Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Digital Twins |
| Untertitel | Tools and Concepts for Smart Biomanufacturing |
| Herausgeber/-innen | Christoph Herwig, Ralf Pörtner, Johannes Möller |
| Seiten | 57-69 |
| Seitenumfang | 13 |
| Band | 176 |
| Auflage | 1 |
| ISBN (elektronisch) | 9783030716608 |
| Publikationsstatus | Veröffentlicht - 1 Sept. 2020 |
Publikationsreihe
| Name | Advances in biochemical engineering/biotechnology |
|---|---|
| ISSN (Print) | 0724-6145 |
Abstract
The production of pharmaceuticals, industrial chemicals, and food ingredients from biotechnological processes is a vast and rapidly growing industry. While advances in synthetic biology and metabolic engineering have made it possible to produce thousands of new molecules from cells, few of these molecules have reached the market. The traditional methods of strain and bioprocess development that transform laboratory results to industrial processes are slow and use computers and networks only for data acquisition and storage. Digitalization, machine learning (ML), and artificial intelligence (AI) methods are transforming many fields - how can they be applied to bioprocessing to overcome current bottlenecks? What are the challenges, especially for regulatory issues, in the production of biopharmaceuticals? This chapter begins with a discussion of the current challenges for strain and bioprocess development and then considers how digitalization can be used to approach these tasks in completely new ways. Finally, regulatory considerations are addressed, with the goal of incorporating these issues from the outset as new digitalization methods are created.
ASJC Scopus Sachgebiete
- Immunologie und Mikrobiologie (insg.)
- Angewandte Mikrobiologie und Biotechnologie
- Chemische Verfahrenstechnik (insg.)
- Bioengineering
- Biochemie, Genetik und Molekularbiologie (insg.)
- Biotechnologie
Zitieren
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- BibTex
- RIS
Digital Twins: Tools and Concepts for Smart Biomanufacturing. Hrsg. / Christoph Herwig; Ralf Pörtner; Johannes Möller. Band 176 1. Aufl. 2020. S. 57-69 (Advances in biochemical engineering/biotechnology).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Beitrag in Buch/Sammelwerk › Forschung › Peer-Review
}
TY - CHAP
T1 - Digitalization and Bioprocessing
T2 - Promises and Challenges
AU - Scheper, Thomas
AU - Beutel, Sascha
AU - McGuinness, Nina
AU - Heiden, Stefanie
AU - Oldiges, M.
AU - Lammers, Frank
AU - Reardon, Kenneth F.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - The production of pharmaceuticals, industrial chemicals, and food ingredients from biotechnological processes is a vast and rapidly growing industry. While advances in synthetic biology and metabolic engineering have made it possible to produce thousands of new molecules from cells, few of these molecules have reached the market. The traditional methods of strain and bioprocess development that transform laboratory results to industrial processes are slow and use computers and networks only for data acquisition and storage. Digitalization, machine learning (ML), and artificial intelligence (AI) methods are transforming many fields - how can they be applied to bioprocessing to overcome current bottlenecks? What are the challenges, especially for regulatory issues, in the production of biopharmaceuticals? This chapter begins with a discussion of the current challenges for strain and bioprocess development and then considers how digitalization can be used to approach these tasks in completely new ways. Finally, regulatory considerations are addressed, with the goal of incorporating these issues from the outset as new digitalization methods are created.
AB - The production of pharmaceuticals, industrial chemicals, and food ingredients from biotechnological processes is a vast and rapidly growing industry. While advances in synthetic biology and metabolic engineering have made it possible to produce thousands of new molecules from cells, few of these molecules have reached the market. The traditional methods of strain and bioprocess development that transform laboratory results to industrial processes are slow and use computers and networks only for data acquisition and storage. Digitalization, machine learning (ML), and artificial intelligence (AI) methods are transforming many fields - how can they be applied to bioprocessing to overcome current bottlenecks? What are the challenges, especially for regulatory issues, in the production of biopharmaceuticals? This chapter begins with a discussion of the current challenges for strain and bioprocess development and then considers how digitalization can be used to approach these tasks in completely new ways. Finally, regulatory considerations are addressed, with the goal of incorporating these issues from the outset as new digitalization methods are created.
KW - Digital twins
KW - Digitalization
KW - FDA
KW - QbD
KW - Regulatory considerations
UR - http://www.scopus.com/inward/record.url?scp=85102571922&partnerID=8YFLogxK
U2 - 10.1007/10_2020_139
DO - 10.1007/10_2020_139
M3 - Contribution to book/anthology
SN - 9783030716592
SN - 9783030716622
VL - 176
T3 - Advances in biochemical engineering/biotechnology
SP - 57
EP - 69
BT - Digital Twins
A2 - Herwig, Christoph
A2 - Pörtner, Ralf
A2 - Möller, Johannes
ER -