生物
类有机物
吞吐量
计算生物学
药物发现
药品
遗传学
生物信息学
药理学
计算机科学
电信
无线
作者
Jiangwei Zuo,Yanhua Fang,Ruoyu Wang,Shanshan Liang
标识
DOI:10.1093/stmcls/sxae070
摘要
Tumor organoids have emerged as an ideal in vitro model for patient-derived tissues, as they recapitulate the characteristics of the source tumor tissue to a certain extent, offering the potential for personalized tumor therapy and demonstrating significant promise in pharmaceutical research and development. However, establishing and applying this model involves multiple labor-intensive and time-consuming experimental steps and lacks standardized protocols and uniform identification criteria. Thus, high-throughput solutions are essential for the widespread adoption of tumor organoid models. This review provides a comprehensive overview of current high-throughput solutions across the entire workflow of tumor organoids, from sampling and culture to drug screening. Furthermore, we explore various technologies that can control and optimize single-cell preparation, organoid culture, and drug screening with the ultimate goal of ensuring the automation and high efficiency of the culture system and identifying more effective tumor therapeutics.
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