Stop Shipping What Won’t Be Used: How a Clinical-Stage Biotech Used Consulting and Analytics to Cut Clinical Trial Supply Waste Without Putting a Single Site at Risk of Stock-Out

Clinical trial supply chains are built around a specific fear: the investigator site that runs out of investigational product midway through a patient’s treatment cycle. That fear is legitimate.

The client’s supply planners had set site inventory buffers at the start of the trial based on projected enrolment rates and had not systematically revisited those buffers as the actual enrolment trajectory diverged from the forecast across different site clusters. Some sites were enrolling ahead of projection and running through inventory faster than the model expected.

The practical difficulty was that the clinical operations team was understandably cautious about any buffer reduction conversation, because the consequences of a stock-out were visible and attributable in a way that wastage costs were not. Moving the conversation from a blanket buffer to a risk-stratified model required an analytical basis for distinguishing which sites genuinely needed their current buffer and which were holding safety stock against an enrolment trajectory that no longer warranted it.

Key Challenges

• No site-level analytics distinguishing sites where inventory buffers were materially in excess of actual consumption risk from those where buffers were genuinely warranted.
• Blanket inventory buffer levels set at trial initiation and not revisited as actual site enrolment trajectories diverged from the original forecast.
• Expiry-driven wastage running at nearly thirty percent of total drug manufactured, generating significant cost against the biotech’s constrained manufacturing budget.
• Clinical operations team caution about any buffer reduction conversation given the asymmetric visibility of stock-out versus wastage costs.
• No risk-stratified resupply model that could reduce wastage at slow-enrolling sites without reducing buffers at sites with genuine consumption velocity risk.
• Supply chain finance pressure to address the wastage rate before the next manufacturing campaign committed further product to a model producing thirty percent expiry loss.

Clinical trial supply waste is not a supply chain efficiency problem in the conventional sense. It is a calibration problem: buffers sized to a forecast that no longer matches reality. The solution is not to reduce buffers uniformly but to understand which sites are holding excess against a revised trajectory and which are holding exactly what the current enrolment pattern warrants.