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Process Intensification in Animal Cell-based Vaccine Manufacture

William G. Whitford
BioContinuum™ Seed Train Platform

Vaccine Manufacturing

The industry is experiencing an acceleration in the development and approval of novel prophylactic and therapeutic vaccine modalities. Concurrently, many biopharmaceuticals are experiencing the benefits of manufacturing process intensification (PI). Describing such advances for cell-culture based processes is challenging in the field of vaccinology because of the number of vaccine types, innovative delivery and adjuvant systems, and production platforms.1 Restricting ourselves to cell-based manufacturing yields a diversity of platforms, from E. coli to yeast to animal cells. Further restriction to only animal cell-based production still includes such distinctions as classical vs single-use, suspension vs. adherent, and fed-batch vs. perfused continuous platforms. Even adherent culture is performed in a variety of formats, including stacked array flasks, roller bottles, and macro- and micro-carrier fabric or beads, as well as moving and fixed-bed bioreactors. So, there is a large and growing number of methods to produce vaccines in the large-scale culture of diverse cell types.

Common vaccine processes requiring cultured animal cells include production of primary antigenic materials, attenuated viruses, vectored vaccines, virus-like particles, plasmid templates and other structures to deliver the antigens or nucleic acids. Mammalian-cell based systems producing over 40 different viral vectors have been described. While adenoviruses and modified vaccinia Ankara viruses have been common, adeno-associated viral (AAV) vector technologies to become popular to deliver, e.g., genetic sequences of the SARS-CoV-2 Spike antigen inducing an immune response to the coronavirus.

Process Intensification

There has been a great expansion of bioprocess science and technologies supporting these manufacturing process intensification efforts, ranging from advances in cell biology understandings to the revolution in “Pharma 4.0” digital technologies.

Some use the phrase “process intensification” to include increases in many things, such as product quality. Here we use the phrase to refer only to improvement in productivity by producing more product per such metrics as cell, time, volume, footprint, or costs.

The vaccine industry is now facing such challenges as delivering new therapies faster than ever and fulfilling the huge global demand by increasing manufacturing capacities and improving titers and yields. PI, especially in upstream processing, is a component of the high yields and titers, process robustness, consistent product quality, rapid turn-around process times, and scalability required to achieve product success. Martin Friede, coordinator of the Initiative for Vaccine Research at the World Health Organization (WHO) has remarked “Process intensification has the potential to make vaccines and biologicals production cheaper by orders of magnitude.2, 3

Many aspects of the intensification of cell-based vaccine manufacturing are coincident with that of any large-scale biomanufacturing. Yet, there are some distinctions, such as the fact that some virally infected cultures display a heightened or unique metabolite requirement, or that some viruses require such special culture media components for activation.

Intensification Techniques

Digitally enabled asset performance management (APM) and enterprise resource planning (ERP) are integrated management tools providing a comprehensive view of asset and operational performance, leading to better control over production while minimizing costs and risk.

The “rational design” engineering of a null cell-line, such as a manipulation of outputs (e.g., transcripts) or gene contexts (e.g., epigenetic markers) in popular platforms improves such phenotype as peak cell density, culture duration, production at high cell densities, maintaining correct transcript post-translational (PT) modifications and folding, and reducing the emergence of non-producer mutants.

Two clear examples of process simplification supporting a reduction in process footprint are the cryopreservation of high volume or high cell-density working stocks, as well as employing intensified perfusion in the seed train. Both of these can even support the skipping of an entire n-X culture cycle.

BioContinuum™ Seed Train Platform
BioContinuum™ Seed Train Platform - Courtesy of MilliporeSigma, the life science business of Merck KGaA, Darmstadt, Germany and / or its Affiliates – All rights reserved

While promoted for many other values, various approaches to continuous bioprocessing can also dramatically increase productivity in terms of time, volume, and footprint. Modifying media composition, operating cell density, perfusion rate and culture duration in existing perfusion modes can provide further improvements.

PI through selection of the most appropriate bioreactor, process mode and control system is becoming more challenging. There were previously only a few, rather intuitive approaches − but even in examining stirred-tank suspension culture approaches, there are now many configurations to choose from. And other bioreactor types, such as fixed bed and hollow fiber do present even more options4

After a decade of success in other industries, we now see “digital” approaches in vaccine manufacturing taking hold. This industry has recently seen such early “Pharma 4.0” initiatives as autonomous warehouses, paperless data recording, and electronic batch records. New data sources, as well as their means of transmission, storage, and curation are maturing rapidly. Current PI-related digital tools in vaccine manufacturing includes connectivity through industrial internet of things (IIoT), and eventually through the internet of everything (IoE).5

Supervisory control and more powerful data acquisition are supporting model-based adaptive control systems addressing many variables and actuating dynamic changes in new output variables. New artificial intelligence (AI) applications are further empowering PAT and QbD in harnessing the massive amounts of process data generated by new probes, sampling technologies, monitoring instrumentation, as well as automated high-throughput and multiplexed analytics.

“Digital twins” are in-silico model providing a digital transformation of each operation− supporting, analysis, prediction, control, and optimization of the manufacturing process. AI and machine learning will soon interface with them to provide novel solutions to complex problems, even with less than optimally governed and labeled data. It will make appropriate decisions for bioprocess development, predictions, recommendations, and control using advanced monitoring, big data processing capabilities and new industrial connectivity.

The speed and power of data processing hardware, as well as the capability of new optical, chemical, and physical sensors continue to grow. Improvements in the monitoring of existing parameters, and well as entirely new ones are being enables by such powerful developments as capillary electrophoresis integrated mass spectrometry,6, 7, 8, 9 monolith immobilized enzymes providing on-line digestion of proteins, 10 and smart sensors converting surrogate measurements to functional values in silico.11

In process development activities for intensification, there is growth in the use of automated parallel microbioreactor systems capable of running as either high inoculation fed batch and or as perfusion mimics. Developments in clone selection techniques include new criteria, such as culture behavior and robustness in the actual production media and mode, and the early use of product quality profiling. Cloning, cell-line development and gene editing are being advanced greatly through new applications of microfluidics.12

Finally, qualified vendors of facility design and build now specifically support many of the intensification initiatives mentioned above, integrating laboratory information management systems (LIMS) with enterprise resource planning and control. Orchestration of such digital technologies as cloud- and edge-based systems, process automation, and AI supports advanced production layouts. This, as well as features of modular and prefabricated design, enable both process flexibility and intensification in a data-intensive landscape.