DESCRIPTION

One of the world’s largest pharmaceutical companies is extending deployment of the MaxTrace™ predictive cloud engine following the successful completion of an 8-week proof-of-value initiative in October 2021. This was phase 1 of a multi-phase collaboration with MaxQ, the specialist cold-chain packaging, predictive intelligence and automation company. The two organizations are now undertaking subsequent phases covering operational validation, scaling and expansion, and automation. The pharmaceutical company found MaxTrace intelligence can provide a highly accurate three-hour advance prediction of any temperature excursion, with control tower alerts that greatly reduce the need for in-transit intervention. Because of this, the company expects to significantly cut operational costs as well as quality assurance and compliance expenditure. Furthermore, during this phase 1, unexpected levels of data and insights were provided – for example, the logistics team had no idea its containers were being opened so frequently.

CHALLENGE

Ensuring safe and compliant transportation of active pharmaceutical ingredients (APIs) on a global scale can be challenging. The biopharma industry loses approximately $35 billion annually as a result of failures in temperature-controlled logistics, according to the IQVIA Institute for Human Data Science, so companies aim to protect high-value, life-saving products from spoilage and loss. They also seek to cut operational costs by triggering in-transit action only when essential. And there is a growing need to reduce expenditure related to all-important quality assurance (QA) and compliance.

SOLUTION

In this phase 1 collaboration, MaxQ used MaxTrace technology with the pharmaceutical company’s active container (Envirotainer RKN e1) equipped with Roambee sensors; it contained APIs maintained at 2-8 C and it travelled on two multimodal lanes (Switzerland-USA and Switzerland-Brazil) in controlled ambient conditions.

The MaxTrace predictive cloud engine predicted the dynamic thermal life, calculating the time remaining until temperature excursion. MaxTrace is also capable of providing the pharmaceutical company’s control tower with real-time actionable insights about thermal life inside the container and can deliver data about the current and changing state, along with predictions of future state. This information can be delivered direct to decision makers via an online dashboard and other smart tools – a level of intelligence that would otherwise be difficult and prohibitively expensive to obtain.

OUTCOME

Analytics & Modelling

MaxTrace performed descriptive, diagnostic, and predictive analytics on over 350 shipment data sets. In addition, it used the physical and thermal characteristics of the Envirotainer to train the dynamic energy model which predicted the container’s battery level based on lane standard operating procedures (SOPs), location, inertial measurements, and ambient exposure.

This model assessed the impact of extreme lane ambient temperatures and charging compliance, and found the latter was the highest risk factor in the analyzed shipments.

Excursion Detection

Any payload temperature measurement outside the required range was detected. MaxTrace identified more than half (53%) of the shipments experienced a temperature incident with between one and five hours of measurements outside the 2-8 C range. Just over a quarter (27%) experienced incident excursions of less than an hour while 7% experienced incident excursions exceeding 15 hours.

Incident Classification

Several incident types were identified: sensor issues (information with which to improve quality control), door-open incidents (helpful for root cause analysis, RCA), non-compliant ambient temperature issues (useful for logistics provider accountability), extreme ambient temperature issues (enabling RCA and corrective action), and loss of power issues (useful for RCA and preventative and corrective analyses).

FINDINGS FROM PHASE 1

Effectively Predicted Excursion

With this intelligence, MaxTrace was able to predict temperature excursions and provide a three-hour window of opportunity for a proactive response. It also predicted the time to depletion of the container battery that will allow triggering an alert whenever the remaining battery charge level reaches 40%, sending this notification to the pharmaceutical company’s control tower. These predictive capabilities will enable the shipment team to take early preventative action, eliminating product spoilage and loss.

Maximized Thermal Life of Shipment

Using historical as well as current data, MaxTrace was able to provide insights beyond the pharmaceutical company’s expectations. For example, spikes in payload data were understood when correlated with newly classified door-open incidents. The company had not expected the container to be opened so frequently during transportation, and now realized a simple way to increase the thermal life of each shipment.

Reduced Quality Assurance & Compliance Costs

Real-time data-driven risk management not only enables zero temperature excursions but also SOP compliance. MaxTrace compared the measured lane ambient temperature data against planned SOP ambient data. An important output of this phase 1 initiative was a framework for automated post-shipment SOP compliance assessment using temperature data. These capabilities have given the pharmaceutical company access to automated, auditable corrective and preventative actions (CAPA) and enabled a significant reduction in QA and compliance expenditure.

Workflow Optimization

The pharmaceutical company identified several additional benefits of MaxTrace deployment including sustainability improvements through optimized packaging, physical and cold chain security improvements through real-time data and supply chain visibility, and higher levels efficiency through operational and workflow optimization.

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For further information, please contact maxtracesupport@flymaxq.com