Using a chemical starting point called a "bait," Chemotype Evolution enables rapid synthesis and screening of target-focused libraries, thereby providing relevant and information-rich datasets ideally suited for machine learning. Ideas generated from machine learning are then used to design new iterations of Chemotype Evolution, creating synergistic cycles of data generation and data mining. The combination of Chemotype Evolution and machine learning allows Kimia to explore vast chemical diversity with unprecedented speed, thus improving the probability of success in the drug discovery process.