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Enzymatic reaction kinetics, metabolism, experimental proﬁle mod-el ing, oxidative metabolites, computational model ing
The human metabolic network of enzymatic reactions limits the toxicity associated with the exposure to substances such as therapeutic drugs, hormones, carcinogens and vitamins. Modelling metabolism is therefore necessary for the study of drug pharmacokinetics and the assessment of the health impact of foreign and endogenous substances. In particular, predictive metabolic models may provide guidance on the required dosage of therapeutic drugs needed to reach cancerous tumors. Models of metabolic networks may be used to estimate the concentration dynamics of oxidative metabolites which is required for the development of cancer risk models. The proposed
approach to the modelling of metabolism, we call experimental proﬁle modelling, relies on a ﬁrst-order approximation of reaction kinetics with an experimentally driven estimation of its parameters. The modelling strategy is illustrated through the development of a model
of estrogen metabolism. This model is shown to yield a satisfactory
prediction of the experimental proﬁles of metabolite concentrations. However, the future availability of new experimental data and the conception of novel model parameter tuning algorithms is expected to enhance the prediction capacity of the model.