Cell therapy developers need purpose-built process monitoring technologies, according to researchers who say better systems would accelerate manufacturing and reduce costs. The conclusion is based on a study that looked at the use of process analytical technology (PAT) in cell therapy manufacturing. The key finding was that the lack of bespoke systems means many developers continue to rely on platforms designed for large-molecule drug production.
This is a problem because cell therapies are much more complex than protein therapeutics, notes Krishnendu Roy, PhD, director, NSF Engineering Research Center (ERC) for Cell Manufacturing Technologies (CMaT) at Georgia Tech.
“In biologics or monoclonal antibodies, the product is a singular well-defined entity. Cell therapies are living products that change with every manipulation,” he tells GEN. “A cell has thousands of proteins, RNA, lipids, carbohydrates–any combination of which can be the CQAs [critical quality attributes], and simple changes in processes affect properties and behavior of the cells. This complexity makes it much harder.
“Current analytical technologies are inadequate. We need PATs to be tailored for cell manufacturing.”
Instead, the cell therapy industry requires technologies that are able to track multiple parameters in real-time at every stage of development and production, explains Roy.
“PAT, especially multiplexed systems capable of sensing of many parameters at or in process during the discovery and process development stages, would allow us to learn every detail of how the cells are behaving, their differentiation and growth trajectories. and how process parameters affect the cells and the end product,” he continues.
“Later, once we understand a set of CQAs or CPPs [critical process parameters], only a few things need to be measured at the manufacturing stage to ensure that the process is behaving as expected or if any process control/changes are needed to keep the end product within CQA limits.”
In the study Roy and his co-authors suggest developers and technology suppliers work together to incorporate novel sensor technologies and machine learning into PAT methodologies.
“Advances in PATs are necessary to identify CQAs and CPPs, overcome limitations in current operating processes, reduce overall product cost, and significantly accelerate the translation of laboratory discoveries into commercialized cell therapy products,” says Roy, who adds that there are encouraging signs industry is beginning to act. “Many new PAT companies are already forming which partner with research consortiums and therapy companies.”
One such example is the group set up by Cell and Gene Therapy Catapult in June. The project, which brought together 20 pharmaceutical companies, technology providers, therapy developers, and charities, is designed to assess the application and combination of multiple technologies for process analytics within the cell and gene therapy industry.