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Operationalizing digital twins in biomanufacturing through interoperable process analytical technology

delete2026-07-16
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OA
AI
A
Abhijeet Satwekar *
M
M. Cyndell Gracieux-Singleton
C
Chris Cummings
J
Jonquil A. R. Horton
M
Monica Accerbi
V
Veerabhadraiah Palakollu
R
Ryan Barton
S
Sandeep Kedia
T
Thomas Cornish
K
Katharina Yandrofski
R
Roger Hart
D
Dannielle Berlinghieri
J
James Saylor
K
Kelvin H. Lee
DOI:10.1007/s00449-026-03369-9delete
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Abstract

Abstract

En 中文
The integration of Process Analytical Technologies (PAT) within digital twin architecture represents an important advancement in biopharmaceutical manufacturing. While existing literature has separately addressed digital twin dimensions, interoperability levels, and manufacturing standards, their systematic integration for real-time bioprocess control remains underexplored. Our work provides an operational framework that bridges established frameworks on digital twin dimensions with hierarchical interoperability levels. Our conceptual framework establishes an interoperability “triangle” wherein Data and Connection dimensions function as the central hub linking Physical and Virtual entities with Services to enable model-based predictive control (MPC) through PAT integration. We exemplify the practical application of our proposed approach using a galactosylation adaptive control case study that spans purpose-driven systematic technology assessment to operational deployment at the testbed. Our study provides theoretical advancement in digital twin operationalization and a practical approach for implementing MPC-enabled PAT systems in highly regulated biopharmaceutical manufacturing, with potential for applicability across multiple critical quality attributes, unit operations, and manufacturing scales.
Keywords:
Process analytical technologies
Digital twins
Interoperability
Model-based predictive control
Biomanufacturing
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Journal

Bioprocess and Biosystems Engineering cover
Bioprocess and Biosystems Engineering
IF:
3.6
Papers:
3.5K
Citations:
6.8K

Organization

I
Institute for Bioscience and Biotechnology Research
Scholars:
22
Papers: 9
Citations: 830
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