Nascent advanced therapies, including regenerative medicine and cell and gene therapies, rely on the production of cells in bioreactors that are highly heterogeneous in both space and time. Unfortunately, advanced therapies have failed to reach a wide patient population due to unreliable manufacturing processes that result in batch variability and cost prohibitive production. This can be attributed largely to a void in existing process analytical technologies (PATs) capable of characterizing the secreted critical quality attribute (CQA) biomolecules that correlate with the final product quality. The Dynamic Sampling Platform (DSP) is a PAT for cell bioreactor monitoring that can be coupled to a suite of sensor techniques to provide real‐time feedback on spatial and temporal CQA content in situ. In this study, DSP is coupled with electrospray ionization mass spectrometry and direct‐from‐culture sampling to obtain measures of CQA content in bulk media and the cell microenvironment throughout the entire cell culture process (≈3 weeks). Post hoc analysis of this real‐time data reveals that sampling from the microenvironment enables cell state monitoring (e.g., confluence, differentiation). These results demonstrate that an effective PAT should incorporate both spatial and temporal resolution to serve as an effective input for feedback control in biomanufacturing.

中文翻译：

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局部采样可通过在线电喷雾电离质谱法监测细胞状态

新生的先进疗法，包括再生医学以及细胞和基因疗法，都依赖于生物反应器中细胞的生产，这种生物反应器在空间和时间上都是高度异质的。不幸的是，由于不可靠的制造过程导致批次的可变性和成本过高的生产，先进的治疗未能覆盖广泛的患者群体。这在很大程度上可以归因于现有工艺分析技术（PAT）中的空白，该工艺能够表征与最终产品质量相关的分泌的关键质量属性（CQA）生物分子。动态采样平台（DSP）是用于细胞生物反应器监控的PAT，可以与一系列传感器技术结合使用，以就位和时域CQA内容提供实时反馈。在这项研究中，DSP结合电喷雾电离质谱法和直接培养后取样，可测量整个细胞培养过程（约3周）中大块培养基和细胞微环境中CQA含量。对这些实时数据的事后分析表明，从微环境中采样可以监测细胞状态（例如，融合，分化）。这些结果表明，有效的PAT应该同时包含空间和时间分辨率，以作为生物制造中反馈控制的有效输入。对这些实时数据的事后分析表明，从微环境中采样可以监测细胞状态（例如，融合，分化）。这些结果表明，有效的PAT应该同时包含空间和时间分辨率，以作为生物制造中反馈控制的有效输入。对这些实时数据的事后分析表明，从微环境中采样可以监测细胞状态（例如，融合，分化）。这些结果表明，有效的PAT应该同时包含空间和时间分辨率，以作为生物制造中反馈控制的有效输入。