Novel technologies are available for continuous monitoring of cells without the need for extensive labelling. Different optical and dielectric methods will be explored in this presentation to show the potential of each method to distinguish cells at different states of metabolism as they progress through a bioprocess. These include the use of a capacitance probe which allows data to be obtained at a single frequency or through an automated frequency sweep. This may complement digital optical imaging of cells in which critical morphological changes can be analysed. These methods allow fine control during biopharmaceutical production processes.  

Cellular therapies and regenerative medicine have progressed significantly over recent years, introducing novel methods of clinical intervention to replace, repair or restore the lost function of tissues and organs. The integration of life sciences and engineering tools as bioreactors would allow the translation from the concept of a medical intervention in a complex disease scenario to the manufacture of safe and effective innovative medicinal products.

An improved understanding of the cultural environment within bioreactors is essential for developing robust, high-yielding processes. We will explore the usage of advanced process control and predictive modeling in mammalian cell cultures to automate and optimize bioreactor feeding and control strategies. A series of case studies will cover topics including utilizing integrated PAT tools for automated at-line feeding and using machine learning to control and refine bioreactor set points.

We present a methodology for building robust and predictive Raman models for closed-loop control of key CHO cell culture parameters. Our approach relies on the generation of data by the Cell Culture Development team (USP) who communicates them to Non-Clinical Biostatistics team leading to the building and the strengthening of Raman models. Our objective is to implement Raman spectroscopy in production process development.

Initial process development was performed in bench-scale and Ambr bioreactors, designed to select suitable clones in terms of productivity but also in robustness and shear stress sensitivity, tested via high agitation rate and sparging. Yet, a significant loss in performance was observed while scaling up. A series of bench-scale experiments were performed to understand these observations and fine-tune the process, which was then confirmed at scale before being transferred to manufacturing.

Research shows that dissolved CO₂ (DCO₂) is a bioprocess Critical Process Parameter (CPP). Its active control increases viability and product yield. It improves consistency of process scale-up and scale-down across R&D, Pilot and Production scale reactors: real-time control of DCO₂ will result in comparable mass transfer independent of scale. The Hamilton CO2NTROL Solid State Sensor technology provides the most accurate and maintenance-free solution for real-time in-line control of PAT CPP.

Direct measurement of Product Quality Attributes (PQAs) and spent media information can now be offered with dedicated workflows coupling bioreactors like the Sartorius Ambr 15 or 250 systems to the Waters BioAccord LC-MS system.

Process engineers have access to the information they need; drug substance quality and yield can be maximized, and downstream impurities minimized. This ultimately results in accelerating development from weeks to days, saving resources from multiple optimization cycles.

Sufficient process understanding in the QbD concept is a cumbersome task. Hybrid modeling and advanced design space screening methods reduce the required experimental effort to reduce overall development timelines. Conserving process understanding and learning in these models enables model transfer from early-stage development until manufacturing. The presentation will cover model-assisted process characterization, process optimization, implementation of soft-sensors, and a concept for implementing model predictive control highlighted on bacterial and CHO bioprocesses.

Bioprocess 4.0 demonstrates the need for process intensification, real-time data acquisition, and predictive modeling. While real-time measurements are currently available for many critical parameters, monitoring the extracellular environments to assess cell metabolism and create predictive models still suffers from a lack of relevant data. At-line MS-based technologies presented here provide key cellular metabolic insights when you need them.

Among the most decisive parameters for keeping a certain process performance across scales are the viability and vitality of the microbial hosts. Therefore it is important to keep cell physiology parameters and population heterogeneity constant across scales in order to achieve one of the pre-requisites for similarity. The talk will summarize recent advances in single-cell technologies and their value for process optimization, scale up and scale down. Relations between the process performance and population measures are demonstrated for microbial cultivations under stress conditions. Perspectives for applying this data for improved process control and prediction are discussed.

Given time & cost pressures, miniaturized high-throughput devices that are representative of a specific production process part are increasingly being used in pharma. We showcase how we developed a Digital Twin (DT) solution for the ambr250 perfusion bioreactor system. We show how we addressed the challenges in terms of experiment design, data acquisition, model development and connectivity we faced during the DTs development and how we overcame them.

The production of mRNA vaccines in a rapid, responsive, and scalable manner has become crucial since the emergence of the COVID-19 pandemic. This presentation will give an overview of the synthesis and purification process around production of RNA vaccines, before moving on to look at a case study.

The pharmaceutical industry needs to stay competitive; this means (i) processing more projects with lower budget and (ii) more aggressive timelines. The industry therefore applies their historical process knowledge in combination with novel technologies (predictions etc.). This presentation shows as a case study how we can unlock the full potential of our data treasure by tearing down the data silos of different departments. The application of data lakes and harmonization of data enable scientists to get easy access to data and work on more value-adding activities. Furthermore, the connection of innovative web UI software with the data lake will be presented.

Recombinant adeno-associated virus (rAAV) can be efficiently produced on a large scale using the insect cell-baculovirus expression vector system (IC-BEVS). We implemented three real-time monitoring tools for an rAAV production process in the IC-BEVS: fluorescence spectroscopy, digital holographic microscopy, and dielectric spectroscopy. Here we present the modeling strategies applied to develop prediction models for process variables and increase process understanding, supporting Process Analytical Technology (PAT) initiatives.

Long-term storage of cell culture media at room temperature is currently limited by their instability and change in color. One of the critical contributing factors toward media browning is tryptophan. LC-MS technology was utilized to identify tryptophan degradation products, which were shown to contribute significantly to color in solutions but also to exhibit toxicity against CHO cells. A cell-culture-compatible antioxidant, a-ketoglutaric acid, was found to be an efficient additive for stabilizing components against degradation, thus providing a viable method for developing room-temperature stable cell culture media.

Clonal derivation is an essential quality attribute of a Master Cell Bank that is to be used for therapeutic purposes.

This presentation will explore how  a range of single cell cloning methods are impacted by differences in the inherent nature of CHO, HEK and iPSC cells.

Data will be presented from both a cloning efficiency and clonality assurance perspective

CHO cell line selection is a painful bottleneck in biotherapeutic development, particularly for complex molecules like bispecifics. The Opto™ CLD workflow on the Beacon® system accelerates early CLD by integrating high throughput cell sorting, cloning, culture, productivity, growth, and product quality assays into a single, 5-day automated process. Hear about capabilities of on-chip detection that pinpoints best clones early on.