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The proliferation of counterfeit pharmaceuticals represent a significant threat to global public health and the integrity of supply chains. Traditional anti-counterfeiting solutions remain limited by their reliance on manual verification and their deployment mainly at the final stages of the supply chain, often after counterfeit products have already reached patients, thereby undermining the reliability of both medicines and the supply chain system. To address these limitations, this paper proposes ReACT-Pharma (Real-time Anti-Counterfeit Tracking for Pharmaceuticals), an intelligent and modular framework that integrates IoT sensors, Multi-Agent Systems (MAS), Artificial Intelligence (AI) and Blockchain technology. The framework is structured into four functional layers: Real-Time Monitoring Layer, Proactive Agent Layer, Blockchain Layer and Actor Interface Layer. Each layer plays a strategic role in ensuring end-to-end data acquisition, proactive counterfeit detection, autonomous decision-making and tamper-proof event logging. Experimental evaluation demonstrates its effectiveness in real time counterfeit detection and decision reliability, offering a scalable solution for safeguarding drug authenticity.

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Multi-layered Framework for Counterfeit-Free Pharmaceutical Chains

  • 会议论文

  • 发表日期：

    2026年

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  • Abir Ghannem,
  • Hajer Nabli,
  • Raoudha Ben Djemaa,
  • Layth Sliman

摘要

The proliferation of counterfeit pharmaceuticals represent a significant threat to global public health and the integrity of supply chains. Traditional anti-counterfeiting solutions remain limited by their reliance on manual verification and their deployment mainly at the final stages of the supply chain, often after counterfeit products have already reached patients, thereby undermining the reliability of both medicines and the supply chain system. To address these limitations, this paper proposes ReACT-Pharma (Real-time Anti-Counterfeit Tracking for Pharmaceuticals), an intelligent and modular framework that integrates IoT sensors, Multi-Agent Systems (MAS), Artificial Intelligence (AI) and Blockchain technology. The framework is structured into four functional layers: Real-Time Monitoring Layer, Proactive Agent Layer, Blockchain Layer and Actor Interface Layer. Each layer plays a strategic role in ensuring end-to-end data acquisition, proactive counterfeit detection, autonomous decision-making and tamper-proof event logging. Experimental evaluation demonstrates its effectiveness in real time counterfeit detection and decision reliability, offering a scalable solution for safeguarding drug authenticity.