3D Renal Tissue Chip Models to Evaluate Nephrotoxic Effects of Drugs

项目总结 目前的药物发现途径与25.5亿美元的成本和10-15年的 开发一种单一的药物以进入市场。预测药物毒性和有效性的挑战是 归因于药物代谢酶活性和细胞类型特异性的固有物种差异 对毒物的敏感性。芯片器官是一种新兴的疾病建模和筛查技术 治疗，以解决动物模型和人类临床试验之间的差异。他们利用组织 工程学、流体力学和生物材料复制体内复杂器官的结构和功能 还有纸巾。活体肾近端小管(PT)暴露于流体流动和机械应力(压力， 拉伸、剪切)，这些刺激在维持细胞表型和动态平衡方面起着重要作用。 目前，现有的原型无法复制体内环境，因为它们经常无法模拟 生理力量。因此，这些模型在预测药物诱因方面的成功有限。 肾毒性。在这个方案中，我们将对PT的动态平台进行生物工程和评估，并研究 药物和肾小管功能障碍的影响，以确定其在翻译研究中的潜力。人肾近端 人肾小管细胞(HRPTECs)将在明胶甲基丙烯酰凝胶(GelMA)水凝胶中进行生理性剪切培养 和压力。这些设备还将通过使用hRPTEC来整合患者群体的多样性 以确定年龄、性别和种族差异对肾毒性效应的影响。毒品会 根据他们的肾毒性风险(高、中、低)进行分类，该平台将包括 自动读数以反映细胞功能和生存能力。总而言之，这将有助于更准确地调查 药理和病理反应，并确定体外灌流模型的实用性。第二， 将开发一种更复杂、更新颖的生物工程平台。该设计包含一个3D PT管材和 周细胞血管网环绕的三维血管。然后，平台将受到 生理剪应力和压力显示的流动循环可以准确地模拟细胞的组织， 紧密连接的建立，屏障功能的维持，以及体内的选择性运输。这 装置由hRPTECs、人脐静脉内皮细胞(HUVECs)和人 GelMA水凝胶中的真皮成纤维细胞(HDF)来模拟重吸收和 分泌功能是复制的。最后，这项建议研究了PT组织芯片的翻译潜力 通过PT糖尿病肾病模型的论证和工程多井病例的建立，促进高脂血症的发生。 吞吐量研究。在这项研究中开发的芯片上的器官将提供一种使能技术， 在基础研究和翻译研究中的广泛应用，以模拟疾病状态，研究与其他 组织芯片，并准确预测药物毒性。

PROJECT SUMMARY The current pathway for drug discovery is associated with costs of $2.55 billion and between 10-15 years of development for a single drug to reach the market. The challenges in predicting drug toxicities and efficacies are attributed to inherent species differences in drug-metabolizing enzyme activities and cell-type-specific sensitivities to toxicants. Organs-on-a-chip are an emerging technology in disease modeling and screening therapeutics to address discrepancies between animal models and human clinical trials. They utilize tissue engineering, fluid mechanics, and biomaterials to replicate in vivo architectures and functions of complex organs and tissues. The renal proximal tubule (PT) in vivo is exposed to fluid flow and mechanical stress (pressure, stretch, shear) and these stimuli play an important role in maintaining cellular phenotype and homeostasis. Currently, available prototypes fall short of replicating the in vivo environment because they often fail to mimic the physiological forces. Therefore, these models have had limited success in predicting drug-induced nephrotoxicity. In this proposal, we will bioengineer and evaluate a dynamic platform of the PT and study the effects of drugs and tubular dysfunction to establish its potential for translational research. Human renal proximal tubule cells (hRPTECs) will be cultured within gelatin methacryloyl (GelMA) hydrogels under physiological shear and pressure. These devices will also incorporate the diversity in the patient population by using hRPTECs from multiple donors to determine the impact of age, sex, and racial differences on nephrotoxicity effects. Drugs will be classified based on their nephrotoxic risk (high, intermediate, and low) and the platform will incorporate automated readouts to reflect cellular function and viability. Together, this will help investigate more accurate pharmacological and pathological responses and to determine the utility of in vitro perfusion models. Secondly, a more complex and novel bioengineered platform will be developed. This design contains a 3D PT tubule and 3D vascular vessels surrounded by pericyte vascular networks. The platform will then be subjected to physiological shear stress and pressure to demonstrate the flow loop can accurately mimic cellular organization, establishment of tight junctions, maintenance of barrier function, and selective transport as seen in vivo. This device composes of a co-culture of hRPTECs, human umbilical vein endothelial cells (hUVECs), and human dermal fibroblasts (hDF) within a GelMA hydrogel to model an environment where both reabsorption and secretion functions are replicated. Lastly, this proposal investigates the translational potential of PT tissue chips through demonstration of a PT diabetic nephropathy model and engineering multi-well PTs to facilitate high- throughput studies. The organ-on-a-chip developed in this study will provide an enabling technology that has broad applications in basic and translational research to model disease states, study interactions with other tissue chips, and accurately predict drug toxicity.