In small molecule and drug discovery research, machine learning (ML) and exploratory data analysis techniques are crucial to making screening processes more efficient and performing quantitative structure-activity relationship (QSAR) studies. Scientists investigate sets of thousands of chemical compounds and analyze their properties, similarities, and other information using cheminformatics tools. In silico experiments are already part of life science research in general and have proved their value in drug discovery and design .