The data-driven approach to chemical discovery has been gaining relevance and importance owing to emerging public databases of chemical substances, such as PubChem , ZINC , ChemBL , and PubChemQC . These open-source databases allowed the development of several machine learning (ML) methodologies and models for the discovery of new advanced materials , the study and discovery of bioactive compounds , and the synthesis of new compounds . Therefore, DS can accelerate scientific research, including research in organic chemistry, where it can be used to analyze and make predictions on chemical reactions, structures, physical-chemical and biological properties, and big data analysis.