In this chapter, the authors explore the synergistic integration of advanced machine learning techniques with bioinformatics to revolutionize drug discovery. This interdisciplinary research is jointed on the premise that combining computational power with biological data can lead to more efficient, precise, and innovative approaches to identifying new therapeutic compounds. The chapter begins by detailing the journey of drug discovery from ancient times to modern. The authors discuss the current challenges in drug discovery and delve into how machine learning algorithms can analyze vast amounts of biological data. A significant portion of the chapter is dedicated to case studies where these techniques have been successfully applied, demonstrating their potential in identifying novel drug candidates and in personalizing treatment. The authors also discuss the various regulations and guidelines that address the challenges of data heterogeneity and the need for robust and interpretable models.