On a general model structure for macroscopic biological reaction rates.

Area of Science:

• Bioprocess Engineering
• Mathematical Modeling
• Biotechnology

Background:

• Macroscopic bioprocess modeling necessitates accurate biological reaction schemes and kinetic models.
• Selecting appropriate kinetic model structures is challenging due to limited bioprocess knowledge and numerous similar kinetic laws.
• Parameter identification is difficult due to strong non-linearities in kinetic laws, often rendering structures non-linearizable.

Purpose of the Study:

• To generalize a previously developed linearizable kinetic structure for bioprocess modeling.
• To enhance the representation of saturation effects within the kinetic model.
• To improve the biological interpretability of model parameters and facilitate systematic estimation procedures.

Main Methods:

• Generalization of a linearizable kinetic structure to incorporate improved saturation effect modeling.
• Development of an associated systematic parameter estimation procedure.
• Validation of the proposed model using both simulated and experimental bioprocess data.

Main Results:

• The generalized kinetic structure effectively represents activation/inhibition and saturation effects.
• A systematic estimation procedure was developed and associated with the proposed structure.
• The model's utility was demonstrated through successful application to simulated and experimental datasets.

Conclusions:

• The proposed generalized linearizable kinetic model offers improved saturation effect representation and parameter interpretability.
• The associated systematic estimation procedure simplifies parameter identification in bioprocess modeling.
• The model provides a valuable tool for macroscopic bioprocess modeling and analysis.