Harnessing AI for Natural Drug Discovery: Integrating Big Data and AI-based Algorithms Models in Advancing Drug Discovery and Drug Development

Abstract Artificial intelligence (AI) is a branch of computer science that studies intelligent machine learning, including various advanced tools capable of mimicking human intelligence. AI plays an important role in the research field, especially in new drug discovery. AI can tackle many disciplines, including computer science, psychology, and philosophy. AI can work in various fields including science, technology and the pharmaceutical as well as natural science sector to improve efficacy and productivity. AI is now widely used in many industries and research fields because of the high-performance of computer hardware, ample storage, easily available software, and also be a cost effective. In recent years, the continuous advances in Machine learning (ML) algorithms have led to the development of Deep learning (DL) techniques with stronger capabilities in handling big data, which can further assist in identifying natural products and validation of computer-assisted lead identification. This review mainly summarized the rational application and advantages of AI based models to enhance the drug discovery process, including the Natural drug discovery and optimizing drug structures through ML/DL computational tools.