Organoid engineering with microfluidics and biomaterials for liver, lung disease, and cancer modeling

微流控 类有机物 个性化医疗 计算机科学 材料科学 人类疾病 疾病 纳米技术 精密医学 医学 生物信息学 病理 生物 神经科学
作者
Su Kyeom Kim,Yu Heun Kim,Sewon Park,Seung‐Woo Cho
出处
期刊:Acta Biomaterialia [Elsevier BV]
卷期号:132: 37-51 被引量:76
标识
DOI:10.1016/j.actbio.2021.03.002
摘要

As life expectancy improves and the number of people suffering from various diseases increases, the need for developing effective personalized disease models is rapidly rising. The development of organoid technology has led to better recapitulation of the in vivo environment of organs, and can overcome the constraints of existing disease models. However, for more precise disease modeling, engineering approaches such as microfluidics and biomaterials, that aid in mimicking human physiology, need to be integrated with the organoid models. In this review, we introduce key elements for disease modeling and recent engineering advances using both liver and lung organoids. Due to the importance of personalized medicine, we also emphasize patient-derived cancer organoid models and their engineering approaches. These organoid-based disease models combined with microfluidics, biomaterials, and co-culture systems will provide a powerful research platform for understanding disease mechanisms and developing precision medicine; enabling preclinical drug screening and drug development. STATEMENT OF SIGNIFICANCE: The development of organoid technology has led to better recapitulation of the in vivo environment of organs, and can overcome the constraints of existing disease models. However, for more precise disease modeling, engineering approaches such as microfluidics and biomaterials, that aid in mimicking human physiology, need to be integrated with the organoid models. In this review, we introduce liver, lung, and cancer organoids integrated with various engineering approaches as a novel platform for personalized disease modeling. These engineered organoid-based disease models will provide a powerful research platform for understanding disease mechanisms and developing precision medicine.
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