Modular Design and Dynamic Adjustment Strategy for Enhanced Economic Robustness in Continuous Pharmaceutical Manufacturing

Continuous pharmaceutical manufacturing plants are conventionally built with customized, fixedcapacity equipment, leading to high capital risk and suboptimal operational performance when adjusting production throughput to match fluctuating market demands. To overcome these limitations, this study proposes a modular design and dynamic adjustment strategy that adapts to demand uncertainty. The aim is to ensure long-term economic performance and flexibility. Demand uncertainty is represented using two stochastic models: a fixed-rate compound annual growth rate (CAGR) scenario capturing uncertainty under long-term market growth trends, and a time-dependent CAGR scenario accounting for annual growth rate fluctuations within those longterm trends. As a case study, we evaluate the continuous ibuprofen manufacturing process by comparing the conventional plant consisting of customized reactors with the modular plant including standardized reactor modules. The dynamic adjustment strategy selects active reactor modules based on a kinetically informed switching strategy to maintain optimal performance. Long-term economic performance is evaluated using the levelized cost of production (LCOP) across 100 independent stochastic demand trajectories for each CAGR scenario. Results indicate that conventional design is highly sensitive to demand uncertainty, whereas the modular design demonstrates greater economic robustness, achieving a lower mean LCOP with reduced cost variability, and eliminates the risk of unprofitability.