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Estimation of Process Model Parameters.

Sahar Deppe1, Björn Frahm2, Volker C Hass3

  • 1Biotechnology & Bioprocess Engineering, Ostwestfalen-Lippe University of Applied Sciences and Arts, Lemgo, Germany.

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|December 21, 2019
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Summary
This summary is machine-generated.

This study presents a framework for estimating parameters in cell culture bioprocess models. This approach enhances the implementation and improvement of mathematical models for biopharmaceutical manufacturing.

Keywords:
Model implementationModelingParameter estimationProgramming

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Area of Science:

  • Biotechnology
  • Bioprocess Engineering
  • Pharmaceutical Science

Background:

  • Cell culture technology is crucial in modern biotechnology, especially for biopharmaceutical production.
  • In vitro cultivated cells are increasingly used in regenerative medicine.
  • Modeling complex, nonlinear bioprocesses is essential for optimization.

Purpose of the Study:

  • To present a framework for estimating parameters in process models.
  • To support the implementation and improvement of mathematical models in bioprocesses.
  • To verify estimated parameters and validate selected models.

Main Methods:

  • Development and implementation of a parameter estimation framework.
  • Application of the framework to a mammalian cell culture batch process model.
  • Evaluation of estimated parameters for model verification.

Main Results:

  • A functional framework for process model parameter estimation was developed.
  • The framework was successfully applied to a specific mammalian cell culture model.
  • Parameter evaluation confirmed the utility of the approach for model verification.

Conclusions:

  • The presented framework effectively supports parameter estimation in bioprocess models.
  • This methodology aids in the implementation and refinement of mathematical models for cell culture.
  • Accurate parameter estimation and evaluation are vital for reliable bioprocess modeling.