Multistep Modelling and Monitoring of Bioprocesses

A new approach is proposed for modelling and monitoring bioprocesses dynamics characterized by different metabolic states. Bioprocesses cannot be described by a single model. For this reason, three phases characterised by the bioprocess are defined – periodic, exponential, and stationary. During each phase, the process passes through one or more physiological states. Each physiological state is described by a sub-model with a different structure and parameter values. The transition of the process from one physiological state to another is carried out by switching the sub-models based on a predefined key parameter. Monitoring is performed by a cascade of software sensors using the sub-models and real-time measurement of the concentrations of the main process variables. The proposed approach was tested by modelling and monitoring the Escherichia coli phytase production process.

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Publication Details

Journal
International Journal Bioautomation
Published
2024-12-01
DOI
https://doi.org/10.7546/ijba.2024.28.4.001033
Primary Topic
Viral Infectious Diseases and Gene Expression in Insects
Type
article
Field-Weighted Citation Impact
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article

Multistep Modelling and Monitoring of Bioprocesses

Olympia Roeva, Velislava Lyubenova, Maya Ignatova, Denitsa Kristeva
International Journal Bioautomation
Viral Infectious Diseases and Gene Expression in Insects
article

Multistep Modelling and Monitoring of Bioprocesses

Olympia Roeva, Velislava Lyubenova, Maya Ignatova, Denitsa Kristeva
article en

Abstract

A new approach is proposed for modelling and monitoring bioprocesses dynamics characterized by different metabolic states. Bioprocesses cannot be described by a single model. For this reason, three phases characterised by the bioprocess are defined – periodic, exponential, and stationary. During each phase, the process passes through one or more physiological states. Each physiological state is described by a sub-model with a different structure and parameter values. The transition of the process from one physiological state to another is carried out by switching the sub-models based on a predefined key parameter. Monitoring is performed by a cascade of software sensors using the sub-models and real-time measurement of the concentrations of the main process variables. The proposed approach was tested by modelling and monitoring the Escherichia coli phytase production process.

International Journal BioautomationVol. 28(4)
Openalex Percentile: Top 79%
Viral Infectious Diseases and Gene Expression in Insects
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