A Blockchain-Based Pharmaceutical Traceability System with Neural Anomaly Detection Using Hyperledger Fabric

Asillo Mendoza J.E.; Lopez Huaman E.A.; Felix R. · International Conference on Enterprise Information Systems, ICEIS - Proceedings (2026) · DOI: 10.5220/0014577100004018

Resumen

The counterfeiting of pharmaceutical products remains a critical public health threat, with an estimated 10% of medicines in developing countries classified as substandard or falsified. These products generate severe consequences, including therapeutic failure, toxicity, antimicrobial resistance, and significant economic losses. This study proposes a decentralized web-based system that integrates a Hyperledger Fabric blockchain with deep neural network models to ensure end-to-end traceability and authenticity verification of pharmaceutical products. The system records supply-chain events through smart contracts on an immutable ledger and performs real-time anomaly detection over lifecycle data. A pilot deployment with real pharmaceutical batches was conducted to validate performance and operational feasibility. Results show a 100% verified traceability rate from laboratory to pharmacy and 93% from laboratory to end-user. The system sustained over 99.9% transaction success with confirmation latencies below 5 seconds, demonstrating a scalable, transparent, and high-performance architecture capable of mitigating adulteration risks in pharmaceutical supply chains. Copyright

Instituciones: Universidad Peruana de Ciencias Aplicadas