Role of Automation, Natural Language Processing, Artificial Intelligence, and Machine Learning in hospital settings to identify and prevent Adverse Drug Reactions

  • Akanksha Togra Lokmanya Tilak Municipal Medical College and General Hospital, Sion Mumbai, India.
  • Sudhir Pawar Lokmanya Tilak Municipal Medical College and General Hospital, Sion Mumbai, India
Keywords: Pharmacovigilance, Artificial intelligence, Machine learning

Abstract

Patient Safety is at the center of all pharmacovigilance activities. As several covariates can impact the safety of a medicinal product in patients, a large amount of data is required for an accurate assessment of the safety and therefore, the benefit-risk balance of a medicinal product. Natural language processing, Artificial Intelligence, and Machine Learning are being popularly used to facilitate various pharmacovigilance activities in the Pharma industry. Artificial Intelligence and Machine learning if properly used in hospital settings can also facilitate the identification of adverse events from hospital records and discharge summaries and prescription errors, thus, alerting treating physicians regarding the same. However, the potential of using these techniques needs to be fully explored in hospital settings to facilitate the collection and evaluation of safety data.

Author Biography

Akanksha Togra, Lokmanya Tilak Municipal Medical College and General Hospital, Sion Mumbai, India.

Department of Pharmacology.

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Published
2022-09-01
How to Cite
1.
Togra A, Pawar S. Role of Automation, Natural Language Processing, Artificial Intelligence, and Machine Learning in hospital settings to identify and prevent Adverse Drug Reactions . jpadr [Internet]. 2022Sep.1 [cited 2022Sep.27];3(3):3-. Available from: https://jpadr.com/index.php/jpadr/article/view/102