Why you should be automating your ATMP QC assays
Somatic ex-vivo gene therapy products are an emerging class of living cell-based therapies that have come to prominence thanks to the approval of two CD19 CAR T products: Kymriah and Yescarta.
As opposed to allogeneic cell therapy or even a traditional biologic such as a monoclonal antibody (mAb), these products are made on a per-patient basis with patient demand being matched through a scale-out and not a traditional scale-up model. This has resulted in a high cost of goods for the production of these living therapies, a technical risk that compounds the already significant market risk of these products.
Controlling the per batch cost of manufacturing (to enable wider payor adoption) has thus moved areas such as Chemistry, Manufacturing and Controls (CMC), and Quality Control (QC) to the fore. Cell and gene therapy companies have a need to increase production output (without increasing facility footprint), maintain quality, and reduce costs. If they are unable to address these issues, the market has already observed the outcomes. Dendreon, the now defunct creator of Provenge, at one point, was running an unsustainable Cost of Goods (CoGs) of 77%, compared to a CoGs of approximately 10% for a mAb.
The literature around CoGs in cell therapy production indicates that the cost of producing a single batch of genetically modified patient material will be between $50,000 - $100,000 USD, with approximately 50% of the total cost coming from full-time employee (FTE) and QC/QA costs ($25,000-$50,000), with 20% of this cost bracket coming from QC ($5,000-$10,000, 10% of total CoGs).
As autologous products are made with donor material, their manufacturing process must account for high donor variability to deliver the desired target product profile (TPP). The quality of the cell therapy product against its TPP is assessed using predetermined critical quality attributes (CQAs), which in turn are measured via a variety of different analytical methods. The importance of rigorous QC has introduced the aforementioned FTE cost into the manufacturing process and with high competition for the talent required to operate in a regulated cell therapy QC environment anything companies can do to move towards an autonomous 24/7/365 facility operation is going to deliver benefit to patient and payer.
One solution is analytics automation. Using ‘open and static’ or ‘bolt together’ solutions for analytics automation will allow cell therapy QC teams to increase throughput, reduce FTE cost and avoid excessive CapEx (e.g. by having to construct new facilities). These solutions should also be flexible, allowing companies to scale/descale for variances in patient demand.
So what QC assays should you look to automate now?
Despite there being a number of CQAs and a variety of techniques to measure them (Table 1), in our experience, it’s invariably the same 3 release assays that come up each time: qPCR, ELISA and flow cytometry.
By introducing analytics automation for these 3 methods, throughput can be increased, and QC cost decreased.
