Future of cold chain

        When it comes to supply chain management, the pharmaceutical industry is characteristically conservative compared to other key industries such as automotive, aerospace & food service. This may be due to the fact that only the basic requirements for pharmaceutical distribution have been outlined in key guidance regulations. It has become clear that actionable cold chain logistics management is vitally important to preserving the efficacy of valuable cold chain- dependent medicines and for risk mitigation. Basic requirements outlined in drugs  National List of Essential Medicines (NLEM) are under the purview of the DPCO for traceability of equipment utilized in the manufacture and storage of drug substance and drug product must be implemented and utilized in the drug distribution space.

Impact of next-gen technology

Innovative technology is already making its way into space, through next-generation shippers and data management devices that not only report on chain of custody and chain of the condition but also have the ability to interact with a user. If we look at some of the reported capabilities of one of the new tech-centric logistics start-ups, Airspace Technologies, they outline system enhancements — some of which are not readily available in the pharma supply chain space. These include the following:

• A digitally integrated, surface, and air expedited transportation network, designed for time-critical logistics.
• Automated data analysis of the fastest origin/destination routings. Taking into consideration real-time traffic conditions and an estimated 25,000 daily domestic flights.
• An internet-accessible “live” visual map interface, displaying continuous shipment status updates onboard vehicles and aircraft.
• Geofencing capabilities to provide shipment proximity notifications to alert necessary personnel

AI enters the scene

Artificial Intelligence (AI) is also becoming more routine in supply chain management. Artificial intelligence can enable exceptional agility and precision in supply chains, regardless of the industry. 

Some of the applications of AI-based supply chain management include:

• Machine learning-based algorithms that are the foundation of the next generation of logistics technologies, with the most significant gains being made with advanced resource scheduling systems.
• Machine learning that shows the potential to reduce logistics costs by finding patterns in track-and-trace data captured using IoT-enabled sensors

Intelligent packaging

    Lastly, companies are developing intelligent packaging and software solutions that leverage some of the aforementioned next-generation technology to provide better transparency, security, and accountability during transit.

    Cryoport has focused on the utilization of packaging and software technology to better understand and manage risk from untrained personnel handling equipment that is responsible for transporting patient-specific, irreplaceable material from the manufacturer to patient.