We applied the newly developed methods mentioned above on a variety of biochemical systems and present a few examples of how it can be used to collect the data for solving diverse scientific problems. We used the system for optimizing buffer mixtures of assays for determining the activity of several glycolytic enzymes. By automatically testing systematic variations of the known standard-protocols, we were able to determine buffer mixtures that substantially increase the activity of the enzymes of interest when compared to the protocols commonly found in literature. One of the glycolytic enzymes, pyruvate kinase, was Fosfomycin calcium investigated in more detail. After an initial experiment in which we investigated the interplay of multiple different modulators of enzyme activity, we became interested in the pH dependence of enzymatic activity. We acquired data for a model of pH dependence of enzyme activity, determined its parameters by nonlinear regression and compared its predictions with our measurement results. In a setting where quantitative experimental parameters have to be varied in order to achieve an optimization goal that can be expressed in a single number, numerical methods allow to get Topiramate closer to an optimal set of parameters in a systematic manner. Numerical optimization methods typically treat the relation between input parameters and experimental outcome as a black box function that satisfies a few general criteria like smoothness. Therefore, they can be applied even when no valid mathematical model of the process under investigation is known. In order to demonstrate how our framework can be used to find optimal reaction conditions for enzymatic assays in an automated iterative procedure, we performed an optimization of pH, KCl and Fructose-1,6-bisphosphate concentrations for maximum PYK activity in five rounds of experiments. In the first round, we measured the activity of the enzyme in 20 different mixtures that were chosen according to a space filling experimental design that covered the complete allowed concentration/pH range of all three variable components.