Diogo Chagas

Background: Process analytical technology (PAT) enhances product quality by monitoring and controlling critical quality attributes (CQAs), offering better insights into process performance. Raman spectroscopy is a promising PAT tool to support the development of control systems for continuous and automated processes. In this study, Raman spectroscopy was used to monitor in real-time ultra- and diafiltration (UF/DF) of adeno-associated virus (AAV) and lentiviral vector (LV). Method: The incorporation of a Raman probe in a tangential flow filtration (TFF) system, when operated in open loop, enabled spectral acquisition during a five-fold concentration of clarified bulk followed by a buffer exchange to PBS with five diafiltration volumes. Results: Principal Component Analysis reduced the dimensionality of the training set, and a Partial Least Squares model was developed for each parameter in each phase. After validation, Raman monitoring platforms showed good performance in predicting CQA of both viral vectors. Batch-to-batch variability was identified as the principal source of spectral variation, and its impact on UF/DF operation was observed. Discussion: This study emphasises the potential of Raman spectroscopy as a PAT for monitoring and control strategies in the downstream processing of viral vectors. Conclusions: These monitoring platforms enhance understanding of TFF’s operation and enable timely decision making by providing real-time information on multiple parameters.