UID:
almahu_9949593062302882
Format:
VII, 254 p.
,
online resource.
Edition:
1st ed. 2021.
ISBN:
9783030716561
Series Statement:
Advances in Biochemical Engineering/Biotechnology, 177
Content:
This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.
Note:
Potential of model-based design of experiments approaches for bioprocess scale-down -- Digital Twins and Their Role in Model-Assisted Design of Experiments -- Digital twins for bioprocess control strategy development and realization -- The Kalman filter for the supervision of cultivation processes.-The challenge of implementing digital twins in operating value chains -- Digital twins in the (bio)pharma industry -- Numerical methods for the design and description of in vitro expansion processes of human mesenchymal stem cells -- Euler-Lagrangian Simulations: A Proper Tool for Predicting Cellular Performance in Industrial Scale Bioreactors.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030716554
Additional Edition:
Printed edition: ISBN 9783030716578
Additional Edition:
Printed edition: ISBN 9783030716585
Language:
English
DOI:
10.1007/978-3-030-71656-1
URL:
https://doi.org/10.1007/978-3-030-71656-1
Bookmarklink
