Automatic extraction of SmPC document for IDMP data model construction using foundation LLM and RAG: a preliminary experiment for pharmaceutical regulatory affairs

Our findings demonstrate that the proposed LLM-RAG approach enables accurate and scalable extraction of structured data from SmPCs. This supports the digital transformation of regulatory processes by promoting standardization, interoperability, and harmonization. If implemented effectively, the method could help pharmaceutical companies improve regulatory compliance, streamline submissions, and improve data consistency.

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Publication Details

Journal
Frontiers in Medicine
Published
2025-08-13
DOI
https://doi.org/10.3389/fmed.2025.1598979
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Automatic extraction of SmPC document for IDMP data model construction using foundation LLM and RAG: a preliminary experiment for pharmaceutical regulatory affairs

Alaa Awad Abdellatif, Hocine Kadi, Daniel Isaac Kemajou Njamen, Florian Pereme
Frontiers in Medicine
Biomedical Text Mining and Ontologies
article

Automatic extraction of SmPC document for IDMP data model construction using foundation LLM and RAG: a preliminary experiment for pharmaceutical regulatory affairs

Alaa Awad Abdellatif, Hocine Kadi, Daniel Isaac Kemajou Njamen, Florian Pereme
article en

Abstract

Our findings demonstrate that the proposed LLM-RAG approach enables accurate and scalable extraction of structured data from SmPCs. This supports the digital transformation of regulatory processes by promoting standardization, interoperability, and harmonization. If implemented effectively, the method could help pharmaceutical companies improve regulatory compliance, streamline submissions, and improve data consistency.

Frontiers in MedicineVol. 12
MSD (France) (FR), Quality of Life Research Center (DK)
Openalex Percentile: Top 82%
Biomedical Text Mining and Ontologies
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