Drug design and discovery is a complex, expensive and arduous procedure taking into account the multiple existing diseases and their variants. This long process includes the identification of potential targets and the development of therapeutically safe and effective drugs.1 Computer-aided drug design (CADD) can make it less time- and resource-consuming. In recent research, computational and statistical techniques are used in an effective way to study biomedical compounds for target identification and hit hunting. The arrival of ML in this field of study offers important enhancement in the efficacy of drug design and discovery process. The success drug design, discovery and development are in concordance with the computational methods and tools. They need to be accurate and use a reliable pre-processed data. Henceforward, Artificial Intelligence/Machine Leaning (AI) approaches to data pre-processing, modeling and representative applications in drug design and discovery will be introduced.