Abstract

REVIEW ON PHARMACEUTICAL APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

*Vaishnavi G. Karule, Kanchan A. Hiwe, Gayatri J. Khanderao and Jitendra A. Kubde

Abstract

To increase productivity and expedite the process of discovering novel medications, artificial intelligence (AI) is applied in drug research. Drug design, virtual screening, and target selection can all benefit from AI. Machine learning is a branch of artificial intelligence (AI) that enables machines to learn from their experiences and get better over time. It analyses data, finds trends, and makes judgements using algorithms. To evaluate data, forecast characteristics, and find possible drug candidates, artificial intelligence (AI) is utilised in the drug discovery process. Artificial Intelligence (AI) can assist increase the success rate of new pharmaceuticals, lower costs, and speed up the drug discovery. The present review discusses about the advancement of AI in pharmaceutics, development and optimization of drug design. Drug discovery is greatly aided by machine learning (ML), which analyses large datasets to predict drug properties, identify potential targets, virtually screen chemical libraries, optimise drug design, and identify potential side effects. In other words, ML improves the efficiency of drug development at all stages, from target identification to clinical trials, and essentially speeds up the process.

Keywords: Artificial intelligence, machine learning, drug discovery, ligands, lead optimization.