Business Cases for Digital Twins in Biopharmaceutical Manufacturing—Market Overview, Stakeholders, Technologies in 2025 and Beyond
Abstract
Over the past years, the biopharmaceutical industry has been marked by substantial growth, with key players dominating market sales. A major change in research and development is the onset of digital twin (DT) technology in manufacturing. This work gives an overview of the market and major stakeholders, such as contract development and manufacturing organizations (CDMOs), regulatory bodies, and academia, their functions, and challenges. Fundamental concepts and definitions are reviewed and serve as an overview of the challenges ahead of the full adaptation of DTs in manufacturing. Using established market analysis tools, the environment is analyzed, and a business case is developed. Opportunities and threats for small startups and larger pharmaceutical companies to gain a competitive edge are analyzed and evaluated. Even small groups of 4–16 employees enable significant margins at a return on investment of less than 1 year.
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Mechanistic models form the foundational layer of both Digital Twins and Digital Shadows, bridging data analytics and biological interpretation.
“Mechanistic models form the foundational layer of both concepts, bridging data analytics and biological interpretation (Fig. 2) [7].”
From Mechanistic model for HEK293 viral vector processes and its application in a digital shadow framework (2026) · cites this paper as [7]
Mechanistic models, formulated from first principle mass balances, can describe the underlying biological and physicochemical phenomena governing cell growth, substrate consumption, and virus formation.
“Mechanistic models, formulated from first principle mass balances, can describe the underlying biological and physico chemical phenomena governing cell growth, substrate consumption, and virus formation [7].”
From Mechanistic model for HEK293 viral vector processes and its application in a digital shadow framework (2026) · cites this paper as [7]
Cited by
Sorted by citations
Kuchemüller, K. B., Austerjost, J., Machleid, R., Roßkamp, A., Niemann, J., & McCready, C. (2026) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-026-03362-2
- Authors
- Schmidt, A., Lütge, J., Uhl, A., Köster, D., & Strube, J.
- Affiliations
- Institute for Separation and Process Technology, Clausthal University of Technology, Leibnizstr. 15, 38678 Clausthal-Zellerfeld, Germany
- Venue
- Processes
- Publisher
- MDPI AG
- Published
- 2025-05-13
- Volume
- 13
- Issue
- 5
- Pages
- 1498
- ISSN
- 2227-9717
- Cited by
- 14
- References
- 0
- Language
- en
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