Design of experiments for the automated development of a multicellular cardiac model for high-throughput screening

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Kavita Raniga , William Stebbeds , Arun Shivalingam , Michelle Pemberton , Chris Denning
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引用次数: 0

Abstract

Cardiovascular toxicity remains a major cause of drug attrition in early drug development, clinical trials, and post-market surveillance. In vitro assessment of cardiovascular liabilities often relies on single cell type-based model systems coupled with functional assays, like calcium flux and multielectrode arrays. Although these models offer high-throughput capabilities and demonstrate good predictivity for functional cardiotoxicities, they fail to consider the vital contribution of non-myocyte cells, thus limiting the potential for integrated risk assessment. Complex 3D hPSC-derived multicellular cardiac model systems have been growing in popularity; however, many of these models are limited to low-throughput with lengthy development timelines and high costs, which hampers their suitability to drug discovery.

To optimize the development of an in vitro multicellular model system containing human-induced pluripotent stem-cell derived cardiomyocytes, endothelial cells and cardiac fibroblasts, we employed the Synthace platform, which enables scientists to express complex experimental intent in a simple format (e.g. Design of Experiments) and to translate this to automation protocols using no-code. Utilizing this approach, we systematically screened the impact of multiple cell culture parameters, including the co-culture of three cell types, on cardiac contractility, with minimal hands-on time. Our platform accelerates the assay development process, providing users with an efficient means to explore and optimize the experimental space for the development of multicellular models. This is particularly valuable in scenarios involving variable biological responses and limited understanding of underling mechanisms. Moreover, users can make better use of resources, streamline their workflows, and drive data-driven decision-making throughout the assay development journey.

设计用于高通量筛选的多细胞心脏模型自动开发实验
在早期药物开发、临床试验和上市后监测过程中,心血管毒性仍然是导致药物减产的一个主要原因。心血管毒性的体外评估通常依赖于基于单细胞类型的模型系统和功能检测,如钙通量和多电极阵列。虽然这些模型具有高通量能力,并能很好地预测功能性心脏毒性,但它们没有考虑到非肌细胞的重要贡献,从而限制了综合风险评估的潜力。复杂的三维 hPSC 衍生多细胞心脏模型系统越来越受欢迎;然而,这些模型中的许多仅限于低通量,开发时间长、成本高,这阻碍了它们在药物发现方面的适用性。为了优化包含人类诱导多能干细胞衍生的心肌细胞、内皮细胞和心脏成纤维细胞的体外多细胞模型系统的开发,我们采用了 Synthace 平台,该平台使科学家能够以简单的格式(如实验设计)表达复杂的实验意图,并使用无代码将其转化为自动化协议。利用这种方法,我们系统地筛选了多种细胞培养参数(包括三种细胞类型的共培养)对心脏收缩力的影响,而且只需极少的动手时间。我们的平台加快了检测开发过程,为用户提供了探索和优化多细胞模型开发实验空间的有效手段。这在涉及多变生物反应和对基本机制了解有限的情况下尤为重要。此外,用户还可以更好地利用资源,简化工作流程,并在整个测定开发过程中推动数据驱动决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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