A Blockchain-AI Framework for Dynamic Inventory Management in Green Pharmaceutical Supply Chains Using Trackable Resource Units (TRUs)

Pharmaceutical supply chains face persistent challenges in ensuring product traceability, optimal inventory levels, and minimal waste, all under growing sustainability pressures. This paper proposes a novel framework integrating blockchain and artificial intelligence (AI) for dynamic inventory management in a green pharmaceutical supply chain. At the core of the framework is the concept of Trackable Resource Units (TRUs) – uniquely identified and traceable units of pharmaceutical product – which are recorded on a blockchain to enable secure, end-to-end visibility. A reinforcement learning-based AI module leverages the real-time, tamper-proof data from the blockchain to optimize inventory decisions (e.g., ordering and re-distribution) in conjunction with traditional Enterprise Resource Planning (ERP), Warehouse Management (WMS), and Supply Chain Management (SCM) systems. The integrated architecture ensures that every unit’s journey is transparent and that inventory control is adaptive to demand fluctuations and expiration constraints. To validate the proposed model, a case study is presented combining simulation experiments and approximated real-world data from industry reports. The results demonstrate improved performance over traditional inventory systems, including reduced inventory costs, significant waste reduction (due to fewer expired drugs), faster response to supply–demand changes, and lower environmental impact. This research contributes an original framework for a sustainable, intelligent pharmaceutical supply chain, illustrating how blockchain-secured traceability and AI-driven decision support can together enhance efficiency, trust, and environmental responsibility.