Comparison of Michaelis-Menten kinetics modeling alternatives in cancer chemotherapy modeling

Model-based optimization and personalization of tumor therapies require tumor growth models that reliably describe the effect of the drug used during the therapy. A key phenomenon in the drug effect mechanism is the pharmacodynamics of the drugs which limits the maximal effect of the drug. The pharmacodynamics can be modeled with Michaelis-Menten kinetics, that can be realized in the differential equations of the model as a Hill function or bilinear functions with one extra state variable if we consider the quasi steady-state approximation or use triplet motifs, respectively. We use experimental data for a chemotherapeutic drug and carry out parametric identification of our tumor model with both Michealis-Menten kinetics models. The results show that the quasi steady-state approximation has better modeling power and less complexity.