Sartorius (Germany)

The paper addresses the transition from traditional to digital calibration certificates (DCC) for weights and mass standards, focusing on the critical aspect of machine interpretability. The main objective is to develop a methodology that converts human-readable calibration information into a format that can be processed by machines. To achieve this, the paper presents a structured approach for encoding information into the DCC framework, supplemented by practical examples that illustrate the fitting of data into the proposed structure. The study underscores the necessity of constructing semantic networks and formulating application rules to ensure consistency and harmonisation across DCCs for various weight and mass measurement devices. The results indicate that accurate digital representation of calibration information is paramount for the effectiveness of DCCs. The paper concludes by emphasising the current need for more advanced semantic networks to facilitate the seamless integration and interpretation of DCCs.

Lateral flow assays (LFAs) have caught new attention in recent years due to extensive use in the containment of the COVID-19 pandemic. Especially the protein and fluid interactions with the nitrocellulose membrane structure are yet to be fully investigated, which affect the fluid and protein distribution of the test and control lines differently due to different adsorptive properties of fluids and proteins. Therefore, the relationship between fluid spread and protein distribution, respectively, and structure needs systematic evaluation. Two procedures were developed based on passive adsorption of complementary fluorescent dyes to investigate these phenomena. These procedures enabled three-dimensional visualization of the membrane structure, fluid as well as the protein spreading, respectively. Confocal laser scanning microscopy was applied after depositing picoliter and nanoliter volumes of the printing buffers containing fluorophore-labeled proteins (immunoglobulin G) and Oregon Green™ 488 onto the membrane using a high precision micro dispenser. The resulting data were correlated with the membrane's tortuosity and permeability. Inverse-proportional dependencies for the lateral spread of the fluid and protein adsorption with the structural parameters were observed. Additionally, surfactants [polysorbate 80 (PS80) and sodium dodecylbenzenesulfonate (SDBS), both at 0.1%] were added individually to the buffers, and the spread of the liquids was evaluated. Both surfactants increase the similarities between fluid and protein shape compared to the reference data. While SDBS increases the general lateral spread, PS80 does increase the penetration depth of the protein into the membrane, which could lead to reduced signal in LFAs.

The primary drivers impacting cell and gene therapy (CGT) time-to-market and COGs include productivity, enabling process control, and ensuring the quality of the final cell product. Achieving these goals requires a functional supply chain and the ability to seamlessly scale-up. This article will discuss the collaborative study between Satorius and University College London, exploring process intensification strategies in stirred-tank bioreactors for CAR-T manufacturing.

Adeno-associated viruses (AAV) are among the leading vectors for in vivo gene therapy. The purification of AAV remains a bottleneck as it typically requires multiple individual process steps, often resulting in product loss and high costs. Current downstream processes are usually serotype-specific and rely primarily on expensive affinity resins. To address these limitations, we developed a serotype-independent purification method using steric exclusion chromatography (SXC) that can be combined with a subsequent anion exchange full/empty separation step. This alternative approach eliminates the need for intermediate concentration and buffer exchange, thereby reducing the number of process steps required while achieving high-purity full AAV particles. SXC conditions were optimized using a design of experiments approach. Isocratic separation of full and empty AAV resulted in further purification of the sample. The overall process achieved a viral genome recovery of 51.7 %, along with impurity depletions of 99.9 % for DNA and 99.8 % for protein. The process was successfully adapted to different AAV serotypes and genes of interest, demonstrating its robustness and versatility. In addition, the scalability of SXC was demonstrated, highlighting its potential for large-scale manufacturing. This streamlined, universal, and scalable process provides a robust and efficient alternative to traditional AAV purification processes, addressing critical challenges in gene therapy production and paving the way for broader implementation in research and manufacturing.

Crosslinking agarose with bisoxiranes and epihalohydrins has been explored for years and is widely applied in the manufacturing of chromatography beads as industrial standard. Nevertheless, the effect on the molecular structure of agarose and the resulting consequences when used as chromatographic adsorber are poorly investigated. Agarose beads modified with 1,4‐butanediol diglycidyl ether (BDDE) and epichlorohydrin (ECH), respectively, were characterized regarding their pore size and diffusion coefficients. Modification with BDDE led to reduced pore sizes, whereas no influence could be observed when using ECH. After functionalization as cation exchanger, BDDE‐ and ECH‐modified beads were analyzed among others regarding their binding capacity of lysozyme and γ‐globulin. Therefore, the hypothesis of crosslinking‐induced diffusion limitation, especially with BDDE, could be further strengthened. Finally, the data were described by calculating the static binding capacity and diffusion coefficient using a cubic grid model and Ogston model, respectively. Overall, those simplified models describe the data quite accurate, whereas the deviation of the model from the static binding capacity is 4% ± 17%, from the diffusion coefficient of the BDDE‐ or ECH‐modified beads 1% ± 16% and from the effective diffusion coefficient of the further sulfonated and column packed beads 11% ± 27%.

Chimeric antigen receptor (CAR) T cell therapy has tremendous potential for the treatment of cancer and other diseases. To manufacture cells of the desired quantity and quality, it is important to expand the CAR T cells ex vivo for an optimal duration. However, identifying the optimal harvest time requires knowledge of the cell concentration during the expansion period. To address this challenge, we have developed a digital shadow of CAR T cell expansion that provides a soft sensor of cell concentration in real‐time. Specifically, a novel mechanistic mathematical model of cell growth within a proportional‐integral‐derivative (PID) controlled perfusion bioreactor has been developed using nonlinear ordinary differential equations. The model is fitted to data generated via bioreactor runs of the Aglaris FACER, in which both donor and patient cells have been expanded in two different media. Off‐line data includes the initial and final cell concentrations, and online data includes the glucose and lactate concentrations as well as the perfusion rate. Training the digital shadow utilizes all the off‐line and online data for each run. In contrast, real‐time testing utilizes only the initial cell concentration and the available online data at the time of model fitting. Real‐time testing shows that with at least 2.5 days of online data, the final cell concentration up to 2.5 days later is predicted with a mean relative error of 13% (standard deviation ≈ 6%). Informative real‐time predictions of cell concentration via the digital shadow can guide decisions regarding the optimal harvest time of CAR T cells.

The emergence of allogeneic, universal chimeric antigen receptor (CAR) T cell therapies requires intensified and scalable manufacturing workflows supported by representative scale-down models (SDMs) to enable efficient process development and future large-scale production of off-the-shelf therapies. Here, we present a 7-day CAR-T cell expansion process intensified via perfusion of serum-free medium in a 2 L Univessel® Single-Use stirred-tank bioreactor (STR), consistently achieving 30 × 106 cells/mL, corresponding to 113 ± 7 anti-CD19 CAR-T doses per batch. Parallel runs in 250 mL Ambr® 250 STRs conducted at equivalent volumetric power input (P/V) of ∼8.78 W/m3 demonstrated comparable process performance and final product quality, with univariate and multivariate analyses of cell growth, phenotype, cytotoxicity, and cytokine secretion validating the Ambr® 250 as a predictive SDM for the 2 L process. Integrating capacitance sensing in the 2 L STR enabled robust monitoring of viable cell concentrations in real-time, with strong correlation to offline measurements (R2 = 0.98). For downstream processing, the Ksep® 400 was used to automate CAR-T cell harvesting, concentration, and washing at the 2 L scale, achieving >90% product recovery and nine-fold volume reduction without impacting product quality attributes compared to manual methods. This study establishes a scalable CAR-T manufacturing workflow supported by a predictive SDM, providing an efficient platform for process development and scale-up to enable future large-scale production of allogeneic CAR-T cell therapies.

Three-dimensional (3D) bioprinting presents a transformative approach to replicating vivo-like environments for mammalian cell cultures, offering potential advances in bioproduction and tissue engineering. In this study, we investigated the growth, metabolic activity, and structural organization of four mammalian cell lines (HEK, MDCK, CHO, and Vero) in 3D bioprinted constructs. Our results demonstrate that even highly selected, immortalised cell lines can regain physiological traits closer to their native tissue when cultured in 3D environments. We observed significant shifts in proliferation kinetics, including reduced growth rates and reduced fermentative activity. A Design of Experiment (DOE) approach identified critical biofabrication parameters—such as hydrogel microporosity and consolidation conditions—that modulate cell behavior and proliferation in 3D matrices. These findings highlight the potential of 3D bioprinting not only for medical applications, such as regenerative medicine and drug testing, but also for enhancing bioproduction processes by supporting higher cell densities and metabolic efficiency. Our work underscores the importance of optimizing 3D culture conditions to mimic vivo-like behaviors and improve productivity, offering new insights into the scalability of bioprinted constructs for industrial applications.