LAPSE:2024.1510
Published Article

LAPSE:2024.1510
Towards the Development of Digital Twin for Pharmaceutical Manufacturing
August 15, 2024. Originally submitted on July 9, 2024
Abstract
Pharma 4.0 has continued to advance as the industry develops advances in process analytical technologies, automation, and digit-ization. Digital twins which transform on-line process measure-ments into meaningful outputs in real-time are being developed to seize the opportunity made possible with this shift. Digital twins can be used for improved process optimization on a range of scales, from determining optimal metabolite concentrations in upstream bioreactors to considering economic and environmental impacts of process decisions. In this paper, we explore the current uses of digital twins in solid-based pharmaceutical space and the bio-pharmaceutical manufacturing. Applications cover scale up of upstream processes, product quality control, and consideration of continuous systems. We also describe the intersection of digital twins in flow sheet modeling, sensitivity analysis and optimization, and design space evaluation. Finally, areas requiring further im-provement for industry adoption are addressed.
Pharma 4.0 has continued to advance as the industry develops advances in process analytical technologies, automation, and digit-ization. Digital twins which transform on-line process measure-ments into meaningful outputs in real-time are being developed to seize the opportunity made possible with this shift. Digital twins can be used for improved process optimization on a range of scales, from determining optimal metabolite concentrations in upstream bioreactors to considering economic and environmental impacts of process decisions. In this paper, we explore the current uses of digital twins in solid-based pharmaceutical space and the bio-pharmaceutical manufacturing. Applications cover scale up of upstream processes, product quality control, and consideration of continuous systems. We also describe the intersection of digital twins in flow sheet modeling, sensitivity analysis and optimization, and design space evaluation. Finally, areas requiring further im-provement for industry adoption are addressed.
Record ID
Keywords
Biopharmaceutical manufacturing, Digital twin, Pharmaceutical manufacturing, Process Modeling
Subject
Suggested Citation
Raudenbush K, Malinov N, Reddy JV, Ding C, Tian H, Ierapetritou M. Towards the Development of Digital Twin for Pharmaceutical Manufacturing. Systems and Control Transactions 3:67-74 (2024) https://doi.org/10.69997/sct.135296
Author Affiliations
Raudenbush K: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Malinov N: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Reddy JV: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Ding C: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Tian H: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Ierapetritou M: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Malinov N: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Reddy JV: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Ding C: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Tian H: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Ierapetritou M: University of Delaware, Department of Chemical & Biomolecular Engineering, Newark, DE, USA
Journal Name
Systems and Control Transactions
Volume
3
First Page
67
Last Page
74
Year
2024
Publication Date
2024-07-10
Version Comments
DOI Assigned
Other Meta
PII: 0067-0074-680032-SCT-3-2024, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2024.1510
This Record
External Link

https://doi.org/10.69997/sct.135296
Article DOI
Download
Meta
Links to Related Works
(0.09 seconds)
[0.09 s]


