Institut für Verfahrenstechnik, Umwelttechnik und Techn. Biowissenschaften
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Mechanisitc Model description for P. chrysogenum

Process Modeling

The development of a reliable and applicable model is usually the critical step before model simulation and application show beneficial effects. We work on generic workflows for the generation of applicable models, which are made for a specific application aim and are kept as simple as necessary.

We work on:

  • Automatic model generation
  • Hybrid modelling
  • Uncertainty analysis and model validation

Model based Design of Experiments and Process Optimization

Coupled strain and process optimization

During process development we aim to run highly informative experiments. By the usage of process simulations, experiments can be planned in-silico, before lab experiments happen. Hereby we aim to decrease the number of needed experiments while increasing the information content per taken sample, by:

  • Optimization of sampling strategies
  • Model-based design of experiments
  • Multi-objective process optimization

Advanced Monitoring and Control

Real-time Model Calibration and Prediction of Product amount

As process performance is highly sensitive to deviations from optimal conditions and often lead to irreversible changes. Therefore, high efforts are invested in accurately monitor and control all influential process parameters.

We provide:

  • Soft sensors for process monitoring
  • Model-based feedback control
  • Experimental verification

Model Deployment and Digitalization

Due to the high-quality requirements of biopharmaceutical products, production processes are supervised by a growing diversity of sensors and analytical devices. To benefit from this increasing amount of information, all data sources need to be accessible and treated already during the process.

We work on:

  • interface between hard-, soft-ware and humans
  • real-time data accessibility and processing

In our novel Process Analytical Technologies (PAT) Lab new production strains and bioprocesses are analysed on a fully automized & digitalized platform

Automation

Automated sampling and offline Analysis

To facilitate process development and in-process control we try to automate reactor sampling and analysis. Hereby we are not only focused on the automation itself to guarantee robust and reliable measurements but also in the overall sampling strategies to guarantee highest information content per taken sample.