• Bandna Sharma
• Anupama Kumari
• Jyoti Sharma
• Mehak

The process of finding new drugs could be completely transformed by artificial intelligence (AI), which offers increased speed, accuracy, and efficiency. This systematic review examines how artificial intelligence (AI) is developing to address issues facing the pharmaceutical industry, with a particular emphasis on drug discovery, supply chain disruptions, clinical trials, and trial operations. Through the application of AI algorithms that examine vast amounts of biological data, such as proteomics and genomics, scientists are able to pinpoint targets linked to disease and forecast how those targets may interact with possible therapeutic candidates. The most popular artificial intelligence (AI) technologies are deep learning and neural networks; potential technologies for clinical trial design are Bayesian nonparametric models. This review highlights the advantages and disadvantages of the many AI-based techniques used in pharmaceutical technology. However, the pharmaceutical industry's ongoing exploration and investment in AI present exciting opportunities for improving patient care and drug development procedures.

Artificial intelligence (AI), Machine learning, Deep learning, Drug discovery, Disease diagnosis, Artificial Neural Network

"A review on Role of Artificial Intelligence in Pharmaceutical Industry and Drug Discovery", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.e81-e87, June-2024, Available :http://www.jetir.org/papers/JETIR2406414.pdf

"A review on Role of Artificial Intelligence in Pharmaceutical Industry and Drug Discovery", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. ppe81-e87, June-2024, Available at : http://www.jetir.org/papers/JETIR2406414.pdf