Abstract

AI-DRIVEN DRUG DISCOVERY: OPPORTUNITIES, CHALLENGES, AND ETHICAL PERSPECTIVES

Ganesh Shivanand Shiralashetti*, Mallikarjun Poleshi, Somanath Janawad, Sakkoobayi Kumbar

ABSTRACT

Artificial Intelligence (AI) has emerged as a transformative tool in pharmaceutical sciences, reshaping how therapeutic molecules are designed, optimized, and validated. Traditional drug discovery processes are laborious, costly, and characterized by high attrition rates. In contrast, AI techniques including machine learning, deep learning, and natural language processing—enable rapid screening of molecular databases, prediction of drug–target interactions, and identification of repurposing opportunities. Despite these advances, AI integration faces challenges related to data quality, algorithmic transparency, and ethical governance. This review critically examines the evolution of AI in drug discovery, exploring technological applications, inherent challenges, and ethical perspectives shaping the future of modern therapeutics.

Keywords: Artificial Intelligence; Drug Discovery; Machine Learning; Deep Learning; Ethics; Pharmaceutical Research.