Drug design is a critical aspect of drug discovery and development, a complex, costly, and time-consuming process aimed at identifying promising drug candidates for human therapeutics. The process consists of two main stages: first, the identification of both the target and the lead molecules, and second, the more challenging step of optimizing the lead molecule to develop a candidate drug. Approaches to drug design are essential in both discovering new leads and optimizing existing ones. Traditionally, lead identification relied on natural products, understanding disease mechanisms, random screening, and human patron recognition. However, the advent of Computer-Aided Drug Design (CADD) techniques has significantly eased the challenges in drug discovery. These methods, based on ligand- and structure-based approaches, involve developing predictive models using tools like QSAR (Quantitative Structure-Activity Relationship), pharmacophores, and docking studies with CAMM (Computer-Aided Molecular Modeling Techniques). These models enable efficient virtual screening, facilitating the identification of lead molecules from vast molecular databases, including focused libraries. CADD also shows promise in repositioning existing generic drugs, which could be particularly beneficial for the Indian pharmaceutical industry. Once suitable leads are identified, they can be further optimized using CADD to address challenges encountered during preclinical and clinical trials, ultimately providing effective drug candidates and new leads. The approaches significantly shorten the timeline from the initial identification of the lead molecules to the selection of the candidate drugs and have been successfully applied in the development of neuroleptics, antihypertensive, anti- Alzheimer’s, and antitubercular agents.