A Comprehensive Review of 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 highly complex and regulated system that requires secure drug distribution, transparency, and strict quality control. Challenges such as counterfeit medicines, inefficient tracking mechanisms, and limited visibility across supply chain stages have created serious risks for patient safety and healthcare management. To overcome these issues, advanced technologies including blockchain and artificial intelligence have emerged as effective solutions for improving security, traceability, and operational efficiency within pharmaceutical logistics. Blockchain technology enables decentralized and tamper-resistant data management, allowing secure tracking of pharmaceutical products from manufacturing to final delivery while ensuring data integrity and transparency among stakeholders. In addition to blockchain, deep learning and contextual attention-based neural networks have shown significant potential in enhancing drug recommendation systems and optimizing pharmaceutical supply chain operations. The integration of White Shark Optimizer-inspired algorithms further improves model performance through efficient optimization and intelligent feature selection. This review explores recent advancements in blockchain-enabled pharmaceutical supply chains and contextual attention network architectures for smart drug management systems. The study highlights key methodologies, existing architectures, and current research challenges related to scalability, interoperability, privacy, and computational complexity. Furthermore, it identifies future research directions for developing intelligent, secure, and efficient pharmaceutical ecosystems capable of supporting reliable drug distribution and advanced healthcare decision-making processes.