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 critical component of global healthcare systems, responsible for ensuring the safe production, distribution, and delivery of medications. However, traditional pharmaceutical supply chains face several challenges, including counterfeit drugs, limited transparency, inefficient logistics, and poor traceability across multiple stakeholders. The emergence of advanced digital technologies such as blockchain and artificial intelligence (AI) has created new opportunities to improve the efficiency, security, and transparency of pharmaceutical supply chains. Blockchain technology enables decentralized and tamper-proof record keeping, allowing stakeholders to securely track drug distribution from manufacturing to end users. At the same time, artificial intelligence techniques can analyze large healthcare datasets to generate intelligent drug recommendations and optimize supply chain decision-making. This survey paper reviews recent developments in blockchain-enabled pharmaceutical supply chain systems and intelligent recommendation frameworks based on contextual attention networks and White Shark optimization techniques. The study analyzes research contributions published recently, focusing on methods that combine blockchain technology with deep learning models for secure drug tracking and intelligent medication recommendation. A comparative analysis of existing methods is presented to highlight their advantages and limitations. The survey also discusses current challenges and future research directions in building smart pharmaceutical supply chain systems that integrate blockchain infrastructure with AI-based decision-support models.