Drug traceability system based on semantic blockchain and on a reputation method

Abstract

Drug traceability is a critical process involving monitoring and validation of the origin, quality, and safety of pharmaceutical products throughout their supply chain to prevent the distribution of counterfeit, substandard, or expired drugs that could harm patients. Traditional centralized solutions for drug traceability, relying on intermediaries and central authorities, introduce risks of data manipulation, corruption, and single points of failure. This work presents the design and implementation of a novel solution for decentralized drug traceability based on blockchain technology and on a reputation mechanism that operates on top of a trustworthy decentralized knowledge base, thus integrating three core technologies: blockchain, semantic, and reputation methods. Blockchain technologies ensure transparent and secure supply chain processes while providing a trustworthy estimation of the reputation of supply chain participants. Semantic technologies address drug data heterogeneity by ensuring interoperability and creating mappings between various data sources, including verifying the identities of the various users. Additionally, the reputation mechanism promotes transparency and accountability, as stakeholders contribute feedback on drug quality, authenticity, and reliability. This fosters a culture of trust and reliability, offering the drug supply chain an effective tool for continuous improvement and informed decision-making based on aggregated feedback, ultimately enhancing overall quality and safety throughout the distribution network. The design and implementation of the system, along with several evaluations, show the feasibility of the new semantic blockchain system in real-world scenarios and the improvement of the entities with a high reputation score. Our solution is more trustworthy, discouraging fraudulent activities as security is based on the various properties included in the semantic model.