Abstract

ROLE OF ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY AND DEVELOPMENT: A REVIEW

B.V. Chaudhari*, S. P. Jaiswal and N. A. Porwar

ABSTRACT

Artificial Intelligence (AI) uses personified knowledge and learns from the solutions it produces to address not only specific but also complex problems. Remarkable improvements in computational power coupled with advancements in AI technology could be utilized to revolutionize the drug development process. The process involves obtaining information, developing rules for using information, making possible or accurate conclusions, and self-correcting. The development of new drug residues begins when basic scientists learn about biological targets (receptor, enzyme, protein, gene). These targets involve the biological processes that occur in patients with a disease. Drug discovery can be through target verification, lead identification, and the effectiveness of lead. AI can offer revolutionary insights into medicine, through data from genetics, proteomics, and other life sciences that advance that process of discovery and development. AI has exciting potential for prosperity in the field of biopharmaceutics which makes efforts to approach AI to improve drug discovery, reduce research and development costs, reduce the time and cost of early drug discovery, and support predicting potential risks in late trials that can be very useful in avoiding traumatic events in clinical trials and ultimately clinical trials. The rapid growth in life sciences and machine learning algorithms has led to enormous statistical access to the growth of AI-based start-ups focused on drug innovation in recent years. At last, AI can improve the efficiency of the drug development process and collaboration of pharmaceutical industry giants with AI-powered drug discovery firms.

Keywords: Artificial Intelligence (AI), drug discovery, Machine learning, Deep learning, Lead.