Bi-Objective Optimization for the Clinical Trial Supply Chain Management

In the pharmaceutical industry, clinical trials constitute a critically important and very expensive part of the new drug development process. A clinical trial supply chain will terminate after 1-2 years, and leftovers at the end of clinical trials constitute an important financial cost since all the unused materials should be disposed after clinical trial completion. Normally, extra safety stocks are kept in the supply chain system to increase the customer service level (CSL), however more leftovers are introduced by increasing safety stocks. By considering a bi-objective optimization using a weightedsum approach, we build an approximation to the CSL vs. leftovers Pareto frontier. This will support the evaluation of the trade-off between these two performance metrics and thus the selection of a safety stock level that optimally balance CSL and leftovers. The entire framework includes four modules: demand forecasting, an integrated planning and optimization formulation, a discrete event simulation model and an outer loop optimization process. An industrially motivated case study is presented to demonstrate the utility of this proposed approach.