A machine‐learning approach to calibrate generic Raman models for real‐time monitoring of cell culture processes-Reference-Cited by-同舟云学术

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A machine‐learning approach to calibrate generic Raman models for real‐time monitoring of cell culture processes

Published:2019-07-21 Issue:10 Volume:116 Page:2575-2586
ISSN:0006-3592
Container-title:Biotechnology and Bioengineering
language:en
Short-container-title:Biotechnology and Bioengineering

Author:

Tulsyan Aditya¹,Schorner Gregg²,Khodabandehlou Hamid³,Wang Tony³,Coufal Myra¹,Undey Cenk³

Affiliation:

1. Digital Integration & Predictive TechnologiesAmgen Inc. Cambridge Massachusetts

2. Digital Integration & Predictive TechnologiesAmgen Inc. West Greenwich Rhode Island

3. Digital Integration & Predictive TechnologiesAmgen Inc. Thousand Oaks California

Publisher

Wiley

Subject

Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bit.27100

Reference17 articles.

1. Real time monitoring of multiple parameters in mammalian cell culture bioreactors using an in-line Raman spectroscopy probe

2. Developing global regression models for metabolite concentration prediction regardless of cell line

3. Quick generation of Raman spectroscopy based in-process glucose control to influence biopharmaceutical protein product quality during mammalian cell culture

4. Applications of Raman Spectroscopy in Biopharmaceutical Manufacturing: A Short Review

5. Raman spectroscopy as a process analytical technology for pharmaceutical manufacturing and bioprocessing

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3. Single‐Use, Metabolite Absorbing, Resonant Transducer (SMART) Culture Vessels for Label‐Free, Continuous Cell Culture Progression Monitoring;Advanced Science;2024-06-20

4. Real-time model correction using Kalman filter for Raman-controlled cell culture processes;Chinese Journal of Chemical Engineering;2024-06

5. Bioprocess in‐line monitoring and control using Raman spectroscopy and Indirect Hard Modeling (IHM);Biotechnology and Bioengineering;2024-04-28

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