Evidence map›Paper›PMID 42331873›Full record

ArticleScientific reports2026

Blockchain-based solution for secure and transparent pharmaceutical supply chain management using drugledger.

Debarati Dutta, Priya G

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Debarati DuttaSchool of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India.
Priya GSchool of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India. gpriya@vit.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pharmaceutical supply chain continues to face significant challenges, including the circulation of counterfeit medicines, limited traceability, and insufficient transparency among stakeholders. To address these issues, this study presents a blockchain- and IPFS-based traceability framework designed to improve the secure tracking and verification of pharmaceutical products. The proposed system combines role-based smart contracts with decentralised off-chain storage to maintain product history and enable integrity validation using unique digital identifiers. The prototype was implemented in Ethereum-compatible environments. Repeated workflow measurements were obtained in the Remix VM environment, while Sepolia was used for deployment-level validation and public testnet verification. The system demonstrated the complete workflow, including participant registration, product enrollment, manufacturing, multi-stage transfer of ownership, and authenticity verification. Analysis of the execution outputs indicates that the core operations exhibit consistent gas consumption across repeated runs, offering clear insight into computational cost and system behaviour. The findings suggest that the proposed framework can serve as a viable foundation for improving traceability in pharmaceutical supply chains at the prototype level. However, further investigation is required to assess system performance under real-world deployment conditions, particularly with respect to scalability, latency, and large-scale operational constraints.

Indexed as

BlockchainComputer SecurityDrug IndustryHumansPharmaceutical PreparationsWorkflowPharmaceutical PreparationsCounterfeit drugsDrug supply chainDrug traceabilityPharmaceutical industrySmart contracts

Identifiers

PMID42331873
PMCPMC13575097

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.