Quantum Computing and Artificial Intelligence in Pharmaceutical Demand Planning: A Bibliometric Analysis

Despite growing interest in advanced analytics for healthcare logistics, the role of quantum computing and artificial intelligence (AI) in pharmaceutical demand planning remains underexplored. This study aimed to map research trends, thematic structures, and future directions through a bibliometric–systematic review of 71 Scopus-indexed articles (2013–2025). Findings reveal rapid growth since 2020, thematic convergence around machine learning, forecasting, and quantum theory, and emerging hybrid quantum–classical models linking molecular computation to supply chain operations. The study contributes by introducing the concept of Quantum–AI Demand Planning Capability, theorizing cross-scale integration mechanisms, and extending adoption frameworks to regulated healthcare contexts. Practically, it outlines hybridization strategies, governance standards, and interoperability requirements. These insights position quantum–AI integration as a transformative pathway for resilient, data-driven pharmaceutical supply chains.