Abstract:
Over the past decade, hundreds of medically necessary drugs have experienced shortages, often caused by supply chain disruptions. Disruptions can be mitigated if companies maintain redundant facilities or hold inventory, though in their absence, there is little a manufacturer can do to adjust. Generic pharmaceutical companies rarely have either, and shortages last over a year on average. We consider two key questions: is it optimal for companies to maintain vulnerable supply chains and what policies would be effective at reducing shortages? To address these, we develop multi-stage stochastic programs to optimize the design of a pharmaceutical company’s supply chain under uncertainty in disruption and recovery. Components include suppliers of active pharmaceutical ingredients (APIs), manufacturing plants, and lines. The supply chain design models are among to consider disruptions at multiple echelons and disruptions and recovery over time. We solve the model with a static supply chain configuration using Sample Average Approximation, and a dynamic version using the Stochastic Dual Dynamic Integer Programming algorithm. We study the effects of policies proposed to reduce shortages on supply chains of example oncology drugs.

Bio:
Dr. Emily Tucker is an Assistant Professor at Clemson University in the Department of Industrial Engineering and a Faculty Scholar in the School of Health Research. Her research focuses on the applications of stochastic optimization in supply chain resiliency and social good. She received her PhD and MSE in Industrial and Operations Engineering from the University of Michigan. She was supported by an NSF Graduate Research Fellowship and her dissertation work was awarded the University of Michigan Richard and Eleanor Towner Prize for Outstanding Ph.D. Research. Prior to graduate school, she worked as a Research Health Economist as RTI International and received her BS in Industrial Engineering from NC State.

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