Design of Experiments (DoE) techniques formalise and streamline the screening that a trained chemist would do naturally. These methods study the individual and combined effects of each factor that could affect yield, selectivity or any other variable that needs to be optimised. Factorial DoE is a commonly used method which tests combinations of each factor at predetermined levels. Factorial DoE is widely used in industry due to the simple interpretability of these methods and availability of several commercial software packages for setting up designs and analysing results. However, the number of experiments required for a full factorial DoE campagin grows exponentially with the number of factors. For example, a project examining temperature and the ratio of two reactants, each at two levels, would require four experiments, but expanding to test a library of 10 bases and 10 solvents would require 400 experiments (N = 2 2 * 10 * 10 = 400). While it is possible to conduct a small experimental design and then follow-up based on the results, the scientist has to make a decision about which variables are most important to screen first. Furthermore, factorial DoE tests continuous variables at predefined values, so optima in between these values might be missed.