Abstract

Artificial Intelligence (AI) has ushered in a profound revolution within the pharmaceutical sector, effectively streamlining the processes of drug development and delivery. The application of AI-driven tools and methodologies, including machine learning and natural language processing, in the realm of pharmaceutical research and development has yielded recent breakthroughs. This accelerated the drug discovery process by meticulously scrutinizing copious data and pinpointing potential drug targets, as expounded upon in this comprehensive review. Furthermore, AI has found utility in optimizing clinical trials, thereby refining trial designs and cost-effectiveness and bolstering patient safety. Notably, AI-based strategies are being harnessed to enhance drug delivery, fostering the creation of intelligent drug delivery systems engineered to target specific cells or organs. This results in heightened efficacy and a concomitant reduction in undesirable side effects. This review also delves into the potential biases residing within AI algorithms and the challenges associated with data quality when integrating AI into the pharmaceutical sphere. The findings of this study underscore the immense potential of artificial intelligence in reshaping the pharmaceutical industry, thereby enhancing the quality of life for patients worldwide.

Keywords: Machine learning adverse event prediction, molecule design, drug development, personalized medicine, artificial intelligence, cost-effectiveness.