Emerging Technologies for Data-Driven Pharmaceutical Supply Chain Management
36th European Modeling & Simulation Symposium (EMSS 2024): Proceedings
2024
Gaļina Merkurjeva
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.
Keywords
Pharmaceutical business intelligence; Data-driven technologies; Demand forecasting; Order planning; Pharmaceutical supply chain; Symbolic regression.
DOI
10.46354/i3m.2024.emss.033
Hyperlink
https://www.cal-tek.eu/proceedings/i3m/2024/emss/033/pdf.pdf
Merkuryeva, G. Emerging Technologies for Data-Driven Pharmaceutical Supply Chain Management. No: 36th European Modeling & Simulation Symposium (EMSS 2024): Proceedings, Spānija, Tenerife, 18.-20. septembris, 2024. [Rende]: CAL-TEK, 2024, Article number 033. ISSN 2724-0029. Pieejams: doi:10.46354/i3m.2024.emss.033
Publication language
English (en)