gxceed
← 論文一覧に戻る

Blockchain-Enabled Traceability in Pharmaceutical Supply Chains: A Mapping Review of Evidence for Visibility, Anti-Counterfeiting, and Chain-of-Custody Control

ブロックチェーンを活用した医薬品サプライチェーンのトレーサビリティ:可視性、偽造防止、およびチェーンオブカストディ管理のエビデンスに関するマッピングレビュー (AI 翻訳)

Félix Díaz, Nhell Cerna, Rafael Liza, Bryan Motta, S. Rojas-Flores

Logistics📚 査読済 / ジャーナル2026-04-10#サプライチェーンOrigin: Global
DOI: 10.3390/logistics10040085
原典: https://doi.org/10.3390/logistics10040085

🤖 gxceed AI 要約

日本語

本論文は、医薬品サプライチェーンにおけるブロックチェーンを用いたトレーサビリティのエビデンスをマッピングレビューで整理した。103件の文献を分析し、スマートコントラクトやEthereumを用いた実装、アーキテクチャ提案、文脈的成熟度のクラスターを特定。チェーンオブカストディの意味論や評価方法の不統一が比較可能性を制限していると指摘し、ベンチマーク型評価と最小限の報告基準の必要性を提言している。

English

This paper presents a mapping review of blockchain-enabled traceability in pharmaceutical supply chains, analyzing 103 records. It identifies core themes of traceability, implementation via smart contracts and Ethereum, and clusters of implemented systems, architecture proposals, and contextual evidence. The study finds that chain-of-custody semantics and evaluation methods are inconsistently formalized, limiting comparability, and calls for benchmark-oriented assessments and minimal reporting standards.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

医薬品サプライチェーンのトレーサビリティは直接的な脱炭素対策ではないが、ブロックチェーンによる可視性向上はスコープ3排出量の正確な把握や持続可能な調達に寄与する可能性があり、日本企業のESG開示やCDP対応の基盤技術として注目される。

In the global GX context

Although focused on pharmaceuticals, this paper's analysis of blockchain for traceability and chain-of-custody is relevant to broader supply chain transparency, which underpins Scope 3 accounting and sustainable procurement in global disclosure frameworks such as CDP and ISSB.

👥 読者別の含意

🔬研究者:This mapping review provides a structured overview of blockchain traceability research, highlighting gaps in evaluation standards that could inform future work.

🏢実務担当者:The findings on modular smart contract roles and governance assumptions offer practical insights for designing blockchain-based supply chain solutions.

🏛政策担当者:The call for minimal reporting standards could guide regulators in establishing interoperability and verification requirements for pharmaceutical traceability.

📄 Abstract(原文)

Background: Blockchain is increasingly proposed to strengthen pharmaceutical traceability, anti-counterfeiting, and chain of custody in multi-actor supply chains, but the evidence base remains heterogeneous in technical rigor and operational clarity. Methods: We conducted a mapping review of Scopus and Web of Science to map publication patterns, identify dominant thematic configurations, and compare citation-salient studies across recurring solution profiles and operational design dimensions. The final corpus comprised 103 records. Results: The literature expanded rapidly from 2019 to 2025, with notable geographic concentration and dissemination mainly through technically focused outlets. Keyword analysis identified a core traceability theme, an implementation stream centered on smart contracts, Ethereum, and security, and additional streams involving vaccines and regulatory or credentialing concerns. Citation-salient studies clustered into implemented systems and prototypes, architecture or framework proposals, and contextual maturity or decision-layer evidence. Across these profiles, transferability depended less on platform choice than on governance and access-control assumptions, modular smart contract roles, and verifiable on-chain/off-chain data placement. Conclusions: Chain-of-custody semantics and evaluation methods remain inconsistently formalized, limiting cross-study comparability and the interpretability of operational claims. Benchmark-oriented assessments and minimal reporting standards specifying governance parameters, logistics scope and checkpoints, workload, measurement conditions, and concrete evidence artifacts are needed.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。