Investigating the Impact of Machine Learning in Pharmaceutical Industry

Nagaprasad, S. and Padmaja, D. L. and Qureshi, Yaser and Bangare, Sunil L. and Mishra, Manmohan and Mazumdar, Bireshwar Dass (2021) Investigating the Impact of Machine Learning in Pharmaceutical Industry. Journal of Pharmaceutical Research International, 33 (46A). pp. 6-14. ISSN 2456-9119

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Abstract

In the pharmaceutical and consumer health industries, artificial intelligence and machine learning played an important role. These technologies are critical for the identification of patients with improved intelligence applications, such as disease detection and diagnostics for clinical testing, for medicine production and predictive forecasts. In recent years, advances in numerous analysis tools and machine learning algorithms have led to novel applications for machine learning in several areas of pharmaceutical science. This paper examines the past, present, and future impacts of machine learning on several areas, including medicine design and discovery. Artificial neural networks are employed in pharmaceutical machine learning because they can reproduce nonlinear interactions typical in pharmaceutical research. AI and learning machines are examined in everyday pharmaceutical needs, industrial and regulatory insights.

Item Type: Article
Subjects: STM Library > Medical Science
Depositing User: Managing Editor
Date Deposited: 13 Mar 2023 06:28
Last Modified: 01 Feb 2024 04:07
URI: http://open.journal4submit.com/id/eprint/1628

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