Abstract

A general optimization-based technique for the estimation of kinetic parameter values in dynamic models of cell metabolism is presented. A discretization strategy is used to transform continuous differential equations given in the model into an approximating set of algebraic equations. The discretized equation set is then used to constrain a non-linear optimization problem, whose solution is an optimal set of model parameter values. As a case study, we examine a simplified dynamic model of mammalian cell culture [Gao, J., Gorenflo, V. M., Scharer, J. M., & Budman, H. M. (2007). Dynamic metabolic modeling for a mab bioprocess. Biotechnology Progress, 23 (1), 168–181]. Our parameter estimation technique is shown to solve the unsimplified variant of this model, and to provide a more accurate simulation of the experimentally observed system behavior than originally reported. We are additionally able to predict physically reasonable system data even in the absence of corresponding experimental measurements, and, finally, to provide a quantitative basis for challenging certain underlying assumptions in the original model solution.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call