AI in Drug Discovery and Development: A Review on Current Trends and Tools.

Authors

  • Ishwar Bhikule Student Department of Pharmaceutical Chemistry, TMV’s Lokmanya Tilak Institute of Pharmaceutical Sciences, Pune, India 411037 Author
  • Prajwal Bansode Student Department of Pharmaceutical Chemistry, TMV’s Lokmanya Tilak Institute of Pharmaceutical Sciences, Pune, India 411037 Author
  • Rohan Ghige Student Department of Pharmaceutical Chemistry, TMV’s Lokmanya Tilak Institute of Pharmaceutical Sciences, Pune, India 411037 Author
  • Shraddha Dingare Assistant professor, Department of Pharmaceutical Chemistry, TMV’s Lokmanya Tilak Institute of Pharmaceutical Sciences, Pune, India 411037 Author

Keywords:

Artificial intelligence (AI), Deep learning (DL), Machine learning (ML), Natural language processing (NLP)

Abstract

AI in drug development defines as the application of artificial intelligence (AI) technologies like deep learning (DL), machine learning (ML), and natural language processing (NLP) to enhance the process drug development by discovering, designing, testing, and launching new active drug to market. AI accelerates drug development by analysing vast biological, chemical, and clinical datasets to identify potential drug candidates. AI increases newly synthesized drug safety and efficacy and reduce its toxicity. This review aims to cover an overview of current tools, technologies, and trends in AI for drug discovery and development and introduce the power of AI in a new era for drug discovery and development, accelerated research functioning, by powering new tools. Simplifying new drug discovery by explaining AI powered tools in each stage of drug development. As the field continues to evolve, ongoing collaboration between scientists, technologists, and regulatory bodies will be essential to harness these advances for the benefit of global health.

Downloads

Published

2025-05-30

Issue

Vol. 1 No. 02 (2025)

Section

Articles