Artificial Intelligence Techniques for Blockchain and Contextual White Shark Attention Network for Drug Supply Chain Management and Recommendations in the Smart Pharmaceutical Industry: Trends and Challenges

Abstract

The pharmaceutical supply chain is essential for ensuring the safe, secure, and timely distribution of medicines, yet it faces persistent challenges such as counterfeit drugs, limited transparency, fragmented logistics, and inefficient tracking mechanisms. Emerging technologies, particularly blockchain and artificial intelligence (AI), offer effective solutions to these issues by improving security, traceability, and decision-making throughout the supply chain. Blockchain provides a decentralized and tamper-resistant platform that records drug manufacturing, transportation, storage, and distribution activities, enabling stakeholders to verify product authenticity and reduce the risk of counterfeit medicines. Simultaneously, AI techniques, including deep learning and contextual attention networks, enhance pharmaceutical analytics by identifying complex patterns in healthcare data and generating accurate drug recommendations. The integration of nature-inspired optimization methods, such as the White Shark Optimizer (WSO), further improves neural network performance through efficient parameter optimization and faster convergence. This review examines recent advancements in blockchain-enabled pharmaceutical supply chains and AI-based recommendation systems, emphasizing contextual attention networks optimized with WSO. The findings indicate that combining blockchain with intelligent attention-based models significantly enhances supply chain transparency, predictive analytics, operational efficiency, and personalized drug recommendations, while highlighting future research opportunities in scalability, security, interoperability, and explainable AI for smart pharmaceutical ecosystems.