Making cell therapies comPATible with large scale manufacturing

Process analytical technologies (PATs) cover a wide range of tools, playing an important role in initiatives such as quality by design (QbD), real-time release, and continuous manufacturing [1]. They are already widely utilized in pharma and biopharma manufacturing, and for the large-scale deployment of cell therapies, they are critical to ensure:

  • Safety – Maintains a consistent process and product quality through in-line and on-line monitoring and analysis
  • Speed – Allows insights into the process helping accelerate R&D and process development, especially when couple with data analytical tools
  • Cost-effectiveness – Insights into culture throughout the process can help optimize reagent usage, reduce process duration, and lower batch failure rates

During process development, many parameters need to be measured across hundreds of experiments to identify the critical process parameters (CPPs) and critical quality attributes (CQAs) required for the desired cell product. Without PATs, this turns into an intractable (both costs and logistics-wise) amount of sampling and manipulation, and an enormous amount of Capex for analytical equipment.

Common parameters measured during process development include:


  • pH
  • Dissolved O2
  • Temperature
  • Dissolved CO2
  • Metabolite concentration
  • Amino-acid concentration

End of process

  • Cell count
  • Cell viability
  • Phenotyping
  • Karyotyping
  • Potency assays

At manufacturing scale, CPPs and CQAs need to be measured constantly to demonstrate batch safety through quality control. With hundreds of thousands of patients per year who could benefit from cell therapies, maintaining the current practices of manually sampling and analysing swathes of data will become commercially and logistically unviable.

So how can you implement PATs into the cell therapy manufacturing process?


Online automation allows for multiple measurements to be taken in parallel, avoiding the need for sampling. For example, using specialist microscopes coupled with trained algorithms next to a bioreactor can supply increasingly accurate cell count and viability measurements, with fluid loops from the bioreactor maintaining a closed culture system. MicrofluidX has gone one step further, directly implementing microscopes on their bioreactor thanks to their bioreactor form factor.

If there isn’t capacity for online measurements, automation can be harnessed in other ways to save time and reduce manual handling, like automating sample prep for flow cytometry.


All these PATs can add up when running multiple bioreactors in terms of costs, space, validation requirements, logistics and maintenance. This is why mutualization is key, and it can be done in a few ways. Robotics can manage the movement of bioreactors to and from pieces of analytical equipment in closed systems, while autosamplers can manage the movement of samples from different bioreactors to one piece of analytical equipment. This drastically decreases Capex, increases productivity of your equipment, and removes variability from manual handling.

At MFX we combine all these approaches to deliver a cost-effective, analytically driven bioreactor platform. Our Cyto Engine™ can be deployed in both process development and large-scale manufacturing. 

[1] Clegg, I. 2020. Specification of Drug Substances and Products, Second Edition. Elsevier, pp 149-173