From black box to clear box: explainable AI for next-gen pharmacovigilance

The EU AI Act classifies PV algorithms as 'high-risk,' imposing strict requirements for human oversight and transparency, aligning with the FDA's GMLP and India's Responsible AI principles. The review emphasizes traceability and governance, recommending convergence with human oversight into a regulatory-fit XAI framework to maximize safety signal detection and foster international trust in AI-based decision-making.

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Publication Details

Journal
Expert Opinion on Drug Safety
Published
2026-02-06
DOI
https://doi.org/10.1080/14740338.2026.2628822
Primary Topic
Pharmacovigilance and Adverse Drug Reactions
Type
article
Field-Weighted Citation Impact
0.00
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article

From black box to clear box: explainable AI for next-gen pharmacovigilance

Sanjay Sharma, Vishnu Priya, Nirmala Suryadevara
Expert Opinion on Drug Safety
Pharmacovigilance and Adverse Drug Reactions
article

From black box to clear box: explainable AI for next-gen pharmacovigilance

Sanjay Sharma, Vishnu Priya, Nirmala Suryadevara
article en

Abstract

The EU AI Act classifies PV algorithms as 'high-risk,' imposing strict requirements for human oversight and transparency, aligning with the FDA's GMLP and India's Responsible AI principles. The review emphasizes traceability and governance, recommending convergence with human oversight into a regulatory-fit XAI framework to maximize safety signal detection and foster international trust in AI-based decision-making.

Expert Opinion on Drug Safety
Narsee Monjee Institute of Management Studies (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 68%
Pharmacovigilance and Adverse Drug Reactions
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