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

这项创新-技术转化伙伴关系（PFI-TT）项目旨在通过一种创新的、多路复用的血清学即时检测（POC），改善蜱传疾病（tbd）的血液检测。该项目将开发一个莱姆病、巴贝斯虫病、无形体病和回归热的综合平台，以弥补目前TBD诊断方法的重大空白。通过将位于相似地理区域的不同tbd包含在内，该平台提供了一个单一的测试解决方案，以确定对多种tbd的暴露情况，从而占领了可用市场的重要部分。该工具的简单性和可负担性使其适用于受tbd影响最大的资源有限地区和农村地区。此外，该平台预计将具有重大的社会和医疗效益，使患者和医生能够及时进行检测，以衡量针对多种tbd的免疫反应，这对于确定患者护理和治疗方案至关重要。该项目的商业潜力在于满足市场对全面和具有成本效益的TBD诊断的大量需求，有望在各种医疗保健环境中广泛采用，包括诊所和现场站。通过加强医学诊断领域的科学认识和技术，该项目与改善全球健康的更广泛目标保持一致。该项目的重点是开发一种能够同时检测多种tbd的多路血清学检测方法。该技术解决了交叉反应性、不同tbd在流行地区的共同感染以及当前血清学检测灵敏度和特异性有限的挑战。通过将不同tbd的特异性抗原表位整合到一个单一的多路分析中，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。本研究涉及到由多路复用面板组成的基于纸张的免疫反应平台的迭代表位选择和优化。该技术还涉及开发一种强大的、基于机器学习的诊断算法，将不同的生物标志物特异性信号分析成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的即时（POC）多路检测的问题，患者通常需要在不同的集中实验室进行多次检测。该项目的预期成果包括提高对各种传染性疾病的血清诊断能力，为医疗诊断和公共卫生领域，特别是在蜱传感染高发地区作出重大贡献。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。

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.