Pugh Phyllis C, Khanal Bijay R, Lemons Jenna L, Murillo Mario A, Patel Jacika N, Boppana Preeya K, Padmanabhan Veera
Manufacturing Sciences and Technology, Operations, Biologics Supply, AstraZeneca, Frederick, Maryland, USA.
Biochem Biophys Rep. 2025 Aug 7;43:102192. doi: 10.1016/j.bbrep.2025.102192. eCollection 2025 Sep.
Complex, chemically-undefined media components are often used as nutrients in the production of biological products via mammalian cell culture. Variability in the compositions of these complex raw materials can significantly impact product yields. This paper investigates the influence of raw material quality on the cell culture process by developing data-based models to estimate final productivity in an industrial antibody production operation at AstraZeneca. Fourier Transform Infrared (FTIR) spectroscopy measurements of selected raw material components were obtained. These measurements were processed, derivatized, and used to create Partial Least Squares (PLS) regression chemometric models. The resulting models were then employed to predict the influence of such raw variability on the yields of biotherapeutic molecules.
在通过哺乳动物细胞培养生产生物制品的过程中，复杂的、化学成分不明确的培养基成分常被用作营养物质。这些复杂原材料成分的变异性会显著影响产品产量。本文通过建立基于数据的模型来估计阿斯利康工业抗体生产操作中的最终生产率，研究了原材料质量对细胞培养过程的影响。对选定的原材料成分进行了傅里叶变换红外（FTIR）光谱测量。对这些测量数据进行处理、衍生化，并用于创建偏最小二乘（PLS）回归化学计量学模型。然后利用所得模型预测这种原材料变异性对生物治疗分子产量的影响。
