Artificial Intelligence (AI) has emerged as a transformative force in the pharmaceutical sector, offering innovative solutions to the complex and resource-intensive process of drug discovery and development. Traditional approaches to developing new medicines are often associated with prolonged timelines, substantial financial investments, and low success rates, creating a growing demand for more efficient research strategies. AI-driven technologies, including machine learning, deep learning, natural language processing, and generative AI, are increasingly being applied to identify therapeutic targets, screen potential drug candidates, optimize lead compounds, predict toxicity, repurpose existing drugs, and improve clinical trial design. By analyzing vast volumes of biomedical, genomic, and chemical data, these technologies enable faster and more accurate decision-making, thereby enhancing research productivity and reducing development costs.

This paper examines the expanding role of AI throughout the drug discovery and development lifecycle, with particular emphasis on its applications, opportunities, and emerging challenges. It explores how AI is reshaping pharmaceutical research while critically evaluating issues related to data quality, algorithmic bias, model interpretability, ethical concerns, regulatory uncertainty, cyber-security, and intellectual property rights. The study also highlights recent advances in generative AI, precision medicine, and personalized therapeutics, which have the potential to accelerate pharmaceutical innovation and improve patient outcomes. Although AI cannot replace scientific expertise, laboratory experimentation, or regulatory evaluation, it functions as a powerful decision-support technology that complements human intelligence and strengthens research capabilities. The paper concludes that the responsible integration of AI into pharmaceutical research requires robust data governance, interdisciplinary collaboration, transparent validation practices, and adaptive regulatory frameworks. Addressing these priorities will be essential for maximizing the benefits of AI while ensuring the development of safe, effective, and accessible therapeutic solutions.