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The projected growth in the biosimilars market will require increased bulk mAb manufacturing.
With biosimilars entering the market, and more expected to reach the market in the near future, the need for good manufacturing practice (GMP) compliance is growing more crucial for bulk monoclonal antibody (mAb) manufacturing. Beyond innovator biologics, biosimilars are expected to account for much of the bulk mAb manufacturing in the future. The global biosimilars market is projected to grow at a compound annual growth rate of 23.5% from 2021 to 2026 and is expected to reach $44.7 billion by 2026, up from $15.6 billion in 2021 (1). The growth of biosimilars is attributed to the rise in chronic diseases and demand for less costly therapeutics.
Although commercial manufacturing of mAbs has been streamlined over the years due to advancements in technology and the continual evolution of regulatory understanding for these compounds, the complex nature of antibodies still presents challenges for biopharma companies as well as development partners, points out Carrie Mason, associate director, Biologics R&D PAT/Automation, Lonza.
The production of mAbs involves highly complex biological processes that require strategic supply chain management and deep theoretical and working knowledge of the antibody. Because of this, building and investing in facilities specialized in the manufacturing process can be resource-intensive; thus, choosing the right development partner is critical to the success of that antibody therapy, Mason explains.
“There are challenges and limitations when manufacturing monoclonal antibody doses. One limitation is that it is dependent on how much the bioreactors can produce and the dosage needed for the final product. As an industry, we are striving to increase titer output from bioreactors, increasing productivity to meet rising demands. However, the challenge faced by continued intensification is product quality. Ensuring that the product continues to be consistently expressed and recovered in the desired structure can be challenging,” says Mason.
Other examples of challenges during the production of recombinant products, including mAbs, include timely delivery, review, and integration of processing data generated by a diverse set of manufacturing operations, adds Christopher Kistler, principal scientist, Biologics Product Development, Catalent Biologics.
Kistler points out that the data operations in mAb production can pose a challenge because information needs to come from connected online systems, including bioreactor control systems, non-connected systems—such as laboratory information management system (LIMS) repositories—and from manual operations where data are locally recorded in documentation. “All data need to come together to enable real-time processing decisions across these diverse unit operations, and delays due to offline analytical testing can result in long intermediate hold times that place stress on even the most robust processes,” he states.
Stability is also a key challenge faced during the bulk manufacture of mAbs, emphasizes Mason. The initial challenge in terms of stability is glycosylation and how to control it during manufacture. Ensuring the correct glycosylation is critical, Mason confirms. “Glycosylation is a complex process susceptible to changing process variables, and challenges arise with creating enough data to characterize a process. Existing testing methods for glycosylation can be time-consuming and resource intensive,” she says.
Another factor in ensuring the stability of the mAb product is what happens to that product outside of the laboratory, such as during its journey from the clinic to the doctors and patients. “The methods for how protein-based therapeutics are stored, distributed, and administered can affect stability, and, unfortunately, there is little research on stability outside of manufacturing sites,” says Mason. “To help solve this, Lonza participates in the Real-World Handling of Protein Drugs—Exploration, Evaluation, and Education (RealHOPE) project to identify critical factors contributing to protein instability during handling and use [those factors] as a starting point to improve testing during drug development and improving the education on its handling by the clinicians and/or patients.”
The implementation of process analytical technologies (PAT) has become standard in many biopharmaceutical development programs these days. Furthermore, technology partners have incorporated analytics into more process equipment, remarks Mason. In mammalian cell culture, for example, screening and optimization tools are more widely used both in clonal cell line development and in cell culture. Such tools aid in accelerating the time to clinic for high yield, robust processes.
“Single-use technologies are playing a more important role in both small molecules and biologics. In combination with closed process systems and ballroom processing concepts, facilities can be configured for concurrent manufacturing. In antibody production, for example, these technologies allow a company to configure processes from standard to next-generation formats such as bi-specifics or to process high titer or other challenging processes,” Mason says.
PAT has improved many areas across the process of recombinant protein manufacture, notes Kistler. The tools that are now available serve to reduce the impact of manufacturing deviations through either accurate automated process control, or through use as an analogous analytical method, he explains. “In the second scenario, the time required to investigate and close a deviation is reduced, freeing facility staff to work on other priorities,” Kistler says.
“Incorporating PAT into downstream development affords greater understanding of a process, which gives greater opportunity for optimization and ensuring it is robust when transferred into manufacturing,” adds Marcia Kary, principal scientist, Biologics Product Development, Catalent Biologics.
One strategy that has thus far been successful in improving process control over bulk mAb manufacturing is the quality-by-design (QbD) approach. QbD can be used to identify optimal process controls that can be used for consistent manufacture.
“QbD takes into account large amounts of data to create processes optimized for the best results, and it is aligned with regulatory and
industry efforts to ensure efficiency, safety, and quality of medications. This strategy enables us to identify and optimize robust process controls to boost the bulk manufacture of mAbs and consistently create quality products,” says Mason.
Mason notes that Lonza is currently working to create a moderative controller to directly influence glycosylation for mAb manufacturing. “With access to a treasure trove of data, we are generating a case study that will allow the consistent reproduction of a specific amount of glycosylated antibody that can be used for a whole panel of attributes that control the quality of the antibody,” she explains.
The company can thus create a high degree of predictability across several quality attributes, which allows it to identify and select specific quality attributes in the product that can be maximized for consistent commercial manufacture of mAbs; this, in turn, benefits the patient, Mason reveals.
Kistler, meanwhile, points out that a powerful strategy is to forward-leverage prior platform knowledge, which he says links well into QbD approaches. “Lessons learned from experience with analogous molecules and processes can reduce the risk of unfavorable process control outcomes, which is especially useful for projects that are on an accelerated timeline,” he states.
Challenges in bioprocessing can still limit effective process control in mAb manufacturing. Real-time monitoring of bioreactor feed components and metabolites remains challenging, for instance, Mason remarks. She further points out that developing models requires large datasets for multi-variable data analysis (MVDA), and the need for a quantitative database for modeling depends on PAT tools. “Advancements need to be made in the development and implementation of more complex PAT solutions,” she states.
Kary suggests that increasing real-time monitoring of critical quality attributes and process parameters with in-line and on-line modes of analysis would improve process control, reduce risk, and provide a higher assurance of product quality. “Currently, there are few analytical tools available for real-time monitoring of the product quality profile early in a manufacturing process, and often product quality attributes are only measured following a purification step, or as a final step in release of a bulk drug substance lot,” Kary says.
“Technologies and approaches that minimize the impact of material storage in a facility would be useful in further streamlining mAb manufacturing processes,” adds Kistler. Examples of useful technologies could include technologies that accelerate the pathway for raw material release and use in processes, Kistler continues.
“The same would be true for single-use component supply chains. Finally, technologies that enabled optimized and lean storage of bulk material following release and prior to further processing or shipment can help streamline the process,” Kistler states.
As the industry moves towards more automated processing based on PAT feedback, it is expected that throughput will continue to increase, concludes Mason, who notes that taking advantage of PAT and more MVDA modeling, including downstream processing, will make strides toward overcoming the current throughput challenges.
1. Markets and Markets, Biosimilars Market by Product (Monoclonal antibodies (infliximab, rituximab, trastuzumab), Insulin, Interferon, Etanercept, Glucagon, Calcitonin), Indication (Oncology, Chronic Disease, Blood Disorder, Autoimmune Disease), Region—Global Forecast to 2026, Market Research Report, September 2021.
Feliza Mirasol is the science editor for BioPharm International.
Vol. 35, No. 9
Pages: 20–22, 44
When referring to this article, please cite it as F. Mirasol, “Streamlining Bulk mAb Manufacturing,” BioPharm International 35 (9) 20–22, 44 (2022).