4.7 Article

Improving reliability of Raman spectroscopy for mAb production by upstream processes during bioprocess development stages

期刊

TALANTA
卷 199, 期 -, 页码 396-406

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2019.02.088

关键词

Raman spectroscopy; Upstream bioprocess monitoring; Process analytical technology; Mammalian cell culture; Local modeling; Batch conditions

向作者/读者索取更多资源

The use of Raman in Bioprocess development have shown great potential for process understanding and monitoring although there are still some challenges and limitations in performance when conditions such as clone, media or scale are changed during bioprocess development. This study proposes different strategies to balance the different information content of multiple mammalian cell cultivations produced during a bioprocess development program, when several conditions are investigated. The result is a pragmatic approach to PAT monitoring that serves both development and manufacturing stages. Combining risk-assessment techniques with two ways of developing monitoring calibrations (local or general models), we were able to obtain good predictive power from Raman spectroscopy used as PAT tool, when multiple cultivation conditions vary. As an example, the effects of process scale, base powder media and cell-line on Raman spectra are discussed and how using local models specific to some of these cultivation conditions, has a positive impact on calibration performance. It is shown how more accurate calibrations can be obtained using Clone-based local models, which requires less batches than usual approaches (up to 3-9). This study uses thirty-five cultivations of four different types of CHO cell lines, eight different clones, and four different scales - 2 L, 7 L, 15 L and 10,000 L - in two Cultivation Modes fed-batch and perfusion. The aim is to serve as blueprint to how can PAT approaches be best developed in parallel to bioprocess development.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据