Received: 14 May 2026
Accepted: 06 August 2026
Published online: 21 August 2026
UDC: 615.1:004.8.
DOI: 10.53511/pharmkaz.2026.4.5
ARTIFICIAL INTELLIGENCE AND DIGITAL TECHNOLOGIES IN PHARMACEUTICAL SUPPLY CHAINS: A SCOPING REVIEW WITH BIBLIOMETRIC ANALYSIS
Zhalgaskali Arystanov1, Gulden Zhalbirova1*, Kateryna Zupanets2,
Zaru Kapassova1, Saule Kilibassova1, Galiya Aipova1
1NCJSC «Astana Medical University», Astana, Kazakhstan
2MEDICE Arzneimittel Pütter GmbH & Co. KG
Introduction. The rapid development of artificial intelligence (AI) and digital technologies is transforming pharmaceutical supply chains by improving transparency, traceability, operational efficiency, and decision-making processes. Technologies such as blockchain, the Internet of Things (IoT), Big Data analytics, and AI are increasingly being integrated into pharmaceutical logistics to address challenges related to drug shortages, cold chain monitoring, inventory management, and supply chain resilience.
Objective. This study aimed to analyze the current scientific landscape of AI and digital technologies in pharmaceutical supply chains and to identify major research trends, thematic areas, and existing research gaps through a scoping review combined with bibliometric analysis.
Methods. A scoping review was conducted following the PRISMA 2020 guidelines. Scientific publications indexed in Scopus, PubMed, and Web of Science databases from 2010 to 2025 were systematically searched and screened. Bibliometric analysis was performed using VOSviewer and Biblioshiny software to evaluate publication trends, keyword co-occurrence, thematic clusters, and relationships between digital technologies in pharmaceutical supply chains.
Results. A total of 80 studies were included in the final review. The bibliometric analysis demonstrated a substantial increase in publications related to digital transformation in pharmaceutical supply chains over recent years. The main thematic clusters were associated with artificial intelligence, blockchain, IoT, cold chain monitoring, traceability, and supply chain optimization. AI emerged as one of the fastest-growing research areas due to its potential for predictive analytics, demand forecasting, and operational optimization. However, the findings also revealed several barriers limiting large-scale implementation, including fragmented data systems, interoperability issues, limited real-world validation, and insufficient digital competencies among professionals.
Discussion. The findings indicate that the successful implementation of artificial intelligence requires integration with other digital technologies, the availability of reliable data, and sufficient digital competencies among pharmaceutical supply chain professionals.
Keywords. Artificial intelligence; pharmaceutical supply chains; digital technologies; blockchain; Internet of Things (IoT); pharmaceutical logistics; drug provision; cold chain; bibliometric analysis; digital transformation; traceability.
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