Clinical trial supply overage – How to reduce product wastage in an unpredictable world?

Illustration of strategies to reduce overage and wastage in clinical trial supply chains while maintaining reliable patient service levels
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Brieuc Triffaux
24/04/2016

Pharmaceutical organizations are putting more and more pressure on clinical supply chain managers to minimize study overage. Study overage represents the kits that will expire unused at the investigational sites, local depots and central depot. Some overage is absolutely needed, both as insurance against the unexpected events that can occur during the trial and as a result of the design of the protocol and distribution network. But often the question is raised (and not only by higher management): is the requested amount of overage absolutely necessary or is it possible to decrease it?

SOURCES OF OVERAGE

Due to the unpredictability in the demand of the drugs and the need to cover for unexpected events, a certain overage is required as safety stock on sites. There will be a necessary overage at sites in order to cover the unpredictability stemming from patient randomization, different treatment arms, dose levels, risk of an unplanned visit should a patient lose a kit, etc. There will also be necessary overage at the local depots in case the demand coming from the supplied sites is much higher during a time period than initially planned. An important factor to consider in the overage levels at the local depots is the shipping lead time between the central depot and the local depot. The longer the lead time, the more necessary overage is needed to be kept at the local depot. Despite requiring sometimes high overage, it remains difficult to estimate the risk at the local depots without simulation. Based on what many large pharma companies, the local depots remain one of the main sources of both risky situations and high overage. Finally, there will also be extra kits kept at the central depot as insurance against the unexpected coming from downstream in the supply chain (e.g. high local demand or lost shipments). Clinical supplies often have to deal with long manufacturing and packaging lead times, impacting the flexibility in the release schedule and thus increasing the necessary overage.

WHAT ARE THE WAYS TO FIGHT AGAINST PRODUCT WASTAGE?

There are many initiatives in place across the industry aimed at fighting against product wastage during trials. Some approaches are more focused on improving existing processes, such as applying Lean methodologies to shorten manufacturing lead-time or allowing for more flexibility in the production planning. This can translate to less overage by allowing better overlap of new lots being shipped to replace expiring kits. Other approaches are more technologically driven, such as drug pooling across protocols to have a better, more flexible usage of medicine across the different studies or, in the future, e-labelling, where protocol numbers can be programmed on the label later in the process (i.e. at site level) and expiry updates can be made directly without relabeling. Further approaches to reduce overage include early collaboration between the Clinical team and the Clinical Supply team during protocol design in order to take decisions such as visit interval, kit design, country selection, randomization level, drug formulation/dose level, etc. Indeed, the decisions at protocol design stage are often taken without full consideration of the supply aspects. Therefore, involving the supply team earlier in this process will significantly decrease the overage (as well as the total cost of supplies) while maintaining focus on patient-centricity. Simulating the trial is a key approach in the fight against too much overage. Simulationidentifies the areas of risk and just how much overage is needed to cover the worst-case situation. Additionally, simulation and optimization of the supply strategy complement many other initiatives, such as providing quantified results on different scenarios investigated during the protocol design. Having these results significantly improves understanding the impact of these early decisions and helps cross department communication.

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