Positioning Inventory in Clinical Trial Supply Chains

As a result of slow patient recruitment and high patient costs in the United States, clinical trials are increasingly going global. While recruitment efforts benefit from a larger global footprint, the supply chain has to work harder at getting the right drug supply, to the right place, at the right time. Certain clinical trial supply chains, especially those supplying biologics, have a combination of unique attributes that have yet to be addressed by existing supply chain models. These attributes include a fixed patient horizon, an inflexible supply process, a unique set of service-level requirements, and an inability to transfer drug supplies among testing sites. In this paper, we provide a new class of multi-echelon inventory models to address these unique aspects. The resulting mathematical program is a nonlinear integer programming problem with chance constraints. Despite this complexity, we develop a solution method that transforms the original formulation into a linear integer equivalent. By analyzing special cases and through numerical study of both real-life and simulated examples, we develop novel insights into inventory positioning and the cost drivers in clinical trial supply chains.