Unveiling Steady-State Multiplicity in Hybridoma Cultures: The Cybernetic Approach

Abhijit Anand Namjoshi, Wei Shou Hu, Doraiswami Ramkrishna

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Mammalian cells grown in suspension produce waste metabolites such as lactate, alanine, and ammonia, which reduce the yield of cell mass and the desired product on the nutrients supplied. Previous studies (Cruz et al., 1999; Europa et al., 2000; Follstad et al., 1999) have shown that the cells can be made to alter their metabolism by starving them on their nutrients in continuous cultures at low dilution rates or starting the culture as a fed-batch. This leads to multiple steady states in continuous reactors, with some states being more favorable than others. Mathematical models that take into account the metabolic regulation that leads to these multiple steady states are invaluable tools for bioreactor control. In this article we present a cybernetic modeling strategy in which Metabolic Flux Analysis (MFA) is used to guide the cybernetic formulation. The hybridoma model presented as a result of this strategy considers the partially substitutable, partially complementary nature of glucose and glutamine. The choice of competitions within the network is guided by MFA and the model is successful in explaining the three multiple steady states observed. The cybernetic model though identified for the hybridoma experiments of Hu and others (Europa et al., 2000) seem generally applicable to mammalian systems as it captures the pathways that are common to mammalian cells grown in suspension. The model presented here could be used for start-up strategies for continuous reactors and model-based feedback control for maintaining high productivity of the reactor.

Original languageEnglish (US)
Pages (from-to)80-91
Number of pages12
JournalBiotechnology and bioengineering
Issue number1
StatePublished - Jan 5 2003


  • Hybridoma cultures
  • Mammalian cells
  • Metabolic flux analysis, cybernetic modeling strategy
  • Multiplicity


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