Hollow fiber-based membrane filtration has emerged as the dominant technology for cell retention in perfusion processes yet significant challenges in alleviating filter fouling remain unsolved. In this work, the benefits of co-current filtrate flow applied to a tangential flow filtration (TFF) module to reduce or even completely remove Starling recirculation caused by the axial pressure drop within the module was studied by pressure characterization experiments and perfusion cell culture runs. Additionally, a novel concept to achieve alternating Starling flow within unidirectional TFF was investigated. Pressure profiles demonstrated that precise flow control can be achieved with both lab-scale and manufacturing scale filters. TFF systems with co-current flow showed up to 40% higher product sieving compared to standard TFF. The decoupling of transmembrane pressure from crossflow velocity and filter characteristics in co-current TFF alleviates common challenges for hollow-fiber based systems such as limited crossflow rates and relatively short filter module lengths, both of which are currently used to avoid extensive pressure drop along the filtration module. Therefore, co-current filtrate flow in unidirectional TFF systems represents an interesting and scalable alternative to standard TFF or alternating TFF operation with additional possibilities to control Starling recirculation flow.

Raman spectroscopy has gained popularity to monitor multiple process indicators simultaneously in biopharmaceutical processes. However, robust and specific model calibration remains a challenge due to insufficient analyte variability to train the models and high cross-correlation of various media components and artefacts throughout the process. Therefore, a systematic Raman calibration workflow for perfusion processes enabling highly specific and fast model calibration was developed. A harvest library consisting of frozen harvest samples from multiple CHO cell culture bioreactors collected at different process times was established, capturing process variability as widely as possible. Model calibration was subsequently performed in an offline setup using a flow cell by spiking process harvest with various sugars known to modulate glycosylation patterns of monoclonal antibodies. In a screening phase, Raman spectroscopy was proven capable not only to distinguish glucose, raffinose, galactose, mannose, and fructose in perfusion harvest, but also to quantify them independently in process relevant concentrations. In a second phase, a robust and highly specific calibration model for simultaneous glucose (RMSEP = 0.32 g/L) and raffinose (RMSEP = 0.17 g/L) real-time monitoring was generated and verified in a third phase during a perfusion process. The proposed offline calibration workflow allowed proper Raman peak decoupling, reduced calibration time from months down to days and can potentially be applied to other analytes of interest including lactate, ammonia, amino acids, or product titer.