Artificial Intelligence and Machine Learning in Drug Discovery

Abstract

The process of finding a medication lead starts with identifying the target of a certain disease, followed by hit identification, and lead optimization. However, the traditional approaches to drug discovery required a lot of human labor, money, and time over an extended period of time. The advancement in the technology of AI and ML techniques becomes an important part in the initial phase to the market analysis reports and tremendously accelerates the research work in the drug discovery. Moreover, AI/ML minimizes the human error as compared to the conventional methods and reduces the risk and expenditure in clinical trials. By assessing clinically pertinent data that directs the discovery of new potential targets, applications of artificial intelligence (AI) in data and chemical synthesis process are directly involved in drug development optimization. In this chapter, we described the role of the AI/ML in the drug discovery process with the application and limitations and future approaches. We anticipate that as more scientists become aware of its potential, the usage of AI/ML in the drug discovery will continue to expand in the search of new drugs.