(558d) Process Modeling of a Continuous Drug Substance Manufacturing Process

Authors: 
Yazdanpanah, N., U.S. Food and Drug Administration
O'Connor, T., U.S. Food and Drug Administration
Cruz, C. N., U.S. Food and Drug Administration
Continuous manufacturing has the potential to increase the efficiency, flexibility, agility, and robustness of pharmaceutical processes delivering benefits to both patients and industry. With respect to drug substance manufacturing, there are examples of continuous unit operations such flow synthesis steps for API manufacturing. The current trend is towards increased process integration as opposed to isolated continuous unit operations in an overall batch process and more advanced control strategy approaches including PAT, diversion of non-conforming products etc.

The unit operation connectivity (steady state mode) and effect of disturbances (process dynamic) on process robustness and challenges of process control to produce “in-range” quality product could be simulated by process modeling. The simulations will be used for case studies and sensitivity analysis to define the sensitivity of the process to particular process parameters, and to investigate the effects of Critical Process Parameters (CPPs) on Critical Quality Attributes (CQAs).

Two steady-state and dynamic process simulation models were developed for an integrated drug substance continuous manufacturing process. The manufacturing process risk analyses were performed and effect of various CPPs on the process robustness and final CQAs were evaluated. With the dynamic model sensitivity analysis and disturbance effects were studied as part of the system dynamic investigation. The system dynamic case studies demonstrate the response of the system to a various disturbances of CPPs (temporal and spatial distributions of disturbances). As a result of this simulation development, process control and manufacturing stability risk analyses were performed and response of the process to different disturbances evaluated under different control strategies.