A partnership between Cary-headquartered SAS and the North Carolina Collaboratory seeks to improve access to COVID-19 vaccines and reduce waste due to logistics challenges, using Internet-of-Things data.
The collaboration involves the collection of data from sensors attached to vaccine storage freezers and the analysis of that data to strengthen cold chain integrity and improve dosage delivery, particularly to underserved and rural communities.
Through the 17 institutions of the University of North Carolina System, the NC Collaboratory provided 63 cold storage freezers across the state with a total capacity of 9.3 million vaccine doses. The NC Collaboratory worked with SAS to “select, transform and operationalize data” from sensors at 10 of these locations as well as other third-party public health data, according to a 陈述.
ADDRESSING COMPLEX LOGISTICS CHALLENGES
“COVID-19 created the largest and most complex medical logistics program in modern history,” said Jeff Warren, executive director of the NC Collaboratory, which was established in 2016 by the North Carolina state legislature. “One of the most formidable challenges has been to protect supply chain integrity as vaccines are transported and stored from manufacturers to administration sites – particularly those in hard-to-reach, underserved communities.”
The partnership project gathered data, and monitored the impact of key sensor data like temperature, humidity, duration, and more, enabled the partners to make predictive insights and identify potential dosage loss. Predictive data also could potentially address the shortages of vaccines in underserved regions, a spokesperson for SAS told WRAL TechWire this week.
“With a cold supply chain, you must constantly maintain very low temperatures, as vaccines that exceed the limit begin to deteriorate in just five hours,” said Rob Handfield, executive director of North Carolina State University’s Supply Chain Resource Cooperative, and an advisor to SAS on its cold chain Internet-of-Things efforts. “The SAS approach seeks to create visibility and prediction into what is today a black box in the cold chain, helping logistics managers identify potential points of failure and proactively minimize vaccine loss.”
One of the key achievements of the project, according to SAS, is leveraging sensor data that tracks freezer capacity, providing an intelligent alert when supply is insufficient “relative to virus spread in the area.” Beyond the analysis of the data, SAS notes that the system can provide proactive recommendations for the reallocation of supply in order to meet demand.
“Our project with SAS demonstrated how IoT analytics and technologies can be a game changer in getting more vaccines to more people,” said Warren.
Another key achievement, according to SAS, came through temperature threshold monitoring. In monitoring and analyzing temperature trends that may indicate deteriorating freezer conditions, the SAS system generated alerts predicting the time remaining before a given temperature threshold is reached. That reduces or prevents vaccine waste, thereby increasing vaccine viability or maintaining supply.
“I’m proud of our university partnerships, and our focus on applying proven IoT solutions to improve critical outcomes and strengthen the cold chain,” said Jason Mann, vice president for Internet of Things at SAS, in a 陈述. “This initiative will undoubtedly accelerate the state’s ability to prepare and respond in the face of the next pandemic, variant or deployment of future mRNA vaccines.”
This was the first collaboration between SAS and the NC Collaboratory, a spokesperson for SAS confirmed to WRAL TechWire. SAS has partnered with the University of North Carolina at Chapel Hill’s Rapidly Emerging Antiviral Drug Development Initiative (READDI), however, which WRAL TechWire 之前报道过.
原文来源： WRAL 技术线