A quality-by-design approach to improve process understanding and optimise the production and quality of CAR-T cells in automated stirred-tank bioreactors.

Ex vivo genetically-modified cellular immunotherapies, such as chimeric antigen receptor T cell (CAR-T) therapies, have generated significant clinical and commercial outcomes due to their unparalleled response rates against relapsed and refractory blood cancers. However, the development and scalable manufacture of these novel therapies remains challenging and further process understanding and optimisation is required to improve product quality and yield. In this study, we employ a quality-by-design (QbD) approach to systematically investigate the impact of critical process parameters (CPPs) during the expansion step on the critical quality attributes (CQAs) of CAR-T cells. Utilising the design of experiments (DOE) methodology, we investigated the impact of multiple CPPs, such as number of activations, culture seeding density, seed train time, and IL-2 concentration, on CAR-T CQAs including, cell yield, viability, metabolism, immunophenotype, T cell differentiation, exhaustion and CAR expression. Initial studies undertaken in G-Rex® 24 multi-well plates demonstrated that the combination of a single activation step and a shorter, 3-day, seed train resulted in significant CAR-T yield and quality improvements, specifically a 3-fold increase in cell yield, a 30% reduction in exhaustion marker expression and more efficient metabolism when compared to a process involving 2 activation steps and a 7-day seed train. Similar findings were observed when the CPPs identified in the G-Rex® multi-well plates studies were translated to a larger-scale automated, controlled stirred-tank bioreactor (Ambr® 250 High Throughput) process. The single activation step and reduced seed train time resulted in a similar, significant improvement in CAR-T CQAs including cell yield, quality and metabolism in the Ambr® 250 High Throughput bioreactor, thereby validating the findings of the small-scale studies and resulting in significant process understanding and improvements. This study provides a methodology for the systematic investigation of CAR-T CPPs and the findings demonstrate the scope and impact of enhanced process understanding for improved CAR-T production.

Progress toward forecasting product quality and quantity of mammalian cell culture processes by performance-based modeling.

The production of biopharmaceuticals requires highly sophisticated, complex cell based processes. Once a process has been developed, acceptable ranges for various control parameters are typically defined based on process characterization studies often comprising several dozens of small scale bioreactor cultivations. A lot of data is generated during these studies and usually only the information needed to define acceptable ranges is processed in more detail. Making use of the wealth of information contained in such data sets, we present here a methodology that uses performance data (such as metabolite profiles) to forecast the product quality and quantity of mammalian cell culture processes based on a toolbox of advanced statistical methods. With this performance based modeling (PBM) the final product concentration and 12 quality attributes (QAs) for two different biopharmaceutical products were predicted in daily intervals throughout the main stage process. The best forecast was achieved for product concentration in a very early phase of the process. Furthermore, some glycan isoforms were predicted with good accuracy several days before the bioreactor was harvested. Overall, PBM clearly demonstrated its capability of early process endpoint prediction by only using commonly available data, even though it was not possible to predict all QAs with the desired accuracy. Knowing the product quality prior to the harvest allows the manufacturer to take counter measures in case the forecasted quality or quantity deviates from what is expected. This would be a big step towards real-time release, an important element of the FDA's PAT initiative.

Advanced online monitoring of cell culture off-gas using proton transfer reaction mass spectrometry.

Mass spectrometry has been frequently applied to monitor the O2 and CO2 content in the off-gas of animal cell culture fermentations. In contrast to classical mass spectrometry the proton transfer reaction mass spectrometry (PTR-MS) provides additional information of volatile organic compounds by application of a soft ionization technology. Hence, the spectra show less fragments and can more accurately assigned to particular compounds. In order to discriminate between compounds of non-metabolic and metabolic origin cell free experiments and fed-batch cultivations with a recombinant CHO cell line were conducted. As a result, in total eight volatiles showing high relevance to individual cultivation or cultivation conditions could be identified. Among the detected compounds methanethiol, with a mass-to-charge ratio of 49, qualifies as a key candidate in process monitoring due to its strong connectivity to lactate formation. Moreover, the versatile and complex data sets acquired by PTR MS provide a valuable resource for statistical modeling to predict non direct measurable parameters. Hence, partial least square regression was applied to the complete spectra of volatiles measured and important cell culture parameters such as viable cell density estimated (R² = 0.86). As a whole, the results of this study clearly show that PTR-MS provides a powerful tool to improve bioprocess-monitoring for mammalian cell culture. Thus, specific volatiles emitted by cells and measured online by the PTR-MS and complex variables gained through statistical modeling will contribute to a deeper process understanding in the future and open promising perspectives to bioprocess control.