3D Engineering of Ocular Tissues for Disease Modeling and Drug Testing
3D Engineering of Ocular Tissues for Disease Modeling and Drug Testing
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DOI：
10.1007/978-3-030-28471-8_7
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发表时间：
2019-01-01
期刊：
影响因子：
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通讯作者：
Song, M. J.
中科院分区：
文献类型：
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作者：
Boutin, M. E.;Hampton, C.;Song, M. J.
尽管科学技术取得了重大进步，资金和投资稳步增加，但几十年来，从研究新药申报到药品审批的成功率仍然很低。未能证明药物疗效一直是药物开发无法超过II期和III期临床试验的主要原因。二维（2D）细胞体外模型和动物模型的组合已经成为基础科学研究和临床前药物开发研究的金标准。然而，这些系统的大多数发现都未能转化为人体试验，因为这些模型只能部分概括人类的生理学和病理学。在2D细胞模型中缺乏动态三维微环境降低了生理相关性，并且由于这些原因，3D和微流体模型系统现在被开发为更类似于天然的生物测定平台。3D细胞体外系统，微流体，自组织类器官和3D生物织物是模拟人类生理学的最有前途的技术，因为它们为多细胞组件提供机械线索和3D微环境。随着人类诱导多能干细胞（iPSC）技术的出现，3D动态体外系统进一步实现了对类人组织模型的广泛访问。随着越来越复杂的3D细胞系统的产生，由于3D组织的厚度和不透明性，当前可视化技术的使用受到限制。组织清除技术通过匹配3D组件之间的折射率来改善光深入组织的穿透。3D分割使得能够基于3D组织图像进行定量测量。使用这些最先进的技术，在3D组织模型中对数千种药物化合物进行高通量筛选（HTS）正在慢慢成为现实。为了筛选数千种化合物，需要应用机器学习来帮助最大限度地利用化学信息学和表型方法进行药物筛选。在这一章中，我们讨论了目前的3D眼部模型重演的生理和病理的眼睛的后面，并进一步讨论可视化和量化技术，可以实现药物筛选在眼部疾病。
The success rate from investigational new drug filing to drug approval has remained low for decades despite major scientific and technological advances, and a steady increase of funding and investment. The failure to demonstrate drug efficacy has been the major reason that drug development does not progress beyond phase II and III clinical trials. The combination of two-dimensional (2D) cellular in vitro and animal models has been the gold standard for basic science research and preclinical drug development studies. However, most findings from these systems fail to translate into human trials because these models only partly recapitulate human physiology and pathology. The lack of a dynamic three-dimensional microenvironment in 2D cellular models reduces the physiological relevance, and for these reasons, 3D and microfluidic model systems are now being developed as more native-like biological assay platforms. 3D cellular in vitro systems, microfluidics, self-organized organoids, and 3D biofabrication are the most promising technologies to mimic human physiology because they provide mechanical cues and a 3D microenvironment to the multicellular components. With the advent of human-induced pluripotent stem cell (iPSC) technology, the 3D dynamic in vitro systems further enable extensive access to human-like tissue models. As increasingly complex 3D cellular systems are produced, the use of current visualization technologies is limited due to the thickness and opaqueness of 3D tissues. Tissue-clearing techniques improve light penetration deep into tissues by matching refractive indices among the 3D components. 3D segmentation enables quantitative measurements based on 3D tissue images. Using these state-of-the-art technologies, high-throughput screening (HTS) of thousands of drug compounds in 3D tissue models is slowly becoming a reality. In order to screen thousands of compounds, machine learning will need to be applied to help maximize outcomes from the use of cheminformatics and phenotypic approaches to drug screening. In this chapter, we discuss the current 3D ocular models recapitulating physiology and pathology of the back of the eye and further discuss visualization and quantification techniques that can be implemented for drug screening in ocular diseases.