Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning

Area of Science:

• Supply Chain Management
• Digital Health Technologies
• Public Health

Background:

• Vaccine supply chains (VSC) face persistent challenges in quality, demand forecasting, and stakeholder trust, leading to inefficiencies.
• The COVID-19 pandemic highlighted and exacerbated existing weaknesses within the VSC.
• Opportunities exist to leverage digital technologies for enhanced VSC management.

Purpose of the Study:

• To establish an intelligent VSC management system for decision support during the COVID-19 pandemic.
• To integrate blockchain, Internet of Things (IoT), and machine learning to address key VSC issues.
• To enhance transparency, ensure vaccine quality, and improve demand forecasting within the VSC.

Main Methods:

• Implementation of a blockchain-based system for transparent stakeholder interactions.
• Utilization of IoT devices for real-time monitoring of vaccine status and quality.
• Application of machine learning for predictive demand forecasting and sentiment analysis of vaccine reviews.

Main Results:

• Blockchain technology enhances trust and transparency among supply chain stakeholders.
• IoT integration ensures real-time monitoring, safeguarding vaccine quality.
• Machine learning effectively predicts demand and provides insights for quality improvement through sentiment analysis.

Conclusions:

• The developed intelligent VSC management system effectively addresses critical issues in vaccine supply chains.
• The integration of blockchain, IoT, and machine learning offers a robust solution for VSC challenges, particularly during pandemics.
• Findings have significant implications for supply chain management, business strategies, and governmental policies in the pharmaceutical sector.