International Journal Of Drug Regulatory Affairs

  • Year: 2025
  • Volume: 13
  • Issue: 2

Artificial Intelligence in Regulatory Compliance: Transforming Pharmaceutical and Healthcare Documentation

  • Author:
  • Anjaneyulu Muppalla, Beena Devi Maddi*, V Nagabhushanam Maddi
  • Total Page Count: 8
  • Page Number: 73 to 80

Department of Pharmaceutical Regulatory Affairs, Hindu College of Pharmacy, Amaravati Road, Guntur-522002, A.P.

*Corresponding author

Online published on 29 January, 2026.

Abstract

Regulatory compliance and documentation are critical components in the pharmaceutical and healthcare industries, ensuring patient safety, ethical practices, and adherence to global standards. Traditional compliance processes often involve time-consuming manual tasks prone to inefficiencies and human error. With the increasing complexity of regulations, data volume, and innovation pace, Artificial Intelligence (AI) has emerged as a transformative tool to enhance regulatory operations. This paper explores the integration of AI technologies—such as Natural Language Processing (NLP), Machine Learning (ML), and Robotic Process Automation (RPA)—into compliance workflows. Applications include automated document analysis, real-time regulatory intelligence, streamlined clinical trial documentation, EHR auditing, and adverse event detection. These technologies offer notable benefits, including improved accuracy, operational efficiency, cost reduction, and faster regulatory submissions. However, the adoption of AI also raises challenges related to data privacy, regulatory acceptance, system integration, and workforce adaptation. Ensuring transparency and maintaining ethical standards are essential for the successful deployment of AI in these high-stakes environments. Overall, AI presents a promising solution to modernize compliance frameworks, provided that its implementation is guided by robust governance and collaboration between industry stakeholders and regulators.

Keywords

Artificial Intelligence (AI), Regulatory Compliance, Pharmaceutical Industry, Healthcare Documentation, Natural Language Processing (NLP), Machine Learning (ML), Robotic Process Automation (RPA), Clinical Trials, Electronic Health Records (EHR), Data Privacy