Based on computational fluid dynamics we fabricated precisely ordered three-dimensional chromatography columns with a pore structure relevant for chromatography. The novel material was generated by 3D printing and the advantages for separation of large and small biomolecules, including bionanoparticles like viruses and virus like particles will be presented.

The fully-automated fermentation platform at Boehringer Ingelheim in Vienna has been developed to the point that it can routinely carry out up to 100 fed-batch fermentation runs per week. Huge amount of data is generated, which in turn paves the way for implementing both mechanistic and statistical modeling approaches. Such models help accelerate process development and build knowledge to reduce developmental efforts, ensuring deeper process understanding and better manufacturing processes. In this talk, I will highlight the implemented models used in our high-throughput platform and their uses in different parts of process development. 

As biologic therapeutics continue to increase in complexity, innovative approaches to candidate screening, characterization and development are more important than ever. Our approaches to high-throughput protein production incorporate advanced analytics, automation and high-quality informatics to enable robust molecule screening, selection and scale-up. These enhancements enable advances in the speed, quality and productivity of our biologics development pipeline.

With dozens of monoclonal antibodies (mAbs) in production, accurate in/at-line mAb quantification is vital to biomanufacturing. Current mAb quantification is time-/labor-intensive. Therefore, we developed the "Dual-Affinity Ratiometric Quenching" (DARQ) assay for rapid quantification of mAb titer and glycosylation, and host cell protein (HCP) titer. The assay is reproducible (variation <1%) and rapid (5 min), and offers excellent sensitivity (<0.5 ng/mL), limit of detection (<100 ng/mL), and dynamic range (100-1600 ng/mL).

Protein purification using traditional chromatography is limited by throughput and requires labor-intensive sample preparation processes. Magnetic beads-based purification permits the incubation of the beads directly into cell culture or crude lysates regardless of sample volume. This provides a simplified approach to direct target capture while minimizing preparation steps and potentially improving the quality of final product. The tools and their application to simplify protein purification, screening cost-effectively will be described.

Genetic engineering of proteins from the classical secretion pathway (CSP) is an alternative for obtaining CHO cell clones with enhanced productivity. However, few CSP targets have been detected from homogenates in previous differential proteomic studies. Hence, we used subcellular proteomics to intensify the identification of CSP proteins associated with cell productivity. Differentially expressed proteins (DEP) from this study participate in protein synthesis and translocation, autophagy, proteasomal degradation, calcium regulation, vesicular transport, ER stress and UPR. About 80% of DEP had not been associated with productivity and their further modulation could have a positive impact on bioprocesses. Supported by IN210419.

Decades of cell line development and media optimization of CHO cell lines has led to notable improvements in recombinant protein (rProtein) production yield.  However, the expression of some rProteins results in little to no yield and remains a challenge.  Our lab has taken a systems biology approach, including machine learning and network analyses, to elucidate host and protein-specific properties that act as determinants of rProteins yield in CHO.

Process intensification strategies in CHO production cultures can potentially increase productivity, lower cost of goods, and improve facility utilization. However, process intensification often triggers apoptotic cell death in the later phases of intensified production process. Here we show that apoptosis-resistant CHO cell lines counteract this undesired outcome, resulting in not only better viability but also enabling extended productivity that significantly improve volumetric productivity without affecting product quality.

With the aim of increasing protein productivity, we generate a novel CHO host with favorable biomanufacturing phenotypes and improved functionality. Producer pools and clones generated from the new host outperformed the standard host by displaying (1) improvement in productivity, (2) reduced product aggregation, (3) enhanced cell viability, (4) low lactate production and (5) improved cell cloning efficiency. Proteomics and western blot analysis demonstrate that the new host acquired multifaceted protection against mitochondrial dysfunction and ER stress.

The control of nutrient availability is critical to large-scale manufacturing of biotherapeutics. Genome-scale metabolic modeling offers a promising approach for in silico monitoring and predicting the consumption of proteinogenic amino acids, which is critical for bioprocess control. However, the prediction accuracy is challenged by the discrepancy between the model assumption and the biological variances in CHO cultures. We demonstrate such challenge can be addressed by integrating a CHO-specific metabolic network model with machine learning to achieve accurate prediction throughout the fed-batch process.

Industry 4.0 can potentially revolutionize biomanufacturing. Digital twins, virtual copies of a process interacting with the process, will play an important role in this transformation. This talk has focus on understanding the needs and challenges faced by the biomanufacturing industry when dealing with this digitalized paradigm. Two major building blocks of a digital twin, data and models, are highlighted. Data characteristics and collection strategies are examined, and new methods and tools for data processing are highlighted. Furthermore, different modelling approaches are presented in view of their use in a digital twin. Potential roadblocks for digital twin implementation are discussed.

We are building higher-throughput, multi-host system, mid-scale, protein expression and screening platform to accelerate drug discovery research at Genentech. This platform is built to perform quick triage of challenging recombinant proteins for structural and biochemical screens. Our semi-automated workflow leverages affinity in tip technology and size exclusion chromatography integrated with liquid robotic handlers to purify multiple samples in parallel. It provides small but sufficient quantities of high-quality proteins to screen for druggability assays and structural determination.

Cell clarification represents a major challenge for processing suspensions with very high cell densities. By using high-capacity protein A magnetic beads, we have developed an integrated affinity process where cell clarification and antibody recovery is performed in a single step. Using this approach on suspensions with 100 million cells/ml, we achieve adsorptions larger than 95% and yields over 90% with a logarithmic host cell protein clearance of 2–3 and resulting HCP concentration of 5 ppm. Scalability of the magnetic bead-based process from lab to pilot scale is also demonstrated.

Lead strain selection is a critical step during microbial process development, initially based on product titer because product quality evaluations are challenged by the timely availability of sufficiently purified material. The capability of a well-proven E. coli expression platform has been enhanced through the use of a scale down/high throughput approach to protein purification using robotics, to enable strain selection based on parallel evaluation of product titer and quality.