Multiple process analytical technology (PAT) tools are now being applied in tandem for cell culture. Research presented used two in-line probes, capacitance for a dynamic feeding strategy and Raman spectroscopy for real-time monitoring. Data collected from eight batches at the 15,000 L scale were used to develop process models. Raman spectroscopic data were modelled using Partial Least Squares (PLS) by two methods—(1) use of the full dataset and (2) split the dataset based on the capacitance feeding strategy. Root mean square error of prediction (RMSEP) for the first model method of capacitance was 1.54 pf/cm and the second modelling method was 1.40 pf/cm. The second Raman method demonstrated results within expected process limits for capacitance and a 0.01% difference in total nutrient feed compared to the capacitance probe. Additional variables modelled using Raman spectroscopy were viable cell density (VCD), viability, average cell diameter, and viable cell volume (VCV).

多过程分析技术（PAT）工具现在正串联应用在细胞培养中。研究提出使用两个在线探头，电容用于动态进给策略，拉曼光谱用于实时监测。从15,000升规模的8个批次中收集的数据用于开发过程模型。拉曼光谱数据使用偏最小二乘（PLS）通过两种方法建模-（1）使用完整数据集和（2）基于电容馈送策略拆分数据集。第一种电容模型方法的预测均方根误差（RMSEP）为1.54 pf / cm，第二种建模方法为1.40 pf / cm。第二种拉曼方法证明了在电容预期过程极限内的结果，与电容探针相比，总养分进料的差异为0.01％。