Evidence map›Paper›PMID 40597373›Full record

ArticleJournal of biomedical semantics2025

medicX-KG: a knowledge graph for pharmacists' drug information needs.

Lizzy Farrugia, Lilian M Azzopardi, Jeremy Debattista, Charlie Abela

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lizzy FarrugiaDepartment of Artificial Intelligence, University of Malta, Msida, Malta.
Lilian M AzzopardiDepartment of Pharmacy, University of Malta, Msida, Malta.
Jeremy DebattistaDepartment of Artificial Intelligence, University of Malta, Msida, Malta.
Charlie AbelaDepartment of Artificial Intelligence, University of Malta, Msida, Malta. charlie.abela@um.edu.mt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The role of pharmacists is evolving from medicine dispensing to delivering comprehensive pharmaceutical services within multidisciplinary healthcare teams. Central to this shift is access to accurate, up-to-date medicinal product information supported by robust data integration. Leveraging artificial intelligence and semantic technologies, Knowledge Graphs (KGs) uncover hidden relationships and enable data-driven decision-making. This paper presents medicX-KG, a pharmacist-oriented knowledge graph supporting clinical and regulatory decisions. It forms the semantic layer of the broader medicX platform, powering predictive and explainable pharmacy services. medicX-KG integrates data from three sources, including, the British National Formulary (BNF), DrugBank, and the Malta Medicines Authority (MMA) that addresses Malta's regulatory landscape and combines European Medicines Agency alignment with partial UK supply dependence. The KG tackles the absence of a unified national drug repository, reducing pharmacists' reliance on fragmented sources. Its design was informed by interviews with practising pharmacists to ensure real-world applicability. We detail the KG's construction, including data extraction, ontology design, and semantic mapping. Evaluation demonstrates that medicX-KG effectively supports queries about drug availability, interactions, adverse reactions, and therapeutic classes. Limitations, including missing detailed dosage encoding and real-time updates, are discussed alongside directions for future enhancements.

Indexed as

Drug Information ServicesPharmacistsArtificial IntelligenceHumansSemanticsDrug-drug-interactionsKnowledge graphsPharmacist decision supportRegulatory information systems

Identifiers

PMID40597373
PMCPMC12211240

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.