Applying Logistic and Monod models in a single equations system framework for cell culture growth modeling and estimation

In modeling cell culture growth, two types of modeling equations are normally used: logistic and Monod. These two equations are known for their strengths and weaknesses in modeling cell culture growth. In this contribution, we show how these equations can be used in a single equations system framework to model cell culture growth that is supported by experimental observation. Specifically, we propose that logistic equation is used to model the dynamic of total cells growth that is simply the summation of viable and dead cells populations in the system. Subsequently, Monod equation is used to model the dynamic of viable cells growth that is subjected to growth-limiting substrate and cells death rate term. With this paradigm, a rate equation can be written for the accumulation of dead cells in the system with a simple understanding that dead cells population is simply the difference between total and viable cells. These equations can be adjoined with appropriate substrate consumption and product generation rate equations to depict a complete time course profiles of batch culture experiment. This modeling framework has been fitted successfully to depict a batch growth data of IgG-secreting murine hybridoma cell from published literature.