Abstract

AI TO ML: IMPACT ON DATA TO DISCOVERY A FOCUS ON INNOVATION, SUSTAINABILITY AND PRECISION

*Dr. Pruthviraj K. Chaudhary, Priyanshi Mishra, Dr. Dhrubo Jyoti Sen, Dr. Viral A. Prajapati and Charmi R. Patel

ABSTRACT

Artificial Intelligence (AI) is revolutionizing the fields of chemistry and drug discovery, driving efficiency, precision, and innovation. AI-powered tools leverage machine learning (ML), deep learning, and generative models to predict reaction outcomes, optimize synthetic routes, design eco-friendly processes, and accelerate molecular docking studies. In drug discovery, AI identifies and optimizes drug candidates, predicts pharmacokinetics, and aids in personalized medicine, while in green chemistry, it minimizes environmental impact and promotes sustainability. These advancements enhance experimental workflows, foster interdisciplinary collaboration, and support global challenges in healthcare, sustainability, and material science. Despite challenges in data quality and interpretability, AI's transformative potential continues to reshape chemical and pharmaceutical research, bridging computational and experimental methodologies.

Keywords: artificial intelligence, drug discovery, driving efficiency, molecular docking and precision, optimize synthetic routes, green chemistry, material science, deep learning.