Browse by author
Lookup NU author(s): Ruth Rowland-Jones
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© 2018 American Institute of Chemical Engineers. The biopharmaceutical industry is moving toward a more quality by design (QbD) approach that seeks to increase product and process understanding and process control. Miniature bioreactor systems offer a high-throughput method enabling the assessment of numerous process variables in a controlled environment. However, the number of off/at-line samples that can be taken is restricted due to the small working volume of each vessel. This limitation may be resolved through the use of Raman spectroscopy due to its ability to obtain multianalyte data from small sample volumes fast. It can, however, be challenging to implement this technique for this application due to the complexity of the sample matrix and that analytes are often present in low concentration. Here, we present a design of experiments (DOE) approach to generate samples for calibrating robust multivariate predictive models measuring glucose, lactate, ammonium, viable cell concentration (VCC) and product concentration, for unclarified cell culture that improves the daily monitoring of each miniature bioreactor vessel. Furthermore, we demonstrate how the output of the glucose and VCC models can be used to control the glucose and main nutrient feed rate within miniature bioreactor cultures to within qualified critical limits set for larger scale vessels. The DOE approach used to generate the calibration sample set is shown to result in models more robust to process changes than by simply using samples taken from the “typical” process. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2740, 2019.
Author(s): Rowland-Jones RC, Jaques C
Publication type: Article
Publication status: Published
Journal: Biotechnology Progress
Year: 2019
Volume: 35
Issue: 2
Print publication date: 05/04/2019
Online publication date: 10/12/2018
Acceptance date: 29/10/2018
ISSN (print): 8756-7938
ISSN (electronic): 1520-6033
Publisher: John Wiley and Sons Inc.
URL: https://doi.org/10.1002/btpr.2740
DOI: 10.1002/btpr.2740
PubMed id: 30378770
Altmetrics provided by Altmetric
