From Bench to Bedside: How Artificial Intelligence is Reshaping Drug Discovery and Clinical Trials

“ AI is likely to be either the best or worst thing to happen to humanity.” -Elon Musk. AI has started to improve its application across different sectors, with the pharmaceutical industry gaining the most benefits, especially in drug discovery, development, and clinical trials by reducing human effort, time, and costs while increasing success rates.AI employs machine learning, deep learning, and natural language processing to analyze large datasets, enabling the rapid identification of drug targets, predicting compound efficacy, and enhancing drug design. Many drug molecules have been discovered through AI-based methods and tools, with several of these newly identified compounds already advancing to clinical trials. This review provides a comprehensive analysis of how AI is transforming the drug discovery and development field, emphasizing its contributions to target identification, virtual screening, drug design, and the optimization of clinical trials. Additionally, we have explored the major challenges and limitations that need to be addressed, such as data quality, model interpretability, regulatory hurdles, data standardization, transparency in AI model development, and the necessity for improved collaboration between AI researchers and pharmaceutical experts.