AI: Catalyst for Drug Discovery and Development

This abstract explores the multifaceted roles of AI in expediting the drug development process. AI-driven algorithms analyze vast datasets, unraveling complex biological interactions and identifying potential drug targets with unprecedented speed and precision. In silico drug screening, powered by machine learning models, accelerates the identification of promising compounds, minimizing the time and resources traditionally required. Furthermore, AI facilitates personalized medicine by analyzing individual patient data to tailor treatments based on genetic and molecular profiles. In clinical trials, AI optimizes patient recruitment, enhances trial design, and expedites data analysis, leading to more efficient and cost-effective drug development. While the adoption of AI presents unprecedented opportunities, challenges such as data security, interpretability, and ethical considerations must be navigated. This chapter provides a comprehensive overview of the current state of AI in drug discovery, emphasizing its potential to reshape the pharmaceutical industry and improve global healthcare outcomes.