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    Item type:Publication, Access status: with files ,
    Analytical and numerical approaches to the analysis of progress curves: a methodological comparison
    (Elsevier, 2025-02-01)
    Waluga, Thomas
    ;
    von Ziegner, Francesca
    ;
    Skiborowski, Mirko
    Accurate models of the reaction kinetics of enzymatic reactions are essential for the design of biocatalytic processes. While many experimental studies still build on initial slope analysis, progress curve analysis offers the potential for modelling enzymatic reactions with a significantly lower experimental effort in terms of time and costs, but requires the solution of a dynamic nonlinear optimization problem. There are many different approaches for solving this problem for parameter regression, building on the experimental progress curve data. In order to provide some guidance for selecting an appropriate approach, this study presents a detailed comparison of two analytical and two numerical approaches analysing their strengths and weaknesses on the basis of three case studies. The analytical approaches build on the implicit and explicit integrals of the respective reaction rate equations, while the numerical approaches consider the direct numerical integration of the differential mass balance equations as well as the transformation of the dynamic problem to an algebraic problem by means of spline interpolation of the reaction data. In particular, the dependence of the results on the initial parameter estimates is evaluated, showcasing that the numerical solution with spline interpolation shows a lower dependence on the initial values providing parameter estimates comparable to the analytical approaches, which are however limited in applicability.
    Publicationtype: Journal Article
      47  17
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    Item type:Publication, Access status: without files ,
    Application of hybrid cybernetic model in simulating myeloma cell culture co-consuming glucose and glutamine with mixed consumption patterns
    (Elsevier, 2013-04-06)
    Geng, Jun
    ;
    Bi, Jingxiu
    ;
    Zeng, An-Ping
    ;
    Yuan, Jingqi
    A dynamic model called hybrid cybernetic model (HCM) based on structured metabolic network is established for simulating mammalian cell metabolism featured with partially substitutable and partially complementary consumption patterns of two substrates, glucose and glutamine. Benefiting from the application of elementary mode analysis (EMA), the complicated metabolic network is decomposed into elementary modes (EMs) facilitating the employment of the hybrid cybernetic framework to investigate the external and internal flux distribution and the regulation mechanism among them. According to different substrate combination, two groups of EMs are obtained, i.e., EMs associated with glucose uptake and simultaneous uptake of glucose and glutamine. Uptake fluxes through various EMs are coupled together via cybernetic variables to maximize substrate uptake. External fluxes and internal fluxes could be calculated and estimated respectively, by the combination of the stoichiometrics of metabolic networks and fluxes through regulated EMs. The model performance is well validated via three sets of experimental data. Through parameter identification of limited number of experimental data, other external metabolites are precisely predicted. The obtained kinetic parameters of three experimental cultures have similar values, which indicates the robustness of the model. Furthermore, the prediction performance of the model is successfully validated based on identified parameters.
    Publicationtype: Journal Article
      63