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Area of Science:

  • Bioprocessing Engineering
  • Viral Mitigation Strategies
  • Chemical Reaction Engineering

Background:

  • Continuous bioprocessing requires effective viral mitigation strategies.
  • Plug flow reactors (PFRs) are utilized for continuous viral inactivation (CVI).
  • Accurate determination of minimum residence time is critical for PFR performance in CVI.

Purpose of the Study:

  • To develop and validate an empirical model for calculating minimum residence time in PFRs for CVI.
  • To assess the impact of operational conditions, specifically Dean number, on residence time distribution.
  • To refine the empirical model to remove operational constraints for broader applicability.

Main Methods:

  • Development of an initial empirical model based on reactor design and operational parameters.
  • Experimental validation using pulse injection of bacteriophage ΦX-174 in non-inactivating conditions.
  • Monitoring PFR discharge via infectivity assays to determine viral breakthrough.
  • Generation of a second, modified empirical model to eliminate Dean number constraints.

Main Results:

  • The initial empirical model accurately predicted ΦX-174 breakthrough only at Dean numbers >100.
  • The modified empirical model successfully calculated first breakthrough across all tested Dean numbers.
  • Lower Dean numbers in CVI operation resulted in increased asymmetry (tailing) of the residence time distribution.

Conclusions:

  • The refined empirical model provides a robust method for predicting viral breakthrough in PFRs for CVI.
  • Operational Dean number significantly influences residence time distribution and requires consideration for process optimization.
  • This work contributes to the development of reliable viral mitigating strategies in continuous bioprocessing.