Drug discovery for COVID-19 and related mutations using artificial intelligence

Abstract

Researchers and scientists can transform interconnected data into valuable knowledge using computational-based models that can assist in disease diagnosis, inspection, and virus containment thanks to recent developments in the fields of artificial intelligence and machine learning. In this paper, we present a comprehensive analysis of how artificial intelligence and machine learning can contribute in the delivery of effective remedies and the fight against the COVID-19 pandemic, particularly in disease treatment and drug discovery. During the pandemic period, a large number of noteworthy studies were conducted in this direction by numerous academic and research communities from many fields. We explore the theoretical developments and practical applications of artificial intelligence algorithms and machine learning techniques that suggest potential solutions for accelerating the discovery of new drugs as well as repurposing existing ones, not only for COVID-19 but also for other related mutations and future pandemics, which unfortunately are highly predicted.