Advanced Analytics Framework for Pharmacovigilance Using Azure ML and SAP HANA

Authors: Sayed Rafi Basheer

DOI: https://doi.org/10.37082/IJIRMPS.v13.i4.232633

Short DOI: https://doi.org/g9t992

Country: United States

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Abstract: This paper introduces a cloud-native analytics architecture that streamlines pharmacovigilance by automating the detection of adverse drug reactions (ADRs) and safety signals in post-market surveillance. Using Azure Machine Learning and SAP HANA, the proposed framework ingests real-world data sources such as electronic health records (EHRs), clinical notes, and social media content. It applies natural language processing (NLP) for signal detection and case prioritization. Evaluation shows a 21% improvement in signal detection precision, a 15% reduction in false positives, and a 30% decrease in regulatory reporting time.

Keywords: Pharmacovigilance, Adverse Drug Reactions (ADR), Azure Machine Learning, SAP HANA, Natural Language Processing (NLP), Real-world Data, Signal Detection, Regulatory Reporting, Clinical Analytics, Deep Learning, BERT, Post-market Surveillance

Paper Id: 232633

Published On: 2025-07-25

Published In: Volume 13, Issue 4, July-August 2025

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