Besides the design of employed catalysts, reaction design involves the identification of optimal reaction conditions, which poses a formidable challenge due to the high dimensionality of the reaction space. In the simplest approach, ideal reaction conditions are identified by changing one parameter at a time based on the chemist's intuition. While this shows the influence of the varied parameter on the observable, interaction effects between the parameters are significantly harder to capture with this approach. Design of experiments (DoE) is a more systematic approach where parameters are varied simultaneously to unravel their effect on the outcome . Gaussian Process Regression (GPR) to optimise the flow rate, the temperature as well as the stoichiometry of the reactant for the organocatalysed synthesis of spirooxindole analogues (Figure ). In a later study the same group expanded the search space for a Brønsted acidcatalysed cross-coupling for the synthesis of biaryl compounds . They utilised Bayesian optimisation to explore a total of six numerical and categorical parameters.