Human Organ-on-a-Chip Microphysiological Systems to Model Musculoskeletal Pathologies and Accelerate Therapeutic Discovery

人体器官芯片微生理系统可模拟肌肉骨骼病理并加速治疗发现

阅读:7
作者:Raquel E Ajalik, Rahul G Alenchery, John S Cognetti, Victor Z Zhang, James L McGrath, Benjamin L Miller, Hani A Awad

Abstract

Human Microphysiological Systems (hMPS), otherwise known as organ- and tissue-on-a-chip models, are an emerging technology with the potential to replace in vivo animal studies with in vitro models that emulate human physiology at basic levels. hMPS platforms are designed to overcome limitations of two-dimensional (2D) cell culture systems by mimicking 3D tissue organization and microenvironmental cues that are physiologically and clinically relevant. Unlike animal studies, hMPS models can be configured for high content or high throughput screening in preclinical drug development. Applications in modeling acute and chronic injuries in the musculoskeletal system are slowly developing. However, the complexity and load bearing nature of musculoskeletal tissues and joints present unique challenges related to our limited understanding of disease mechanisms and the lack of consensus biomarkers to guide biological therapy development. With emphasis on examples of modeling musculoskeletal tissues, joints on chips, and organoids, this review highlights current trends of microphysiological systems technology. The review surveys state-of-the-art design and fabrication considerations inspired by lessons from bioreactors and biological variables emphasizing the role of induced pluripotent stem cells and genetic engineering in creating isogenic, patient-specific multicellular hMPS. The major challenges in modeling musculoskeletal tissues using hMPS chips are identified, including incorporating biological barriers, simulating joint compartments and heterogenous tissue interfaces, simulating immune interactions and inflammatory factors, simulating effects of in vivo loading, recording nociceptors responses as surrogates for pain outcomes, modeling the dynamic injury and healing responses by monitoring secreted proteins in real time, and creating arrayed formats for robotic high throughput screens. Overcoming these barriers will revolutionize musculoskeletal research by enabling physiologically relevant, predictive models of human tissues and joint diseases to accelerate and de-risk therapeutic discovery and translation to the clinic.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。