Enabling New Functionality, Transport Analysis, and Deep Learning in Organ-on-a-Chip Systems

皮氏培养皿发明于19世纪，至今仍是生物学研究实验室中培养活细胞的常用设备，但并不能捕捉到体内真实活细胞、组织和器官周围环境的许多重要元素。虽然培养皿和其他常见的实验室培养物在过去已经导致了许多发现，但今天许多复杂的生物学问题，特别是那些与疾病过程有关的问题，涉及细胞微环境中的关键因素，如多种细胞类型之间的沟通、生物力学和附近血管中的血液流动，其中许多以前被忽视了。片上器官(OOC)系统就是解决这一问题的一种新技术。OOC是在实验室中精确设计的活体3D组织模型，它结合了微制造技术、微尺度流体流动以及各种生物成分，如活细胞和生物材料。通过适当地结合这些元素，OOCs可以模拟人类组织的结构、行为和功能，并比任何其他现有的体外组织模型更准确地响应环境刺激。因此，OOCs有可能给生物医学研究带来革命性的变化，加速科学发现。尽管取得了这些进展，但仍然存在重大的工程挑战，阻碍了OOC在研究和工业中的广泛使用。这些工程挑战包括：缺乏更高效、更可靠的制造方法来大规模制造OOC；直接内置到每个OOC中的功能有限；对OOC内的流体传输过程缺乏了解；以及从OOC实验获得的图像和其他数据的分析瓶颈。 我的研究目标就是解决这些问题，从而使这项技术得到更广泛的应用。该项目将专注于3个主要目标：1)通过开发新的制造方法、创建多层设备架构、添加新的片上传感元件并将模块化OOC连接在一起来创建复杂的OOC多系统来增加功能；2)使用流体力学研究中采用的颗粒跟踪方法分析各种OOC中的流体传输过程；以及3)应用深度学习计算机算法来“训练”计算机，从OOC获取的显微图像中自动有效地识别生物特征。 该项目将显著提高我们对OOC运营的理解，并提高我们开发下一代OOC的工程能力。这些进展将导致新的生物医学发现以及新的创新，这将使加拿大的生物技术行业受益，并促进加拿大不断增长的初创公司生态系统。它还将支持培训7名高素质人员和10名额外的工程专业学生，他们都将暴露在高度跨学科的世界级研究环境中，在那里他们将获得技术、可转移和领导技能。

The Petri dish, which was invented in the 19th century, remains a common device for culturing living cells in the biology research lab, but does not capture many of the important elements of the environment surrounding real living cells, tissues, and organs in the body. While the Petri dish and other common lab cultureware have led to many discoveries in the past, many complex biology questions today, especially those related to disease processes, involve critical factors in the cellular microenvironment such as communication between multiple cell types, biomechanical forces, and blood flow in nearby blood vessels, many of which have been previously neglected. Organ-on-a-chip (OOC) systems (or OOCs) are a new technology that addresses this problem. OOCs are living 3D tissue models engineered precisely in the lab by combining microfabrication techniques, microscale fluid flow, and various biological components such as living cells and biomaterials. By combining these elements appropriately, OOCs can mimic human tissue structure, behaviour, and function, and respond to environmental stimuli more accurately than any other existing in vitro tissue model. Thus, OOCs have potential to revolutionize biomedical research and accelerate scientific discovery. Despite this progress, major engineering challenges exist that hinder OOCs from widespread usage in research and industry. These engineering challenges include: lack of more efficient, reliable fabrication methods to mass manufacture OOCs; limited functionality built directly into each OOC; lack of understanding of fluid transport processes within OOCs; and bottleneck in the analysis of images and other data acquired from OOC experiments. The goal of my research is to solve these issues, leading to more widespread use of this technology. The project will focus on 3 main objectives: 1) increase functionality by developing new fabrication methods, creating multi-layered device architectures, adding new on-chip sensing elements, and connecting modular OOCs together to create complex OOC multi-systems; 2) analyze fluid transport processes in various OOCs using particle-tracking methods adopted from fluid mechanics research; and 3) applying deep learning computer algorithms to “train” a computer to automatically and efficiently identify biological features from microscopy images acquired from OOCs. The project will significantly improve our understanding of OOC operation, and advance our engineering capabilities for developing next-generation OOCs. These advances will lead to new biomedical discoveries as well as novel innovations that will benefit the Canadian biotech industry, and feed the growing ecosystem of startup companies in Canada. It will also support the training of 7 highly qualified personnel and 10 additional engineering students, who will all be exposed to a highly interdisciplinary world-class research environment where they will acquire technical, transferrable, and leadership skills.