THE IMPACT OF AI ON DRUG DEVELOPMENT: FROM DISCOVERY TO PRODUCTION

Artificial Intelligence (AI) is rapidly transforming the pharmaceutical industry by enhancing every stage of drug development, from discovery to manufacturing and post-market surveillance. This article explores the diverse applications of AI, including machine learning, deep learning, and natural language processing, to accelerate the identification of drug targets, predict drug efficacy and safety, and optimize manufacturing processes. AI-driven technologies such as Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) are being employed to analyze medical data, design new drug compounds, and improve clinical trials, reducing costs and timeframes. Additionally, AI is helping improve regulatory submissions and post-approval surveillance, ensuring better safety monitoring and real time decision making. Despite challenges such as data standardization and regulatory hurdles, the growing impact of AI in drug development is clear. AI promises to revolutionize the pharmaceutical industry, making drug discovery more efficient, cost-effective, and personalized, ultimately leading to faster delivery of safer treatments to patients. The continued advancement and implementation of AI technologies are poised to reshape pharmaceutical research and healthcare delivery on a global scale.