GENERATIVE AI APPLICATIONS IN DRUG DISCOVERY: ACCELERATING INNOVATION IN PHARMACEUTICALS

Authors

  • Teja Reddy Gatla Sr. Data Scientist and Research Scientist Department of Information Technology

DOI:

https://doi.org/10.26662/ijiert.v7i12.pp260-271

Keywords:

Generative AI, drug discovery, pharmaceuticals, machine learning, molecular design, drug development, AI in healthcare, therapeutic innovation, pharmaceutical research, personalized medicine.

Abstract

The pharmaceutical industry has seen a transformative shift with the integration of Generative Artificial Intelligence (AI) in drug discovery. This technology harnesses machine learning models to predict molecular properties, design new compounds, and optimize drug development processes. Generative AI has shown immense potential in accelerating the early stages of drug discovery by reducing time and cost while enhancing the precision of drug candidate identification. With the ability to generate novel molecular structures, predict protein folding, and simulate biological interactions, Generative AI is revolutionizing the discovery of effective therapeutics. This paper explores the key applications of Generative AI in pharmaceutical research, its impact on drug design, and the challenges associated with its adoption in the industry. The convergence of AI and drug discovery not only accelerates the pipeline but also promises to deliver personalized and targeted therapies, ultimately transforming the future of healthcare.

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Published

2020-12-31

Issue

Vol. 7 No. 12 (2020): IJIERT

Section

Sciences

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Copyright (c) 2024 International Journal of Innovations in Engineering Research and Technology

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