(402g) Supply Chain Analysis of Continuous Pharmaceutical Manufacturing

In traditional pharmaceutical supply chains, production takes place in two major steps: 1) primary production, and 2) secondary production. In primary production, the raw materials are converted into active pharmaceutical ingredients (APIs) through multiple intermediate production stages. It is common in practice to carry out the first few stages of production in one location, and the other stages in a different location. In secondary production, the APIs are formulated into different drug products (DPs) through various unit operations such as granulation, molding, coating, and packaging. The secondary production facilities are usually located closer to the major markets. Finally, the DPs are supplied to warehouses or retailers for distributions. The above traditional supply chain design has several disadvantages such as high costs of inventory and logistics, long supply-chain cycle times, high degree of supply-chain disruptions, and less resilience. Furthermore, the pharmaceutical industry has been dominated by the batch mode of manufacturing for decades, which greatly contributes to the above inefficiencies in the supply chain. Recently, the Novartis-MIT Center for Continuous Manufacturing has embarked on an innovative project to shift from the batch mode of manufacturing to the continuous mode, where raw materials through the APIs to the finished products are processed seamlessly in an integrated facility. Such an integrated end-to-end production scheme is more promising for several reasons: a) low costs of inventory, logistics, and production, b) short supply-chain cycle times, c) less exposure to supply-chain disruptions, and d) resilient supply chain. Thus, the option of continuous manufacturing brings in additional challenges and opportunities in the context of pharmaceutical supply chains.

In this work, we develop an optimization framework to analyze various supply chain configurations based on continuous production facilities. Since the option of storing APIs contributes to increased degrees of freedom, we also analyze supply chain configurations based on the decoupled production scheme, where primary and secondary production are separated by storage units. However, the mode of production in the decoupled scheme is still continuous. We consider three different supply chain configurations: 1) centralized configuration, where APIs and DPs of all products are produced in a single location, 2) semi-centralized configuration, where APIs of all products are produced in one location, and DPs are produced in different locations closer to the markets, 3) localized configuration, where both APIs and DPs of various products are produced in different locations closer to the markets. We present a mixed-integer linear programming (MILP) model for the analysis of the various supply chain configurations. The key decisions of the proposed framework are which production scheme is economical, which supply chain configuration is efficient, and what should be the sizes of facilities given the demands of products over the planning horizon. We illustrate the application of the proposed framework using three different drug molecules of different dosage levels and different demand volumes.