涉及开发一种基于机器学习的强大诊断算法，将不同的生物标记物特定信号分析为可解释和可操作的诊断，供医生用于治疗患者。该项目解决了目前缺乏针对TBD的护理点(POC)多路测试的问题，在这种情况下，患者通常需要在不同的集中式实验室进行多次测试。该项目的预期成果包括提高各种结核病的血清诊断能力，为医疗诊断和公共卫生领域做出重大贡献，特别是在壁虱传播感染高发地区。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Partnerships for Innovation - Technology Translation (PFI-TT) project seeks to improve blood-based detection of tick-borne diseases (TBDs) through an innovative, multiplexed, serological point-of-care (POC) assay. Addressing a critical gap in current TBD diagnostic methods, this project will develop a comprehensive platform for Lyme disease, Babesia, Anaplasma, and relapsing fever. By encompassing different TBDs co-located in similar geographical areas, the platform provides a single test solution to determine exposure to multiple TBDs, thus capturing a significant segment of the available market. The simplicity and affordability of the tool make it beneficial for resource-limited and rural areas, most impacted by TBDs. Furthermore, the platform is expected to have significant societal and healthcare benefits, allowing patients and physicians to conduct timely testing to measure immune response against multiple TBDs, which is critical in determining patient care and treatment regimens. The commercial potential of this project lies in filling a substantial market need for comprehensive and cost-effective TBD diagnostics, promising widespread adoption in various healthcare settings, including clinics and field-stations. By enhancing scientific understanding and technology in the medical diagnostics field, this project aligns with the broader goal of improving global health.This project focuses on the development of a POC, multiplexed, serological assay capable of detecting multiple TBDs simultaneously. The technology addresses the challenge of cross-reactivity, co-infection of different TBDs in endemic regions and limited sensitivity and specificity in current serological tests. By integrating specific antigen epitopes for various TBDs into a single multiplexed assay and employing advanced machine learning algorithms, this solution aims to significantly enhance serodiagnostic accuracy. The research involves iterative epitope selection and optimization of the paper-based immunoreaction platform comprising the multiplexed panel. The technology also involves developing a robust, machine learning-based diagnostic algorithm to analyze different biomarker-specific signals into interpretable and actionable diagnoses that can be used by physicians to treat patients. This project addresses the current lack of a point-of-care (POC) multiplexed test for TBDs, where patients typically require multiple tests at different centralized labs. The project's anticipated outcomes include improved serodiagnostic capabilities for various TBDs, contributing significantly to the fields of medical diagnostics and public health, particularly in areas with a high prevalence of tick-borne infections.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.