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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要该提案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的心肌细胞（CM）的生成和质量（iPSC）改善人类心血管健康。由 iPSC 产生的 CM 正在彻底改变治疗方法通过药物开发、疾病建模、心脏毒性测试和再生治疗来治疗心脏病。由于 iPSC 可以产生自体或低免疫原性同种异体功能性 CM，因此我们专注于改进干细胞制造面临的两个转化障碍：预测 iPSC-CM 分化的效率并评估 iPSC-CM 的成熟程度。高效分化和成熟是 iPSC-CM 体外和体内应用的瓶颈。单身的批次内和批次间的细胞异质性阻碍了 CM 制造的规模化失败批次导致的成本和生产时间。虽然我们付出了巨大的努力来提高 iPSC-CM 的成熟度，与成人 CM 相比，iPSC-CM 的功能仍不成熟，降低了其体外预测能力和当用作基于细胞的疗法时会导致心律失常。为了实现他们的研究和临床潜力，新需要单细胞过程分析技术和模型来预测 iPSC-CM 分化效率和成熟状态。预测模型可以及早识别失败批次，以实现闭环纠正失败批次的流程，从而形成稳健、简化的流程。当前监测 CM 的方法生物制造专注于终阶段分析，产量低、劳动密集型且具有破坏性。新的需要能够在单细胞水平上预测分化并快速识别成熟状态的技术改善 iPSC-CM 生物制造并推进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。之前的研究（包括我们自己的研究）表明 iPSC-CM 早期会经历剧烈的代谢变化在差异化中。鉴于这些代谢变化，我们假设无标记自发荧光显微镜代谢辅酶与细胞形态相结合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 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 iPSC-CM 分化的效率，并可以监测在非接触式系统中 3 个月内 CM 成熟度的变化。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与发展相关，并将这些工具无缝集成到生物制造工作流程中。