Pharmaceutical Regulatory Affairs in the Era of AI and Machine Learning: Implications for Decision-Making and Compliance Processes

Artificial Intelligence (AI) and Machine Learning (ML) are transforming pharmaceutical regulatory affairs by automating the data analysis, document handling, and compliance monitoring. These technologies lower submission deadlines and compliance concerns while increasing efficiency and facilitating real-time decisionmaking. Data integrity, transparency, ethical issues, and the requirement for workforce training are some of the difficulties associated with their integration. This essay examines how AI and ML are now being used in regulatory procedures, highlighting the significance of precise rules, moral protections, and cooperation between technology and human knowledge. By tackling these issues, the pharmaceutical sector can use AI and ML to improve compliance, expedite regulatory processes, and hasten the delivery of safe and efficient treatments.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-01
DOI
https://doi.org/10.5281/zenodo.16901864
Primary Topic
Theoretical and Computational Physics
Type
article
Field-Weighted Citation Impact
0.00
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article

Pharmaceutical Regulatory Affairs in the Era of AI and Machine Learning: Implications for Decision-Making and Compliance Processes

Zenodo (CERN European Organization for Nuclear Research)
Theoretical and Computational Physics
article

Pharmaceutical Regulatory Affairs in the Era of AI and Machine Learning: Implications for Decision-Making and Compliance Processes

article en

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are transforming pharmaceutical regulatory affairs by automating the data analysis, document handling, and compliance monitoring. These technologies lower submission deadlines and compliance concerns while increasing efficiency and facilitating real-time decisionmaking. Data integrity, transparency, ethical issues, and the requirement for workforce training are some of the difficulties associated with their integration. This essay examines how AI and ML are now being used in regulatory procedures, highlighting the significance of precise rules, moral protections, and cooperation between technology and human knowledge. By tackling these issues, the pharmaceutical sector can use AI and ML to improve compliance, expedite regulatory processes, and hasten the delivery of safe and efficient treatments.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 51%
Theoretical and Computational Physics
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