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Dispatches from the 1st Stem Cell Community Day, Hamburg

UK Catapult: QbD and process automation key for making commercial cell therapies

Dan Stanton

By Dan Stanton+

05-Apr-2017
Last updated on 05-Apr-2017 at 11:23 GMT2017-04-05T11:23:08Z

Image: iStock/JVisentin
Image: iStock/JVisentin

Process automation should be incorporated early when developing large scale cell therapy manufacturing platforms, according to a lead scientist from the UK Catapult.

For the increasing number of stem cell therapies and regenerative products in development, there are a range of tools and equipment available for production at laboratory-scale, but industry lacks standard controlled, robust, reproducible and cost-effective methods for larger – and potentially commercial – volumes.

The 1st Stem Cell Community Day, organised by Eppendorf, took place in Germany on Wednesday bringing together a series of projects from industry and academia looking to address this issue.

There are problems and bottlenecks across all areas of pluripotent stem cell production, from the process itself, to the quality, regulatory, clinical and logistics space, but one major way to overcome these is in process automation, according to Ricardo Baptista, a lead scientist in the Process Development Team at Cell Therapy Catapult, UK.

“Process automation is a key aspect to industrialise the manufacturing of pluripotent stem cell derived therapies and should be incorporated in the early stages of process development,” he told the audience in Hamburg.

Quality by Design

He added the process should be viewed from an end-to-end perspective, rather than by individual unit operations, and stem cell manufacturers must also take into account such things as the reagent supply chains, and the cold supply chain to avoid bottlenecks.

“Our strategy is to use a structured process development focusing on high priority areas, the goal is to reduce the risks of failed GMP manufacturing, and to reduce the costs of manufacture,” he said, adding the UK’s Catapult uses a series of diagnostic tools as part of it working to quality by design (QbD) principles.

These include knowledge and design space understanding (process mapping), failure modes and effects analysis (FMEA), root cause and effect analysis, and cost-of-goods (CoGs) modelling.

Such tools, he continued, help set important outputs – critical process parameters, critical quality attributes, control measures and risk mitigation strategies, reagent quality and sustainability etc – early on in the process, protecting against problems further on in the scale-up.

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