LyoCONNECT

LyoCONNECT creates the connected product data layer for lyophilization. It brings together real-time vial-level product temperature data, sensor identity, process parameters, and visualization to build a digital twin foundation at the product and freeze-dryer levels.

For development, engineering, and technology transfer teams, this means freeze-drying is no longer interpreted solely in terms of equipment settings. LyoCONNECT makes the actual product response visible, comparable, and reusable across scales. It helps teams understand hot and cold product behavior, evaluate process margins, and build a stronger data basis for transfer decisions.

LyoCONNECT answers a fundamental question in lyophilization: how can the actual product behavior in the vial be consistently linked to process and equipment information? The traditional view of freeze-drying processes is often equipment-dominated. Shelf temperature, chamber pressure, Pirani/capacitance manometer data, and other process data describe the freeze dryer, but they do not automatically reflect the actual product temperature and drying behavior inside the vial.

LyoCONNECT closes this gap. It creates a continuous connection among real product temperature measurements, sensor position, process data, and visualization. This forms the foundation for digital twins at two levels: the product level and the freeze-dryer level.

• Product Level: Real temperature and drying profiles of individual vials become visible and comparable.
• Freeze-dryer Level: Equipment behavior, pressure control, heat transfer, and load distribution can be interpreted in the context of product behavior.
• Data Continuity: The same logic can be applied from R&D through engineering runs to technology transfer.
• Digital Twin Foundation: LyoCONNECT provides the structured data foundation on which later analysis and decision functions can build.

• Product Temperature:
  Real, vial-level temperature information during lyophilization.
  Makes visible what happens in the product – not only what the equipment is set to do.
• Sensor Identity and Position:
  Assignment of sensor ID, vial position, and process run.
  Improves traceability and supports hot- and cold-spot interpretation.
• Process Data:
  Integration of relevant equipment parameters, where available.
  Enables comparison between product response and process control.
• Visualization / TLM-3D:
  Display of temperature distribution, load behavior, and relevant process signals.
  Makes complex process states understandable for R&D, MSAT and Engineering.
• Digital Twin:
  Representation of product and equipment behavior as reusable context.
  Creates the basis for scale-up, transfer, and later process intelligence.