Analytical and data strategy for continuous downstream manufacturing

As advances emerge in developing continuous biomanufacturing processes, there is an increased need to deploy PAT tools to characterize, monitor, and control key quality attributes and a criticality to have a data infrastructure to support the immense amount of information being generated. While the desire for these tools exists in traditional batch processing, in a continuous operation, these become a requirement to ensure consistent product quality and enable proactive approaches in maintaining performance. The ultimate goal is to deploy PAT tools to reliably provide real-time information on product and process impurities throughout the entire operation. However, in its current state, there is a reliance on a mixture of inline, at-line, and offline technologies. By identifying the time criticality of CQAs, efforts can be focused on where to prioritize real-time measurements or instead, quicker or more automated testing for a subset of analytics. This work describes the application of this approach in the development of small-scale, compact in-line UV instruments to measure real-time protein concentration and in the integration of an automated sampling system with at-line and offline instrumentation for in-process impurity characterization. Introduction of these PAT tools add to the complexity of the data infrastructure as it introduces requirements for platforms capable of supporting spectral data, chemometric model deployment, spectral instrument management, and time-alignment of discrete data. With the vast amount of information produced in a continuous environment, interface and analysis tools need to be developed so that any end-user can digest data into a format that easily allows them to gain insight into an ongoing batch. This work will highlight the data architecture of the continuous platform, with a focus on software tools selected for aggregation and real-time data visualization. The capabilities of these software packages were demonstrated through a proof-of-concept study using single-pass tangential flow filtration (SPTFF) as a model unit operation, which allowed integration of continuous, spectral, and discrete data. These tools allowed scientists to go from viewing real-time data across multiple, equipment-specific software to one consolidated interface, which in turn reduced time spent in compiling data for analysis and reporting. In addition, advanced capabilities of deploying model predictive control in SPTFF were demonstrated to show the application of a closed loop process control in continuous manufacturing

Towards implementation of novel single-use devices in integrated processes for biopharmaceuticals

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Peptide ligands targeting the vesicular stomatitis virus G (VSV-G) protein for the affinity purification of lentivirus particles

The recent uptick in the approval of ex vivo cell therapies highlights the relevance of lentivirus (LV) as an enabling viral vector of modern medicine. As labile biologics, however, LVs pose critical challenges to industrial biomanufacturing. In particular, LV purification—currently reliant on filtration and anion-exchange or size-exclusion chromatography—suffers from long process times and low yield of transducing particles, which translate into high waiting time and cost to patients. Seeking to improve LV downstream processing, this study introduces peptides targeting the enveloped protein Vesicular stomatitis virus G (VSV-G) to serve as affinity ligands for the chromatographic purification of LV particles. An ensemble of candidate ligands was initially discovered by implementing a dual-fluorescence screening technology and a targeted in silico approach designed to identify sequences with high selectivity and tunable affinity. The selected peptides were conjugated on Poros resin and their LV binding-and-release performance was optimized by adjusting the flow rate, composition, and pH of the chromatographic buffers. Ligands GKEAAFAA and SRAFVGDADRD were selected for their high product yield (50%–60% of viral genomes; 40%–50% of HT1080 cell-transducing particles) upon elution in PIPES buffer with 0.65 M NaCl at pH 7.4. The peptide-based adsorbents also presented remarkable values of binding capacity (up to 3·10⁹ TU per mL of resin, or 5·10¹¹ vp per mL of resin, at the residence time of 1 min) and clearance of host cell proteins (up to a 220-fold reduction of HEK293 HCPs). Additionally, GKEAAFAA demonstrated high resistance to caustic cleaning-in-place (0.5 M NaOH, 30 min) with no observable loss in product yield and quality

Pseudo-affinity capture of <i>K. phaffii </i>host cell proteins in flow-through mode: purification of protein therapeutics and proteomic study

K. phaffii is a versatile expression system that is increasingly utilized to produce biological therapeutics – including enzymes, engineered antibodies, and gene-editing tools – that feature multiple subunits and complex post-translational modifications. Two major roadblocks limit the adoption of K. phaffii in industrial biomanufacturing: its proteome, while known, has not been linked to downstream process operations and detailed knowledge is missing on problematic host cell proteins (HCPs) that endanger patient safety or product stability. Furthermore, the purification toolbox has not evolved beyond the capture of monospecific antibodies, and few solutions are available for engineered antibody fragments and other protein therapeutics. To unlock the potential of yeast-based biopharmaceutical manufacturing, this study presents the development and performance validation of a novel adsorbent – PichiaGuard – functionalized with peptide ligands that target the whole spectrum of K. phaffii HCPs and designed for protein purification in flow-through mode. The PichiaGuard adsorbent features high HCP binding capacity (∼25 g per liter of resin) and successfully purified a monoclonal antibody and an ScFv fragment from clarified K. phaffii harvests, affording &gt;300-fold removal of HCPs and high product yields (70 – 80%). Notably, PichiaGuard outperformed commercial ion exchange and mixed-mode resins without salt gradients or optimization in removing high-risk HCPs – including aspartic proteases, ribosomal subunits, and other peptidases – thus demonstrating its value in modern biopharmaceutical processing