Operationalizing digital twins in biomanufacturing through interoperable process analytical technology

Area of Science:

• Biopharmaceutical Manufacturing
• Process Analytical Technologies (PAT)
• Digital Twin Architecture

Background:

• Existing research addresses digital twin dimensions, interoperability, and standards separately.
• Systematic integration of these for real-time bioprocess control is underexplored.

Purpose of the Study:

• To provide an operational framework bridging digital twin dimensions and interoperability levels.
• To enable model-based predictive control (MPC) through PAT integration within digital twin architecture.

Main Methods:

• Developed a conceptual framework establishing an interoperability "triangle" (Data, Connection, Physical, Virtual, Services).
• Applied the framework to a galactosylation adaptive control case study.
• Demonstrated technology assessment to operational deployment.

Main Results:

• The framework links Physical and Virtual entities with Services via Data and Connection dimensions.
• Successfully exemplified practical application in a biopharmaceutical manufacturing case study.
• Enabled MPC through PAT integration.

Conclusions:

• Provides theoretical advancement in digital twin operationalization for bioprocesses.
• Offers a practical approach for implementing MPC-enabled PAT systems in regulated biopharmaceutical manufacturing.
• Potential applicability across various critical quality attributes, unit operations, and scales.