Label-free single-cell imaging for quality control of cardiomyocyte biomanufacturing

项目摘要/摘要 这项提议的目标是开发无标记显微镜和计算模型来预测效率 人诱导多能干细胞分化为心肌细胞的代次和分化质量 (IPSCs)以改善人类心血管健康。由IPSC产生的CMS正在革命性地治疗 通过药物开发、疾病建模、心脏毒性测试和再生治疗，为心脏疾病的治疗提供新的技术支持。 由于IPSCs可以产生自体或低免疫原性的同种异体、功能性CMS，我们专注于改进 干细胞制造面临的两个翻译障碍：预测IPSC-CM分化的效率 评价IPSC-CM成熟程度。 高效分化和成熟是IPSC-CMS体内外应用的瓶颈。单人 批次内和批次之间的细胞异质性阻碍了CM制造的扩大，因为 不合格批次的成本和生产时间。虽然重大努力旨在提高IPSC-CMS成熟度， 与成年CMS相比，IPSC-CMS在功能上仍然不成熟，降低了它们在体外和 当用作基于细胞的治疗时，会导致心律失常。为了实现他们的研究和临床潜力，新的 预测IPSC-CM分化效率需要单细胞过程分析技术和模型 和成熟状态。预测模型提供对不合格批次的早期识别，以实现闭环 纠正不合格批次的流程，从而实现健壮、流畅的流程。当前监控CM的方法 生物制造侧重于终端分析，是低产量、劳动密集型和破坏性的。新的 需要能够在单细胞水平上预测分化和快速识别成熟状态的技术 改进IPSC-CM的生物制造，促进这些细胞的保健应用。 细胞代谢的变化为IPSC-CM分化和分化提供了有吸引力的过程分析方法 成熟。以前的研究，包括我们自己的研究表明，IPSC-CMS在早期经历了戏剧性的代谢变化 在差异化方面。考虑到这些代谢变化，我们假设无标记自体荧光显微镜 结合细胞形态的代谢辅酶可以提供实时的早期预测 检测IPSC-CM的分化效率，鉴定IPSC-CM在生物制造过程中的成熟状态。我们的 初步数据显示，NAD(P)H和FAD荧光强度和寿命(光学代谢成像， 或OMI)可以在分化第1天预测第12天的IPSC-CM分化效率，并可以监测 在非接触系统中，CM成熟度在3个月内的变化。在这里，我们将构建并验证此OMI 使用IPSC-CMS和体内基准创建分类模型的过程分析方法 坚固且与发展相关，并将这些工具无缝地集成到生物制造工作流程中。

PROJECT SUMMARY / ABSTRACT The goal of this proposal is to develop label-free microscopy and computational models to predict the efficiency of generation and the quality of cardiomyocytes (CMs) differentiated from human induced pluripotent stem cells (iPSCs) to improve human cardiovascular health. CMs generated from iPSCs are revolutionizing treatment of heart disease through drug development, disease modeling, cardiac toxicity testing, and regenerative therapy. Since iPSCs can generate autologous or hypoimmunogenic allogeneic, functional CMs, we focus on improving two translational roadblocks facing stem cell manufacturing: predicting the efficiency of iPSC-CM differentiation and assessing the extent of iPSC-CM maturation. Efficient differentiation and maturation are bottlenecks for in vitro and in vivo applications of iPSC-CMs. Single cell heterogeneity within and between batches has impeded the scale-up of CM manufacturing by increasing cost and production times through failed batches. While significant efforts aim to improve iPSC-CMs maturity, compared to adult CMs, iPSC-CMs remain functionally immature, reducing their predictive capacity in vitro and resulting in arrhythmias when used as a cell-based therapy. To realize their research and clinical potential, new single-cell process analytic technologies and models are needed to predict iPSC-CM differentiation efficiency and maturation state. Predictive models provide early identification of failed batches to enable closed loop processes to correct failing batches, resulting in a robust, streamlined process. Current methods to monitor CM biomanufacturing focus on end-stage analytics, are low-throughput, labor-intensive, and destructive. New technologies that can predict differentiation and rapidly identify maturation state at the single cell level are needed to improve iPSC-CM biomanufacturing and advance health care applications of these cells. Changes in cell metabolism provide attractive process analytic assays for iPSC-CM differentiation and maturation. Previous studies, including our own, show that iPSC-CMs undergo dramatic metabolic changes early in differentiation. Given these metabolic changes, we hypothesize that label-free autofluorescence microscopy of metabolic co-enzymes combined with cell morphology can provide real-time early-stage prediction of the efficiency of iPSC-CM differentiation and identify iPSC-CM maturation state during biomanufacturing. Our preliminary data shows that NAD(P)H and FAD fluorescence intensities and lifetimes (optical metabolic imaging, or OMI) can predict on differentiation day 1 the efficiency of iPSC-CM differentiation at day 12, and can monitor changes in CM maturation over 3-months in a touch-free system. Here, we will build and validate this OMI process analytic approach using iPSC-CMs and in vivo benchmarks to create classification models that are robust and developmentally relevant, and seamlessly integrate these tools into the biomanufacturing workflow.