Abstract

REVIEW ON ARTIFICIAL INTELLIGENCE PARADIGM FOR DRUG DISCOVERY

Aditi Gupta, Smriti Singh Rajput, Anjali Guru, Vivek Jain*, Sunil Kumar Jain

Adina Institute of Pharmaceutical Science, NH86A, Lahdara, Sagar, MP 470001

ABSTRACT

Drug discovery can be through target identification, target verification, lead identification, and effectiveness of lead. Artificial intelligence (AI) is a simulation of the process of human intelligence through computers. The process involves obtaining information, developing rules for using information, making possible or accurate conclusions, and self-correcting. The biopharmaceutical industry 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/side effects in late trials that can be very useful in avoiding traumatic events in clinical trials. In this review, we provide an overview of current AI technologies and offer a glimpse of how AI is reimagining drug discovery by highlighting examples where AI has made a real impact. Considering the excitement and hyperbole surrounding AI in drug discovery, we present a realistic view by discussing both opportunities and challenges in adopting AI in drug discovery. The rapid growth in life sciences and machine learning algorithms has led to enormous statistical access to the growth of AI-based startups focused on drug innovation in recent years.

Keywords: Drug discovery,Artificial intelligence,Computers,Innovation.