C. Kontoravdi, A. Mantalaris, S.P. Asprey, and E.N. Pistikopoulos (UK)
: Dynamic modelling, Biotechnology, Global sensitivity analysis.
Global sensitivity analysis (GSA) is able to quantify the importance of model parameters and their interactions with respect to model output. In this study, the Sobol' method for GSA is applied to a dynamic model of monoclonal antibody-producing mammalian cell cultures in order to identify the parameters that need to be accurately determined experimentally. The results show that most parameters have low sensitivity indices and exhibit strong interactions with one another. These parameters can be set at their nominal values and unnecessary experimentation can therefore be avoided. However, certain parameters have been identified as sensitive at specific times during culture time and could be estimated given sufficiently rich experimental data. In this regard, GSA can serve as an excellent precursor to optimal experiment design in that important parameters are identified, as well as their corresponding optimal culture times for sampling.
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