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Updated: Dec 22, 2025

Real-time Monitoring of Reactions Performed Using Continuous-flow Processing: The Preparation of 3-Acetylcoumarin as an Example
Published on: November 18, 2015
The development and validation of a quality by design based process analytical tool for the inline quantification of
Suha M Dadou1, Zoe Senta-Loys1, Ammar Almajaan1
1Pharmaceutical Engineering Group, School of Pharmacy, Queen's University Belfast, Belfast, United Kingdom.
Abstract:
Continuous processing is superseding conventional batch processing as a means of manufacturing within the pharmaceutical research/industry. This paradigm shift has led to the implementation of Process Analytical Technology (PAT) as a semi-automatic, predictive tool offering real-time quality control that can be built into the production line. However, PAT tools have been mainly utilised to monitor a single process (e.g. powder blending, synthesis of biopharmaceuticals and small molecules) rather than a full continuous manufacturing process. In addition, there is a paucity of guidance documents that consider the continuous and dynamic conditions of real-time measurements for validation purposes. In this study, the feasibility of developing and validating a predictive and reliable Raman method based on quality by design (QbD) and PAT frameworks for the real-time quantification of Ramipril (RMP) during hot-melt extrusion (HME) were investigated. Through QbD, a design space elucidating the quality attributes of RMP stability was successfully identified based on offline HPLC measurements. Process temperature and powder feeding rate were the main quality attributes to affect the stability of RMP during HME. The optimum combination of process and formulation variables were extracted from the validated design space and used to extrude RMP at a concentration range of 2.5-12.5 %w/w. Three calibration models were established using PLS regression analysis. The developed PLS calibration models showed excellent linearity (R2 = 0.989, 0.995, 0.992), accuracy (RMSEcv = 0.31, 0.26, 0.30%) and specificity (PC1 = 81, 85, 89%) for models 1, 2 and 3, respectively. Furthermore, the developed QbD-PAT model was able to predict the quantity of RMP at varied process feed rate (10, 35 rpm) operating under long processing time (60 min). The output of this study allows in-process optimisation of formulation and process variables to control the quality and quantity of RMP during HME. Furthermore, it allows the implementation of PAT tools as routine methods of analysis within the laboratory.
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