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

用于心肌细胞生物制造质量控制的无标记单细胞成像

• 批准号: 10675976
• 负责人: Sean P Palecek
• 金额: $ 65.08万
• 依托单位: MORGRIDGE INSTITUTE FOR RESEARCH, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10675976
• 关键词: 3-Dimensional; Adolescent; Adult; Allogenic; Arrhythmia; Autologous; Benchmarking; Biological Assay; Biomanufacturing; Bioreactors; Cardiac; Cardiac Myocytes; Cardiotoxicity; Cardiovascular Diseases; Cell Count; Cell Line; Cell Maturation; Cell Therapy; Cell physiology; Cells; Cellular Metabolic Process; Cellular Morphology; Classification; Clinical; Clinical Trials; Coenzymes; Computer Models; Data; Data Set; Development; Disease model; Early identification; Electrophysiology (science); Embryo; Failure; Fatty Acids; Flow Cytometry; Fluorescence; Generations; Glucose; Glycolysis; Goals; Healthcare; Heart Diseases; Heart failure; Heterogeneity; Human; In Vitro; Label; Marketing; Measurement; Metabolic; Metabolism; Methods; Microscopy; Modeling; Monitor; Mus; Neonatal; Optics; Pharmaceutical Preparations; Phenotype; Photons; Procedures; Process; Production; Protocols documentation; Quality Control; Research; Resolution; Structure; System; Technology; Testing; Time; Tissues; Touch sensation; Toxicity Tests; Toxicology; Withdrawal; cardiogenesis; cardiovascular health; cellular imaging; cost; drug development; human pluripotent stem cell; improved; in vivo; induced pluripotent stem cell; induced pluripotent stem cell derived cardiomyocytes; manufacture; metabolic imaging; monolayer; new technology; oxidation; predictive modeling; regenerative therapy; scale up; sex; stem cells; tool; two photon microscopy; two-photon

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.

项目摘要 /摘要 该建议的目的是开发无标签显微镜和计算模型以预测效率 与人类诱导的多能干细胞不同的发电和心肌细胞（CMS）的质量 （IPSC）改善人类心血管健康。 IPSC产生的CM正在彻底改变 通过药物开发，疾病建模，心脏毒性测试和再生治疗的心脏病。 由于IPSC可以生成自体或低免疫原性同种异体功能CM，因此我们专注于改进 面向干细胞制造的两个翻译障碍：预测IPSC-CM差异的效率 并评估IPSC-CM成熟的程度。 有效的分化和成熟是IPSC-CMS体外和体内应用的瓶颈。单身的 批次之间和之间的细胞异质性通过增加阻碍了CM制造的规模 成本和生产时间通过批处理失败。虽然旨在提高IPSC-CMS成熟度的巨大努力，但 与成年CMS相比，IPSC-CM在功能上保持不成熟，从而降低了其预测能力，并且 当用作基于细胞的治疗时，导致心律不齐。为了实现他们的研究和临床潜力， 需要单细胞工艺分析技术和模型来预测IPSC-CM分化效率 和成熟状态。预测模型提供了失败批次的早期识别以实现闭环 纠正失败批处理的过程，从而导致坚固，简化的过程。当前监视CM的方法 生物制造专注于终阶段分析，是低通量，劳动密集型和破坏性的。新的 需要在单细胞水平上预测分化并快速识别成熟态的技术 为了改善IPSC-CM生物制造并提高这些细胞的医疗保健应用。 细胞代谢的变化为IPSC-CM分化和 成熟。先前的研究，包括我们自己的研究表明，IPSC-CMS会尽早发生戏剧性的代谢变化 在分化中。鉴于这些代谢变化，我们假设无标记的无标记自动荧光显微镜 与细胞形态相结合的代谢共酶可以提供实时的早期预测 IPSC-CM分化的效率并确定生物制造过程中IPSC-CM成熟状态。我们的 初步数据表明，NAD（P）H和FAD荧光强度和寿命（光学代谢成像， 或OMI）可以在第1天的差异上预测IPSC-CM差异的效率，并且可以监视 在无触摸系统中，在3个月内CM成熟的变化。在这里，我们将构建并验证此OMI 使用IPSC-CM和体内基准的过程分析方法来创建分类模型 强大且在发展上相关，并将这些工具无缝整合到生物制造工作流程中。