An HPLC-SEC-based rapid quantification method for vesicular stomatitis virus particles to facilitate process development.

Virus particle (VP) quantification plays a pivotal role in the development of production processes of VPs for virus-based therapies. The yield based on total VP count serves as a process performance indicator for evaluating process efficiency and consistency. Here, a label-free particle quantification method for enveloped VPs was developed, with potential applications in oncolytic virotherapy, vaccine development, and gene therapy. The method comprises size-exclusion chromatography (SEC) separation using high-performance liquid chromatography (HPLC) instruments. Ultraviolet (UV) was used for particle quantification and multi-angle light scattering (MALS) for particle characterization. Consistent recoveries of over 97% in the SEC were achieved upon mobile phase screenings and addition of bovine serum albumin (BSA) as sample stabilizer. A calibration curve was generated, and the method's performance and applicability to in-process samples were characterized. The assay's repeatability variation was <1% and its intermediate precision variation was <3%. The linear range of the method spans from 7.08 × 108 to 1.72 × 1011 VP/mL, with a limit of detection (LOD) of 7.72 × 107 VP/mL and a lower limit of quantification (LLOQ) of 4.20 × 108 VP/mL. The method, characterized by its high precision, requires minimal hands-on time and provides same-day results, making it efficient for process development.

Integrated process model for the prediction of biopharmaceutical manufacturing chromatography and adjustment steps.

A fundamental process understanding of an entire downstream process is essential for achieving and maintaining the high-quality standards demanded for biopharmaceutical drugs. A holistic process model based on mechanistic insights could support process development by identifying dependencies between process parameters and critical quality attributes across unit operations to design a holistic control strategy. In this study, state-of-the-art mechanistic models were calibrated and validated as digital representations of a biopharmaceutical manufacturing process. The polishing ion exchange chromatography steps (Q Sepharose FF, Poros 50 HS) were described by a transport-dispersive model combined with a colloidal particle adsorption model. The elution behavior of four size variants was analyzed and included in the model. Titration curves of pH adjustments were simulated using a mean-field approach considering interactions between the protein of interest and other ions in solution. By including adjustment steps the important process control inputs ionic strength, dilution, and pH were integrated. The final process model was capable to predict online and offline data at manufacturing scale. Process variations at manufacturing scale of 94 runs were adequately reproduced by the model. Furthermore, the process robustness against a 20% input variation of concentration, size variant and ion composition, volume, and pH could be confirmed with the model. The presented model demonstrates the potential of the integrated approach for predicting manufacturing process performance across scales and operating units.

Development and performance of a 3D-printable poly(ethylene glycol) diacrylate hydrogel suitable for enzyme entrapment and long-term biocatalytic applications.

Physical entrapment of enzymes within a porous matrix is a fast and gentle process to immobilize biocatalysts to enable their recycling and long-term use. This study introduces the development of a biocompatible 3D-printing material suitable for enzyme entrapment, while having good rheological and UV-hardening properties. Three different viscosity-enhancing additives have been tested in combination with a poly(ethylene glycol) diacrylate-based hydrogel system. The addition of polyxanthan or hectorite clay particles results in hydrogels that degrade over hours or days, releasing entrapped compounds. In contrast, the addition of nanometer-sized silicate particles ensures processability while preventing disintegration of the hydrogel. Lattice structures with a total height of 6 mm consisting of 40 layers were 3D-printed with all materials and characterized by image analysis. Rheological measurements identified a shear stress window of 200 < τ < 500 Pa at shear rates of 25 s-1 and 25°C for well-defined geometries with an extrusion-based printhead. Enzymes immobilized in these long-term stable hydrogel structures retained an effective activity of approximately 10% compared to the free enzyme in solution. It could be shown that the reduction of effective activity is not caused by a significant reduction of the intrinsic enzyme activity but by mass transfer limitations within the printed hydrogel structures.