Literature DB >> 29603893

Development of generic raman models for a GS-KOTM CHO platform process.

Thaddaeus A Webster1, Brian C Hadley1, William Hilliard1, Colin Jaques2, Carrie Mason1.   

Abstract

The monitoring and control of bioprocesses is of the utmost importance in order to provide a consistent, safe, and high-quality product for consumers. Current monitoring and control schemes rely on infrequent and time consuming offline sampling methods, which inherently leads to some variability in the process which may impact the product quality profile. As part of Lonza's dedication to process analytical technology (PAT) initiatives this study evaluated the ability to generate generic calibration models, which are independent of the cell line, using Raman probes to monitor changes in glucose, lactate, glutamate, ammonium, viable cell concentration (VCC), total cell concentration (TCC) and product concentration. Calibration models were developed from cell culture using two different CHOK1SV GS-KOTM cell lines producing different monoclonal antibodies (mAbs). Developed predictive models, measured changes in glucose, lactate, ammonium, VCC, and TCC with average prediction errors of 0.44, 0.23, 0.03 g L-1 , 1.90 × 106 cells mL-1 , and 1.85 × 106 cells mL-1 , respectively over the course of cell culture with minimal cell line dependence. The development of these generic models allows the application of spectroscopic PAT techniques in clinical and commercial manufacturing environments, where processes are typically run once or twice in GMP manufacturing based on a common platform process.
© 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:730-737, 2018. © 2018 American Institute of Chemical Engineers.

Entities:  

Keywords:  inline Raman spectroscopy; predictive modelling; process analytical technology

Mesh:

Substances:

Year:  2018        PMID: 29603893     DOI: 10.1002/btpr.2633

Source DB:  PubMed          Journal:  Biotechnol Prog        ISSN: 1520-6033


  3 in total

1.  Automated Data Generation for Raman Spectroscopy Calibrations in Multi-Parallel Mini Bioreactors.

Authors:  Alexander Graf; Angus Woodhams; Michael Nelson; Douglas D Richardson; Steven M Short; Mark Brower; Marek Hoehse
Journal:  Sensors (Basel)       Date:  2022-04-28       Impact factor: 3.847

Review 2.  The role of Raman spectroscopy in biopharmaceuticals from development to manufacturing.

Authors:  Karen A Esmonde-White; Maryann Cuellar; Ian R Lewis
Journal:  Anal Bioanal Chem       Date:  2021-10-20       Impact factor: 4.142

3.  Generic Chemometric Models for Metabolite Concentration Prediction Based on Raman Spectra.

Authors:  Abdolrahim Yousefi-Darani; Olivier Paquet-Durand; Almut Von Wrochem; Jens Classen; Jens Tränkle; Mario Mertens; Jeroen Snelders; Veronique Chotteau; Meeri Mäkinen; Alina Handl; Marvin Kadisch; Dietmar Lang; Patrick Dumas; Bernd Hitzmann
Journal:  Sensors (Basel)       Date:  2022-07-26       Impact factor: 3.847

  3 in total

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