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Ranking bioprocess variables using global sensitivity analysis: a case study in centrifugation.

J M P King1, N J Titchener-Hooker, Y Zhou

  • 1The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Torrington Place, London, UK. josh.king@ucl.ac.uk

Bioprocess and Biosystems Engineering
|January 20, 2007
PubMed
Summary

Global sensitivity analysis helps optimize bioprocess design by identifying critical variables. This method reveals system-specific sensitivities, guiding engineers to focus on key parameters for improved bioprocessing efficiency.

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Area of Science:

  • Bioprocess Engineering
  • Chemical Engineering
  • Systems Biology

Background:

  • Bioprocess design involves complex interactions and numerous variables.
  • Regulatory constraints necessitate robust bioprocess design tools.
  • Conventional sensitivity analysis methods are insufficient for complex bioprocesses.

Purpose of the Study:

  • To introduce global sensitivity analysis (GSA) as a tool for bioprocess design.
  • To identify and prioritize key variables influencing bioprocess performance.
  • To demonstrate the application of GSA in optimizing operating conditions.

Main Methods:

  • Applied global sensitivity analysis (GSA) to identify critical variables.
  • Utilized two case studies based on centrifugation.

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  • Assessed performance by measuring supernatant clarification.

    • Main Results:

    • GSA effectively determined the importance of variables and their interactions.
    • Identified significant differences in variable sensitivities between case studies due to feed material properties.
    • Demonstrated that variable sensitivities are system-specific.

    Conclusions:

    • GSA provides valuable insights for bioprocess design and optimization.
    • Understanding system-specific sensitivities allows for focused optimization of operating strategies.
    • The approach aids in managing complexity and regulatory demands in bioprocessing.