The current standard, and proven scale down model (SDM), for Ultrafiltration/Diafiltration (UFDF) process characterization (PC) of monoclonal antibodies is to perform one run at a time using equipment such as the PendoTECH TFF Process Control System. Hence, 20 to 30 experiments for UFDF PC takes several weeks to perform due to the absence of a suitable high-throughput scale down model (HT-SDM). After evaluating different high-throughput tangential flow filtration (HT-TFF) systems, we present a HT approach for UFDF PC using Ambr Crossflow, developed by Sartorius. This system effectively replicates the performance of larger-scale processes in terms of yield, flux trends, and critical quality attributes as is expected for an SDM. Critically, it enables shortening of the PC timeline from several weeks to only a few days by allowing simultaneous runs (up to 16) at different process parameter setpoints, each with independent control.
Furthermore, we also evaluated UFDF performance using Pellicon XL50 membrane (50 cm²) in comparison to the standard Pellicon 3 membrane (88 cm²) (extensively used as a SDM owing to the conserved length of the channel flow path across different scales, including manufacturing scale) used for monoclonal antibodies. Whereas the compact 50 cm² cartridge has the advantage of not needing bulky metal holders for operation and having a lower hold-up volume as compared to the Pellicon 3 membrane (88 cm²), the initial design of the Pellicon XL50 membranes had concerns regarding flux scalability to large scale. However, with the recently redesigned Pellicon XL50 membranes (with upgraded feed channel hydrodynamics) we demonstrate adequate representativeness of the process across scales while significantly reducing the material requirements. Together, our work establishes the capability of the Ambr Crossflow system to serve as a HT-SDM for UFDF operations using both Pellicon 3 and Pellicon XL50 membranes, allowing for substancial acceleration of process characterization activities with reduced material requirements.

Lara Fernandez-Cerezo

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