CAREER: Reconfigurable Microfluidic-Microbalance Sensors to Monitor and Optimize the Performance of Microphysiological Models

可重构传感系统是可适应的平台，可以根据需要检测和量化任何目标；然而，此类系统尚未被翻译和应用于生物传感和生物技术领域。传感器设计的范式转变需要新的生物传感能力，从定制传感器以适应狭窄的目标和条件，转向更具适应性的平台，其中传感器体系结构不变，同时其性能可调整以匹配生物分析物的特定浓度和复杂性。该项目旨在研究和设计新一代可重构生物传感器平台，用于测量多个循环生物标志物，并为微生理模型的开发和分析提供信息。微生理学模型复制了人体器官功能，是基础生物学研究和发现可翻译生物标记物、药物和再生疗法的很有前途的技术；然而，由于微生理学模型在解剖学和细胞学上的复杂性，在测量和分析这种复杂系统的功能和性能方面存在重大挑战。可重构的多路传感器将为监测微生理模型的并行化提供一种新的技术，即可以同时操作、监测和分析多个微生理模型和生物标志物。这样的技术将有助于我们更好地理解任何工程化的大组织、器官或模型的基本发展。这一知识将通过减少变异性和提供更多统计上强大的试验，更好地为动物或临床试验提供信息，并确定新的研究目标，从而加速生物技术研究。该项目的跨学科性质，结合了微电子、微流体、数据科学和组织工程，将需要同样的跨学科教育和全球参与计划，这将通过与高中STEM教师通过真实的夏季研究经验和参加面向本科生和研究生的国际普查生物传感器研究竞赛来实施。该计划的研究目标是设计、制造和验证用于可重构的、多路复合的微流体-微天平的传感器，该系统由一系列微型石英晶体微天平和集成的微流体组成，以表征微生理模型的生化和生物物理特性。具体地说，将研究新型生物合成识别部分的工作频率、结合选择性和再生。了解这些参数将使微流控-微平衡平台能够针对不同的生物标记物进行重新配置；此外，多路传感可以阐明生物标记物集合与生物功能之间的新关联。拟议的研究将包括(1)在复杂介质中微流控-微天平阵列的传输和操作的建模，(2)具有新型生物合成识别元件的传感器的微制造和实验测试，以及(3)开发必要的硬件和计算算法来处理多路数据流。为了展示这些创新，传感器将通过人体微血管系统的微生理模型进行验证，以(1)提取、处理和生化分析循环介质，(2)测量灌流压力和粘度，并将其与微血管发育相关联，以及(3)利用这些数据流来预测和优化模型的生物功能。这项工作将为研究微生理模型和复杂的体外生物系统的新的多路传感策略奠定基础。总的来说，这项研究将为未来研究制造传感器的创新方法指明一条道路，使其能够同时监测多个生化分析物，重新配置用于不同器官的MPM，并为机器学习方法的未来发展生成数据流，以分析和发现生物标记物之间的新关联。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。

Reconfigurable sensing-systems are adaptable platforms that can detect and quantify any target on-demand; however, such systems have not been translated and applied to fields of biosensing and biotechnology. New biosensing capabilities are needed for a paradigm shift in sensor design, from tailoring the sensor to fit a narrow range of targets and conditions, towards a more adaptable platform, wherein the sensor architecture is unvaried, while its performance is tuned to match a particular concentration and complexity of the biological analyte. This project aims to investigate and engineer a new generation of reconfigurable biosensor platforms that can be used to measure multiple circulating biomarkers and inform the development and analysis of microphysiological models. Microphysiological models replicate human organ function, and they are promising technologies for fundamental biological research and discovery of translatable biomarkers, pharmaceuticals, and regenerative therapies; however, due to the anatomical and cellular complexity of microphysiological models, a major challenge exists in measuring and analyzing the function and performance of such complex systems. Reconfigurable, multiplexed sensors will provide a new technique for the parallelization of monitoring microphysiological models, i.e. many microphysiological models and biomarkers can be operated, monitored, and analyzed simultaneously. Such a technology is poised to better our understanding of the fundamental development of any engineered large tissue, organ, or model. This knowledge will accelerate biotechnology research by reducing variability and providing more statistically powerful trials, better informing animal or clinical testing, and identifying new targets for investigation. The interdisciplinary nature of this project, combining microelectronics, microfluidics, data science, and tissue engineering will require equally interdisciplinary education and global engagement plan, which will be implemented by collaborating with high school STEM teachers through authentic summer research experiences and participating in the international SensUs Biosensors Research Competition for undergraduate and graduate students.The research objective of this proposal is to design, fabricate, and validate sensors for a reconfigurable, multiplexed microfluidic-microbalance system, which is comprised of an array of miniature quartz-crystal microbalances and integral microfluidics to characterize both biochemical and biophysical properties of microphysiological models. Specifically, the operational frequency, binding selectivity, and regeneration of the novel biosynthetic-recognition moieties will be investigated. Understanding these parameters will enable the microfluidic-microbalance platform to be reconfigured for different biomarkers; moreover, the multiplexed sensing can elucidate new correlations between sets of biomarkers and biological function. The proposed research will include (1) modelling of microfluidic delivery and operation of microfluidic-microbalance arrays in complex media, (2) microfabrication and experimental testing of sensor with novel biosynthetic-recognition elements, and (3) the development of the necessary hardware and computational algorithms to process the multiplexed data streams. To demonstrate these innovations, the sensors will be validated with a microphysiological model of human microvasculature to (1) extract, process, and biochemically analyze circulating media, (2) measure and correlate perfusion pressure and viscosity to microvascular development, and (3) harnesses these data streams to predict and optimize biological function of the model. This effort will be the foundation for new multiplexed sensing strategies to investigate microphysiological models and complex in vitro biological systems. Broadly, this research will illuminate a pathway for future research into innovative means of making sensors to monitor multiple biochemical analytes simultaneously, to be reconfigured for use in MPMs of different organs, and to generate data streams for the future development of machine learning methods to analyze and discover novel correlations between biomarkers.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.