We validated the quality of our Regorafenib Monohydrate response-surface models in a second experiment in which we kept KCl concentration fixed at 90.6 mM while varying pH values and Fructose 1,6-bisphosphate concentrations in eighty mixtures according to a space-filling design. The data obtained from this experiment was compared to the activities predicted for this KCl concentration by the first model as an indicator of its predictive strength. Both datasets and the models based on them are shown together in Fig. 3. Although not completely identical, the models constructed form the two different data-sets are very similar, indicating that the interpolation from data points with different KCl concentrations provided a reasonable estimate of the activity at 90.6 mM KCl. In order to analyze the influence of substrate concentration on the pH dependence and allosteric modulation of PYK, we performed an experiment in which we tested five different PEP concentrations for each of the 17 points of a space filling design with variable pH and Fructose 1,6-bisphosphate. The different activities determined in the experiment were used to construct a Gaussian Random Process Regression surface with logarithmic scaling of the PEP and Fructose 1,6-bisphosphate axes for visualization. Fig. 4 shows the complex interaction of the variable factors. The data indicates that the pH optimum of pyruvate kinase depends on the PEP concentration with a shift toward acidic pH at low substrate concentrations. The effect was reproduced in multiple experiments, but the number of data-points spread out over the three-dimensional parameter space was not high enough to quantify the exact changes of the optimal pH-value. Combining the abstractive power and extensibility of established object oriented programming environments with existing lab-automation hardware opens up a wide range of new applications beyond Lycopene conventional high-throughput screens. It greatly reduces the amount of programming necessary for performing new variants of similar experiments and thereby increases the usefulness of automated systems for small to midscale experiments such as the development of new methods and the exploration biological system behaviour.