Thinkcyte, K.K., 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Astellas Pharma, Inc., 5-2-3 Tokodai, Tsukuba-shi, Ibaraki, 300-2698, Japan.
Sci Rep. 2024 Sep 19;14(1):21848. doi: 10.1038/s41598-024-72016-8.
Automation and quality control (QC) are critical in manufacturing safe and effective cell and gene therapy products. However, current QC methods, reliant on molecular staining, pose difficulty in in-line testing and can increase manufacturing costs. Here we demonstrate the potential of using label-free ghost cytometry (LF-GC), a machine learning-driven, multidimensional, high-content, and high-throughput flow cytometry approach, in various stages of the cell therapy manufacturing processes. LF-GC accurately quantified cell count and viability of human peripheral blood mononuclear cells (PBMCs) and identified non-apoptotic live cells and early apoptotic/dead cells in PBMCs (ROC-AUC: area under receiver operating characteristic curve = 0.975), T cells and non-T cells in white blood cells (ROC-AUC = 0.969), activated T cells and quiescent T cells in PBMCs (ROC-AUC = 0.990), and particulate impurities in PBMCs (ROC-AUC ≧ 0.998). The results support that LF-GC is a non-destructive label-free cell analytical method that can be used to monitor cell numbers, assess viability, identify specific cell subsets or phenotypic states, and remove impurities during cell therapy manufacturing. Thus, LF-GC holds the potential to enable full automation in the manufacturing of cell therapy products with reduced cost and increased efficiency.
自动化和质量控制（QC）在制造安全有效的细胞和基因治疗产品中至关重要。然而，目前依赖分子染色的 QC 方法在在线测试方面存在困难，并且会增加制造成本。在这里，我们展示了无标记鬼细胞计数（LF-GC）在细胞治疗制造过程的各个阶段中的应用潜力。LF-GC 可准确量化人外周血单核细胞（PBMC）的细胞计数和活力，并识别 PBMC 中的非凋亡活细胞和早期凋亡/死亡细胞（ROC-AUC：接受者操作特征曲线下的面积=0.975）、白细胞中的 T 细胞和非 T 细胞（ROC-AUC=0.969）、PBMC 中的活化 T 细胞和静止 T 细胞（ROC-AUC=0.990）以及 PBMC 中的颗粒杂质（ROC-AUC≥0.998）。结果支持 LF-GC 是一种非破坏性的无标记细胞分析方法，可用于监测细胞数量、评估活力、识别特定的细胞亚群或表型状态，并在细胞治疗制造过程中去除杂质。因此，LF-GC 有可能实现细胞治疗产品制造的完全自动化，从而降低成本和提高效率。
