Recent Advances in AI-Powered Drug Discovery: Leveraging Machine Learning for Mechanism of Action Prediction

In an era where unprecedented speed and precision are required for drug discovery, artificial intelligence (AI) has emerged as a game changer. This chapter gives a clear summary of how AI-powered strategies are transforming the pharmaceutical sector. The investigation focuses on how AI models predict the efficacy of new therapeutic molecules and reveal their interactions with target proteins. Indeed, these breakthroughs play a critical role in lowering the time and resources required for traditional drug discovery, allowing for the rapid development of life-saving drugs. Furthermore, the impact of AI on improving clinical trials and streamlining the path from laboratory testing to patient treatment is investigated and explored. As the trip progresses through this revolutionary landscape, the chapter emphasizes major obstacles and future directions in AI-powered drug discovery, such as Mechanism of Action (MoA) prediction. It provides an introduction to the dynamic world of AI in drug development, making this cutting-edge field accessible to anyone. The study focuses on the use of machine learning methods such as Support Vector Machine (SVM) and Random Forest on a large dataset, with the goal of furthering our understanding and application of AI in drug development.