1. Proceedings
  2. I3M
  3. 2024
  4. EMSS
  5. 10.46354/i3m.2024.emss.033

Emerging Technologies for Data-Driven Pharmaceutical Supply Chain Management

  • a Galina Merkuryeva , 
  • a Institute of Information Technology, Riga Technical University, Kipsalas Street 6A, Riga, LV-1048, 
Cite as
Merkuryeva G. (2024). Emerging Technologies for Data-Driven Pharmaceutical Supply Chain Management. Proceedings of the 36th European Modeling & Simulation Symposium (EMSS 2024), 033. DOI: https://doi.org/10.46354/i3m.2024.emss.033

Abstract

The main challenges faced by small and mid-sized pharmaceutical companies when implementing new digital technologies in practice are analyzed. The current state of data-driven approaches in science and emerging technologies for data-driven pharmaceutical supply chain management is discussed. The opportunities and benefits of increased collaboration in pharmaceutical supply chains, including the exchange and integration of data and management information between its participants, are considered. A real-life use case for integrated demand forecasting and purchase order generation in the pharmaceutical supply chain is described. The conceptual framework of the study is presented. A demand forecasting scenario is applied using a symbolic regression model.

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