A Blockchain-Based Framework for Transparent Pharmaceutical Supply Chains: Development, Implementation and Performance Evaluation

Abstract

This study developed and evaluated a Python-based blockchain framework for improving transparency, traceability, integrity and security in pharmaceutical supply chains. A design-science and simulation-based approach was applied to 10,000 synthetic transactions covering manufacturers, distributors, retailers and customers. The framework integrated stakeholder-specific ledgers, SHA-256 hashing, block-link validation, role-based access control, batch retrieval, counterfeit detection, cold-chain monitoring and performance analysis. Results showed 100% stage-specific traceability completeness, 96.29% QR verification and 100% hash-link validity. All controlled tampering attempts and counterfeit incidents were detected, 99.68% of unauthorized access attempts were blocked, and all recorded Sybil attacks were neutralized. Among cold-chain transactions, temperature and humidity violations occurred in 5.87% and 3.67% of cases, respectively, and all environmental violations generated alerts. Mean transaction latency was 2.157 seconds, processing latency was 51.74 milliseconds, and the transaction-success rate was 96.62%. Batch retrieval averaged 0.90 milliseconds, while complete ledger validation required 78.71 milliseconds, indicating efficient record access and integrity checking within Python. The proposed PoA+FBA mechanism achieved mean CPU utilisation of 37.81%, compared with 60.99% for PBFT, representing a 38% reduction. These findings demonstrate the framework’s technical feasibility under simulated conditions, while real-world deployment requires validation using operational pharmaceutical data, multiple blockchain nodes, IoT sensors and production-grade distributed-ledger platforms.