The SYBA model is a naïve Bayes model that classifies every ligand as ES (easy-to-synthesize) or HS (hard-tosynthesize). It assigns scores to many molecular fragments and combines them to yield the log odds for a molecule to be synthesizable. SYBA is trained on the ZINC15 database of molecules, which are assumed to be synthesizable. It uses Nonpher , a software that iteratively makes simple structural changes to a given molecule, to artificially create examples of hardto-synthesize molecules starting from these molecules. It is shown to yield molecules that are not overly complex on paper, but are hard to synthesize . SYBA was then trained to classify molecules based on these two sets of positive and negative examples.