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Multi-rate nonlinear state and parameter estimation in a bioreactor.

S Tatiraju1, M Soroush, R Mutharasan

  • 1Department of Chemical Engineering, Drexel University, Philadelphia, Pennsylvania 19104, USA.

Biotechnology and Bioengineering
|April 1, 1999
PubMed
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This study developed a multi-rate estimator for real-time biochemical reactor monitoring. It accurately estimates cell growth and key substances using infrequent measurements, crucial for bioprocess optimization.

Area of Science:

  • Biochemical Engineering
  • Bioprocess Monitoring
  • Cell Culture Technology

Background:

  • Real-time monitoring of biochemical reactors is essential for optimizing cell culture processes.
  • Hybridoma cell cultivation requires accurate estimation of various parameters for maximizing monoclonal antibody (MAb) production.
  • Existing estimation methods struggle with multi-rate data and time delays inherent in bioprocesses.

Purpose of the Study:

  • To design and implement a multi-rate nonlinear estimator for real-time state and parameter estimation in a pilot-scale biochemical reactor.
  • To estimate critical process variables including specific growth rate, viable and total cell concentrations, glucose, glutamine, and MAb concentrations.
  • To address challenges posed by infrequent and delayed measurements alongside high-frequency inferred data.

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Main Methods:

  • Development of a multi-rate nonlinear state and parameter estimation algorithm.
  • Implementation of the estimator in a pilot-scale biochemical reactor for mouse-mouse hybridoma cell cultivation.
  • Utilizing frequent dissolved oxygen concentration measurements to infer oxygen uptake rate (OUR).
  • Integrating infrequent and delayed measurements of cell concentrations and key metabolites.

Main Results:

  • The multi-rate estimator successfully estimated specific growth rate and concentrations of viable cells, total cells, glucose, glutamine, and MAb.
  • The estimator effectively handled infrequent (2-17 h) and delayed (0.08-2.00 h) measurements.
  • High-frequency OUR data (every 0.17 h) was accurately inferred and utilized for estimation.
  • Performance evaluation demonstrated the efficacy of the proposed multi-rate estimation strategy.

Conclusions:

  • The developed multi-rate estimator provides accurate real-time monitoring of critical parameters in biochemical reactors.
  • This approach is valuable for optimizing hybridoma cell culture and MAb production.
  • The method effectively overcomes limitations associated with multi-rate and delayed measurements in bioprocesses.