Innovation in Motion

Project purpose

The need for advanced automation and self-driving supply chains become in a context where there is e.g. an increase of predictable outcomes of interventions and treatments in clinical trials and R&D settings as well as predictability of risk and risk mitigations interventions through mass data analytics and digital twinning. This will require a scale-up of knowledge and a digital-driven mindset and skillset for people working in the daily environment of the logistical chain.

Project objective(s)

Pharma.Aero is starting a project to explore the applicability of next-generation digital technologies, such as Artificial Intelligence and mass data analytics, in the air cargo industry and end-to-end supply chain of life science and MEDtech industries.

The project aims to create more insights and details of the applicability of such technologies to minimize risks and ensure quality in the shipments.

Project status and key-takeaways

The project consists of 4 Work Packages:

  • Work Package 1: Desk research (ongoing)
  • Work Package 2: Modelling predictable logistics pharma lane behaviour (ongoing)
  • Work Package 3: Industry webinar on the finding
  • Work Package 4: Publications
    – Technical Report, shared with Pharma.Aero membership only, available in the member area of our website
    White Paper, available for the entire industry

Project support and collaboration

  • Pharma.Aero Board liaison: Brussels Airport Company
  • Project leads: Changi Airport Group, Airport Authority Hong Kong
  • Project members: Cold Chase, Hive-Zox, KatalX, LainPharma, Mytigate, Pharma Air Logistics Group, SmartCAE, Validaide, MSD, Zoetis.
  • Project manager and expert: Virginia Domina, KPMG (external consultant)

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