Once the descriptor library was ready, the next step in the workflow was the use of an algorithm to divide the dataset into training and testing sets, as the more diverse the data the model is trained on, the more likely it is to be transferable to new data points. The training set, termed a universal training set (UTS), represents the variability of the chemical space of the full library. With a library of 1,075 unique reactions consisting of 43 chiral phosphoric acids, 5 thiol nucleophiles, and The last representative example we shall discuss in this sub-section was described by our research group during the validation of VIRTUAL CHEMIST. In this example, we replicated in silico the excellent experimental study by Gerosa et al. that aimed to identify selective chiral pyrrolidines as organocatalysts for the Diels-Alder cycloaddition. In this report, 22 catalysts were synthesized and tested for their ability to catalyze the Diels-Alder cycloaddition between (E)-cinnamaldehyde and cyclopentadiene. The preparation of these potential levoglucosenone-derived organocatalysts required complex synthesis, separation, and characterization of stereoisomers. We developed a workflow using the modular workflow interface in VIRTUAL CHEMIST to simulate the entire process including the 1) parallel synthesis of a small library (ca. 500+) of these organocatalysts, including the ones tested by Gerosa et al. and 2) evaluation of the induced stereoselectivities. We demonstrated that VIRTUAL CHEMIST not only reproduced the process successfully within just a few days, but accurately identified the most stereoselective catalysts determined experimentally.