The demand for effective downstream processing of adeno-associated virus (AAV) is increasing as gene therapies advance toward broader clinical applications. Robust, efficient, and scalable ultrafiltration and diafiltration (UF|DF) operations are essential for generating high-quality AAV preparations, with tangential flow filtration (TFF) serving as a critical unit operation for vector concentration, impurity reduction, and buffer exchange while maintaining viral functionality. Development of TFF processes requires careful consideration of membrane characteristics—including chemistry, pore size or channel architecture—as these parameters directly influence vector retention, fouling behavior, and overall process efficiency. Equally important is the optimization of critical process parameters such as recirculation rate, transmembrane pressure (TMP), and total processing time, all of which govern hydrodynamic performance and product quality. This study assessed two Sartocon® Hydrosart® TFF cassette architectures—ECO-Screen and E-Screen—for the ultrafiltration and diafiltration of AAV8 clarified lysate. Through flux characterization and controlled small-scale evaluations, cassette-specific operating regions were defined. Both configurations supported high viral genome retention; however, the E-Screen geometry achieved faster processing and superior removal of host–cell protein and DNA contaminants, whereas the ECO-Screen format allowed for efficient operation under reduced pump rates and, therefore, lower shear conditions. Reproducibility assessments demonstrated minimal run-to-run variability, confirming the robustness of the optimized operating parameters. A 10-fold scale-up further validated the linearity and predictability of the UF|DF process, with consistent impurity-reduction profiles and only modest deviations in viral recovery. Collectively, these findings provide a quantitative basis for rational cassette selection in AAV purification workflows and establish a scalable, scientifically grounded UF|DF framework applicable across development and manufacturing scales.
Cardoso et al. (Fri,) studied this question.