Blockchain and Artificial Intelligence in Pharmaceutical Supply Chain Traceability: A Systematic Review

Damian Rojas A.S.; Martel Morales O.F.; Ibañez Estrella J.L.; Rueda Ñopo M.I. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/leird2025.1.1.985

Resumen

The objective of this systematic review was to analyze how Blockchain and Artificial Intelligence (AI) technologies are applied to improve traceability in the pharmaceutical supply chain, identifying their benefits and limitations. As a method, the PRISMA and PICO methodology (P(Population), I(Intervention), C(Context), O(Outcomes)) was applied to search and select articles in the Scopus, Web of Science, and IEEE Xplore databases published between 2020 and 2025. After filtering 1731 publications, 60 studies were selected for the final analysis. The results showed that the integration of Blockchain and AI significantly improves drug authentication and logistics efficiency, with neural networks reaching accuracies of up to 95% in fraud detection. However, high implementation costs, interoperability challenges with existing systems, and the need for specialized technical personnel were identified as critical barriers. It is concluded that while the combination of blockchain and artificial intelligence has enormous potential to create a more secure and transparent supply chain, its large-scale adoption is currently limited by significant economic and operational barriers, revealing a gap between theoretical feasibility and practical implementation. © LEIRD 2025.All rights reserved.

Instituciones: Universidad Tecnológica del Perú