Non-Invasive Clinical Testing Using Biosensors

描述(由申请人提供)：非侵入性临床诊断的发展是改善医疗保健的一个重要目标。人们越来越意识到，旨在检测唾液和尿液的特定诊断方法可能与传统的血液测试一样，对许多疾病和障碍具有预测作用。理想情况下，未来对唾液和尿液的检测将是快速、定量的，并能够在适当的时候进行持续监测。生物传感器仪器与新的诊断分析相结合，在这一领域提供了巨大的希望，前提是在解决几个技术问题方面取得了进展。BioHesion公司将在拟议的可行性研究中使用专有协议，以实现以下目标： 1)建立唾液和尿液中总SLGA和白蛋白的定量诊断试验，使用表面等离子体共振检测。测试在10-15分钟内完成。在第二阶段，身体分泌物中的总SLGA测量将是测量特定SLGA的测试的要求。 2)在检测唾液和尿液时显著减少了生物传感器的污垢。 3)生物传感分析的灵敏度至少提高了10倍。 4)提高生物传感表面的耐用性，以允许重复使用或连续监测患者。 这些目标的成功实现将促进能够在检测点进行定量、非侵入性诊断的移动仪器的实施。最终，随着传感器小型化趋势的继续，在该项目中开发的强大的分析将与能够对患者进行连续体内监测的微型传感器集成在一起。

DESCRIPTION (provided by applicant): The development of non-invasive clinical diagnostics is a significant goal for improving healthcare. There is increasing awareness that specific diagnostics designed to test saliva and urine may be as predictive as conventional blood tests for many diseases and disorders. Ideally, future testing of saliva and urine will be rapid, quantitative and capable of continuous monitoring when appropriate. Biosensor instrumentation coupled with novel diagnostic assays offers great promise in this area provided there is progress in addressing several technical problems. BioHesion, Inc. will use proprietary protocols in the proposed feasibility research to achieve the following goals: 1) Development of diagnostic tests to quantify total slgA and albumin in saliva and urine using surface plasmon resonance detection. Testing is completed in 10-15min. Total slgA measurements in body secretions will be a requirement for tests to measure specific slgA in Phase II. 2) A significant reduction in biosensor fouling when testing saliva and urine. 3) An increase in the sensitivity of biosensing assays of at least 10-fold. 4) Increased durability of biosensing surfaces to permit repeated use or continuous monitoring of patients. The successful achievement of these goals will facilitate the implementation of mobile instruments capable of quantitative, non-invasive diagnostics at point-of testing. Ultimately, as the trend in sensor miniaturization continues, the robust assays developed in this project will be integrated with tiny sensors capable of continuous in vivo monitoring of patients.