APPLICATIONS OF GENERATIVE AI IN DRUG DISCOVERY AND DEVELOPMENT
Dr. B. Thangabalan, K. Sasikanth, *K. K. V. Sairam, K. Srimannarayana and T. Vineetha Ratnam
ABSTRACT
The use of Artificial Intelligence (AI) in the pharmaceutical industry has revolutionized the way companies
approach drug discovery, development, and manufacturing. From its humble beginnings in the 1980s to the current
era of deep learning and big data, AI has evolved significantly, transforming the entire process. AI has been
applied to various stages of drug development, including target identification, compound selection, virtual
screening, lead optimization, and drug design. The advantages of A I in drug discovery include increased
efficiency, improved accuracy, and enhanced customer experience. However, there are also challenges associated
with the use of AI, such as data quality, complexity of biological systems, bias in AI models, and regulato ry
challenges. Despite these challenges, AI has the potential to greatly accelerate the development of new drugs and
improve the efficiency of the process. This abstract provides an overview of the current state of AI in drug
discovery and development, its applications, advantages, and challenges, and highlights the potential of AI to
revolutionize the pharmaceutical industry.
Keywords: Artificial intelligence (AI); drug discovery, deep learning, drug development, deep learning, lead optimization, virtual screening, personalized medicine.
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