scholarly journals Advanced monitoring and control of pharmaceutical production processes with Pichia pastoris by using Raman spectroscopy and multivariate calibration methods

2017 ◽  
Vol 17 (12) ◽  
pp. 1281-1294 ◽  
Author(s):  
Jan-Patrick Voss ◽  
Nina E. Mittelheuser ◽  
Roman Lemke ◽  
Reiner Luttmann
Cellulose ◽  
2019 ◽  
Vol 27 (1) ◽  
pp. 157-170 ◽  
Author(s):  
Chamseddine Guizani ◽  
Sanna Hellstén ◽  
Joanna Witos ◽  
Herbert Sixta

Abstract We investigate in this paper the potential of Raman spectroscopy for the quantification of protic ionic liquid components (acid and base) and water, in ionic liquid/water mixtures, taking 1.5-Diazabicyclo[4.3.0]non-5-enium acetate ([DBNH][OAc]) as a case study. We show that the combination of Raman spectroscopy and chemometrics is quite successful for the quantitative analysis of the ionic liquid components and water in mixtures over wide concentration ranges. The finding of the present work suggest that Raman spectroscopy should be considered more universally for the in-line monitoring and control of processes involving ionic liquid/H2O mixtures.


2020 ◽  
Vol 47 (11) ◽  
pp. 947-964 ◽  
Author(s):  
Carina L. Gargalo ◽  
Isuru Udugama ◽  
Katrin Pontius ◽  
Pau C. Lopez ◽  
Rasmus F. Nielsen ◽  
...  

AbstractThe biomanufacturing industry has now the opportunity to upgrade its production processes to be in harmony with the latest industrial revolution. Technology creates capabilities that enable smart manufacturing while still complying with unfolding regulations. However, many biomanufacturing companies, especially in the biopharma sector, still have a long way to go to fully benefit from smart manufacturing as they first need to transition their current operations to an information-driven future. One of the most significant obstacles towards the implementation of smart biomanufacturing is the collection of large sets of relevant data. Therefore, in this work, we both summarize the advances that have been made to date with regards to the monitoring and control of bioprocesses, and highlight some of the key technologies that have the potential to contribute to gathering big data. Empowering the current biomanufacturing industry to transition to Industry 4.0 operations allows for improved productivity through information-driven automation, not only by developing infrastructure, but also by introducing more advanced monitoring and control strategies.


2007 ◽  
Vol 131 (2) ◽  
pp. S70
Author(s):  
Maria Ruottinen ◽  
Martin Kögler ◽  
Monika Bollok ◽  
Antje Neubauer ◽  
Mirja Krause ◽  
...  

2017 ◽  
Vol 16 (1) ◽  
pp. 1-18 ◽  
Author(s):  
S. Kim ◽  
J. Kim ◽  
M. K. Jeong ◽  
K. N. Al-Khalifa ◽  
A. M. S. Hamouda ◽  
...  

2014 ◽  
Vol 86 (5) ◽  
pp. 867-879 ◽  
Author(s):  
Shannon Ewanick ◽  
Elliott Schmitt ◽  
Rick Gustafson ◽  
Renata Bura

AbstractThe production of fuels and chemicals from lignocellulosic biomass demands efficient processes to compete with fossil fuel-derived products. Key biorefinery processes, such as enzymatic hydrolysis of cellulose and microbial fermentation, can be monitored by advanced sensors in real time, providing information about reactant and product concentration, contamination, and reaction progress. Spectroscopic techniques such as Raman spectroscopy provide a means of quickly and accurately assessing many types of reaction mixtures non-destructively, in real time, and with no costly sample preparation and analysis time. Raman spectroscopy techniques have been developed to accurately quantify a number of compounds present in lignocellulosic processes, and methods have been developed to overcome the presence of fluorescent compounds that can increase the spectral background. Online Raman sensors also can provide the feedback measurements necessary for advanced process controls (APCs). Specifically, model predictive control, a common APC used extensively throughout similar processing industries, is especially well suited for ensuring optimal production of bio-based chemicals from lignocellulosic material.


1991 ◽  
Vol 36 (2) ◽  
pp. 167-172 ◽  
Author(s):  
U. Brand ◽  
L. Brandes ◽  
V. Koch ◽  
T. Kullik ◽  
B. Reinhardt ◽  
...  

2015 ◽  
Vol 63 (12) ◽  
Author(s):  
Miriam Schleipen ◽  
Michael Okon ◽  
Robert Henßen ◽  
Thomas Hövelmeyer ◽  
Andreas Wagner ◽  
...  

AbstractToday modern production processes are monitored and controlled via process visualization systems. Engineering of these systems is done manually and often results in high costs and a number of errors. The purpose of the research project “PCFF” is to make a step towards “Industry 4.0” in this context and to increase flexibility of transport equipment and the corresponding software. This paper deals with the basic concept and architecture and highlights project results.


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