Exploring the Role of Artificial Intelligence in Drug Discovery and Development

Abstract

The pharmaceutical research industry has been revolutionized by the use of Artificial Intelligence (AI) at a very rapid rate since it accelerates the development of drugs, simplifies the lead identification process, and reduces the cost of development. Traditional drug discovery procedure is tedious, costly, and lacks high clinical trial success rates. AI technologies, i.e., machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive modeling have become potent tools that are meant to defeat these limitations. Some of the applications of AI include target identification, prediction of molecular properties, virtual screening, de novo drug design, and optimization of clinical trials. The paper discusses the current applications, technology, and benefits of AI in various stages of drug discovery and development, and points out some of the successful cases of AI utilization over the last few years. It looks at the problems of data quality, model interpretability, the ethical issues, and regulations, as well. We will see why AI will transform personalized and precision medicine through the analysis of the recent progress, such as the use of AI in designing molecules through generative AI and in compounds optimization through reinforcement learning. The article recaps the conclusions that pharmaceutical research and development can be revolutionized by AI using the help of human knowledge and vast data infrastructure that will enable them to create drugs significantly quicker, safer, and cheaper.