Drug discovery and development pipelines are extensive, intricate, and contingent upon many factors ( ). ML methodologies offer a range of tools that have the potential to enhance the process of exploration and decision-making for precisely defined inquiries, utilising ample and reliable data. Machine learning (ML) can be applied at several stages of the drug discovery process. Before implementing ML approaches, it is crucial to have a profound understanding of the foundational principles of Machine Learning. Therefore, the application of ML in the various stages of drug development will be examined in the subsequent sixteen subsections.