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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Digital Procurement in Clinical Research: Tools, Governance, and Future Trends for Vendor Management and Process Harmonisation

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  • Digital Procurement in Clinical Research: Tools, Governance, and Future Trends for Vendor Management and Process Harmonisation

Gourab Ray *

School of Computer Science, Indira Gandhi National Open University (IGNOU), New Delhi, India.

Review Article

World Journal of Advanced Research and Reviews, 2025, 28(02), 1461-1471

Article DOI: 10.30574/wjarr.2025.28.2.3857

DOI url: https://doi.org/10.30574/wjarr.2025.28.2.3857

Received 08 October 2025; revised on 15 November 2025; accepted on 18 November 2025

Procurement in clinical research is increasingly orchestrated through complex vendor ecosystems contract research organizations (CROs), central laboratories, eClinical technology providers, and specialty logistics partners whose performance directly shapes cost, cycle time, quality, and inspection readiness. Digital procurement (e‑procurement/source‑to‑pay [S2P] platforms, contract‑lifecycle management [CLM], supplier relationship and vendor performance management [SRM/VPM], robotic process automation [RPA], artificial intelligence and machine learning [AI/ML], and blockchain) promises to transform vendor management while harmonising processes across sites and geographies. We conducted a PRISMA‑guided review (2018–2025) of peer‑reviewed literature spanning supply‑chain management, information systems, operations, and healthcare journals. Twenty‑one studies met inclusion criteria. Convergent evidence shows that integrated e‑procurement/S2P and CLM/SRM/VPM suites can reduce cycle times, enhance transparency and compliance, and provide the data substrate for KPI‑driven oversight; however, value is contingent on data stewardship, integration quality, and operating‑model change. AI/ML increasingly supports supplier‑risk sensing and predictive governance; deep‑learning approaches in particular have demonstrated superior predictive accuracy in critical industries, extending the broader roles of AI identified in procurement. When RPA follows business‑process‑management (BPM)‑led redesign, quasi‑experimental evidence documents meaningful reductions in manual workload and procurement cycle time, while complementary work frames RPA as a strategic capability that must be governed and maintained to scale. Blockchain shows promise for traceability and anti‑counterfeit in healthcare and pharmaceutical supply chains, yet empirical, at‑scale deployments in clinical‑trial settings remain limited, with performance and governance challenges to overcome. A dynamic‑capabilities lens clarifies why tools alone do not harmonise processes: sensing, seizing, and reconfiguring capabilities are prerequisites for sustained impact. We conclude with a practical blueprint for clinical procurement leaders and a research agenda calling for controlled, life‑sciences‑specific outcome studies linking digital procurement to milestones such as time‑to‑site activation, first‑patient‑in, and audit findings.

Clinical Research; Procurement; E‑Procurement; Vendor Management; Process Harmonisation; AI/ML; RPA; Blockchain; Dynamic Capabilities; PRISMA

https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-3857.pdf

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Gourab Ray. Digital Procurement in Clinical Research: Tools, Governance, and Future Trends for Vendor Management and Process Harmonisation. World Journal of Advanced Research and Reviews, 2025, 28(2), 1461-1471. Article DOI: https://doi.org/10.30574/wjarr.2025.28.2.3857

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


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