The recent uptick in the approval of ex vivo cell therapies highlight 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 in 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 3·10 9 TU per mL of resin at the residence time of 1 min) and clearance of host cell proteins (up to 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.

X-ray computed tomography was applied in imaging 3D printed gyroids used for bioseparation in order to visualize and characterize structures from the entire geometry down to individual nanopores. Methacrylate prints were fabricated with feature sizes of 500 µm, 300 µm and 200 µm, with the material phase exhibiting a porous substructure in all cases. Two X-ray scanners achieved pixel sizes from 5 µm to 16 nm to produce digital representations of samples across multiple length scales as the basis for geometric analysis and flow simulation. At the gyroid scale, imaged samples were visually compared to the original computed aided designs to analyze printing fidelity across all feature sizes. An individual 500 µm feature, part of the overall gyroid structure, was compared and overlaid between the design and imaged volumes where individual printed layers could be identified. Internal subvolumes of all feature sizes were segmented into material and void phases for permeable flow analysis. Small pieces of 3D printed material were optimized for nanotomographic imaging at a pixel size of 63 nm, with all three gyroid samples exhibiting similar geometric characteristics when measured. An average porosity of 45% was obtained that was within the expected design range and a tortuosity factor of 2.52 was measured. Applying a voidage network map enabled the size, location and connectivity of individual pores to be identified, obtaining an average internal pore size of 793 nm. Using the Avizo XLAB plugin at a bulk diffusivity of 7.00 x10 -11 m 2s -1 resulted in a simulated material diffusivity of 2.17 x10 -11 m 2s -1 ± 0.16 x10 -11 m 2s -1.

A multiple length scale approach to the imaging and measurement of depth filters using X-ray computed tomography is described. Three different filter grades of varying nominal retention ratings were visualized in 3D and compared quantitatively based on porosity, pore size and tortuosity. Positional based analysis within the filters revealed greater voidage and larger average pore sizes in the upstream quartile before reducing progressively through the filter from the center to the downstream quartile, with these results visually supported by voidage distance maps in each case. Flow simulation to display tortuous paths that flow may take through internal voidage were examined. Digital reconstructions were capable of identifying individual constituents of voidage, cellulose and perlite inside each depth filter grade, with elemental analysis on upstream and downstream surfaces confirming perlite presence. Achieving an appropriate pixel size was of particular importance when optimizing imaging conditions for all grades examined. A 3 µm pixel size was capable of representing internal macropores of each filter structure, however for the finest grade an improvement to a 1 µm pixel size was required in order to resolve micropores and small perlite shards. Enhancing pixel size resulted in average porosity measurements of 70% to 80% for all grades.