3D Tissue Bioprinting Laboratory (3DTBL), Division of Pre-clinical Innovation (DPI), National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, MD, USA.
Biomedical Ultrasonics, Biotherapy and Biopharmaceuticals Laboratory, Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
SLAS Discov. 2021 Oct;26(9):1164-1176. doi: 10.1177/24725552211030903. Epub 2021 Jul 16.
A wide range of complex in vitro models (CIVMs) are being developed for scientific research and preclinical drug efficacy and safety testing. The hope is that these CIVMs will mimic human physiology and pathology and predict clinical responses more accurately than the current cellular models. The integration of these CIVMs into the drug discovery and development pipeline requires rigorous scientific validation, including cellular, morphological, and functional characterization; benchmarking of clinical biomarkers; and operationalization as robust and reproducible screening platforms. It will be critical to establish the degree of physiological complexity that is needed in each CIVM to accurately reproduce native-like homeostasis and disease phenotypes, as well as clinical pharmacological responses. Choosing which CIVM to use at each stage of the drug discovery and development pipeline will be driven by a fit-for-purpose approach, based on the specific disease pathomechanism to model and screening throughput needed. Among the different CIVMs, biofabricated tissue equivalents are emerging as robust and versatile cellular assay platforms. Biofabrication technologies, including bioprinting approaches with hydrogels and biomaterials, have enabled the production of tissues with a range of physiological complexity and controlled spatial arrangements in multiwell plate platforms, which make them amenable for medium-throughput screening. However, operationalization of such 3D biofabricated models using existing automation screening platforms comes with a unique set of challenges. These challenges will be discussed in this perspective, including examples and thoughts coming from a laboratory dedicated to designing and developing assays for automated screening.
目前，人们正在开发广泛的复杂体外模型（CIVMs），用于科学研究以及临床前药物功效和安全性测试。人们希望这些 CIVMs 能够模拟人体生理学和病理学，并比当前的细胞模型更准确地预测临床反应。将这些 CIVMs 整合到药物发现和开发管道中需要严格的科学验证，包括细胞、形态和功能特征；临床生物标志物的基准测试；以及作为强大且可重复的筛选平台的操作化。建立每个 CIVM 所需的生理复杂性程度至关重要，以便准确再现类似天然的内稳态和疾病表型以及临床药物反应。在药物发现和开发管道的每个阶段选择使用哪个 CIVM 将取决于基于要模拟的特定疾病发病机制和所需筛选通量的特定用途方法。在不同的 CIVMs 中，生物制造的组织等效物正在成为强大且多功能的细胞分析平台。生物制造技术，包括使用水凝胶和生物材料的生物打印方法，已经能够生产出具有多种生理复杂性和受控空间排列的组织，使其适用于中高通量筛选。然而，使用现有的自动化筛选平台来操作这种 3D 生物制造模型会带来一系列独特的挑战。本文将讨论这些挑战，包括来自专门设计和开发自动化筛选分析的实验室的示例和思路。
