Quality-by-digital-design for the in-process integration of Raman spectroscopy as a PAT tool in continuous manufacturing of pharmaceutical liquids and semi-solids.

Over the past years, process analytical technology (PAT) tools have been increasingly adopted into pharmaceutical manufacturing to enable real-time process monitoring and product quality control. However, the integration of these tools into the process stream remains a significant challenge, primarily relying on empirical trial-and-error approaches. In view of this, this study demonstrates the application of Quality-by-Digital-Design (QbDD) principles for the in-process integration of Raman spectroscopy as a PAT tool in a continuous manufacturing system for pharmaceutical liquids and semisolids through a custom-built interfacing device. By applying a systematic and model-based approach, this study aimed to evaluate the interface performance by locating hydrodynamic anomalies, such as fluid circulation and dead zones within the integrated system. The PAT sensor immersion depth, volumetric flow rate, and dynamic viscosity were identified as high-risk factors. Their impact on the interface performance was investigated using a full-factorial Design of Experiments (DoE). Residence Time Distribution (RTD) analysis was performed using computational fluid dynamics (CFD) simulations to estimate fluid circulation and dead volume fraction. The CFD-RTD simulations were validated using experimentally measured RTD. A tank-in-series model with plug flow and a dead volume fraction model best described the fluid behavior within the PAT interface. CFD simulations revealed the presence of dead zones, which were located at the edges of the interface. The CFD-RTD model predictions indicated that increasing the sensor immersion depth or the dynamic viscosity of the fluid results led to an increase in the dead volume fraction within the system. Moreover, the DoE results showed that the volumetric flow rate is the most important factor affecting fluid circulation, while dynamic viscosity is the most important factor affecting the dead volume fraction.