A Survey of Methods and Architectures for Blockchain and Contextual White Shark Attention Network for Drug Supply Chain Management and Recommendations in the Smart Pharmaceutical Industry

Abstract

The pharmaceutical supply chain is a vital component of global healthcare systems, ensuring the safe production, distribution, and delivery of medications. However, traditional systems face significant challenges, including counterfeit drugs, limited transparency, inefficient logistics, and poor traceability among multiple stakeholders. The integration of advanced technologies such as blockchain and artificial intelligence (AI) offers promising solutions to these issues. Blockchain provides decentralized and tamper-resistant record keeping, enabling secure tracking of drugs from manufacturing to end users and improving transparency across the supply chain. Meanwhile, AI techniques analyze large-scale healthcare data to support intelligent decision-making, optimize logistics, and generate accurate drug recommendations. This survey examines recent advancements in blockchain-enabled pharmaceutical supply chains and AI-driven recommendation frameworks, particularly those based on contextual attention networks and White Shark optimization techniques. It presents a comparative analysis of various methods, highlighting their strengths and limitations in improving efficiency and security. The study also identifies key challenges, including scalability, data integration, and system complexity, and outlines future research directions focused on developing robust, transparent, and intelligent pharmaceutical supply chain systems.