Leveraging Automation To Drive Down Costs For Cell Therapy Production

By Life Science Connect Editorial Staff

The need for greater standardization and automation is a critical driver of innovation for the evolving cell therapy landscape. Implementing more automated workflows in cell therapy manufacturing can serve to minimize open processes and manual touchpoints, increasing reproducibility and improving traceability. This, in turn, has the potential to reduce manufacturing failures and lower the cost of goods sold, facilitating increased patient access.

In a recent installment of Cell & Gene Live, experts from pioneering cell therapy companies sat down to explore how the industry can improve scalability and cost through standardization and automation. Speakers for the event included:

• Craig Beasley, chief technical officer, BlueRock Therapeutics
• Narinder Singh, chief technical officer, Arcellx

Incorporating automation into a cell therapy workflow is a complex endeavor – determining the right technology approach for a unique therapeutic asset and working to mitigate risk when introducing automation to a workflow are crucial to achieving optimized, standardized manufacturing. Yet achieving key improvements to a workflow through automation can greatly improve the consistency of production, bolster a product’s safety and quality, and reduce rework and improve costs.

Breaking Down Automated Manufacturing

When it comes to CAR-T applications or other major cell therapy modalities, many organizations tend to focus on the individual steps within a manufacturing process. While working to optimize discrete process steps is important, achieving optimal scalability requires finding ways to perform some steps concurrently. By automating more standard activities, such as media preparation, companies can focus resources on more critical activities to facilitate the production of multiple lots. This increased capacity, coupled with the greater volumes of data automated instruments can yield, can help operators iterate on a process to achieve greater automation and optimization in the future. This will be key for cell and gene therapies that heretofore have relied on patient-specific batch manufacturing that is difficult to scale cost-effectively.

Despite the advantages automation can impart for a manufacturing process, the first step to realizing its full benefits starts with optimizing a product construct. Considering manufacturability from the get-go, often through establishing a research and process development partnership, can enable scientists to apply the right process-level strategies – including automation – to improve robustness and efficiency. Too many companies begin considering automation after having already locked in a process, which can raise new questions about comparability, facility footprint, media optimization, and other key considerations. Instead, by outlining a process’s potential failure points early, organizations can design within those ranges, enabling automation that fits within a process.

Testing automation is another important consideration for comprehensive workflow standardization. Automating sample retrieval and quality control testing can have significant impacts on cost, resourcing, and process flexibility. Evaluating and automating these workflow steps alongside others in the process can offer operators latitude on bottlenecks or otherwise time-sensitive steps. Equally important is evaluating supply chain considerations as they relate to automation – deciding later that electronic batch records tied to individual unit operations be made available for a larger supply chain, for example, can overwhelm a network and result in a 30-minute step taking hours.

In order to automate optimally, organizations must cultivate a deep understanding of the cost drivers and inefficiencies inherent to a process. Reducing the process cycle time for one process, for example, can positively impact plant capacity by a wide margin. Rightsizing that optimization can help operators achieve a “sweet spot” wherein the right changes, to the right degree, strike a balance between investment and return. Likewise, understanding the potential for variability across a range of considerations, from patient materials to reagents to the process itself, allows for a robust process capable of integrating automation solutions more seamlessly.

Technology Needs For Automated Manufacturing

Some organizations have begun working to standardize across certain common process steps, such as washing and expansion, which are likely to engender a larger shift for the industry. This shift will allow for greater focus on more detailed automation around product-specific steps, such as transfection.  Achieving more standardization for these baseline process steps requires a focus on improving the reliability of automated equipment – the highly bespoke nature of autologous cell therapies, for example, means that losing one lot and having to manufacture another from scratch can have serious consequences for a patient. This also requires a close examination of the data integrity of these instruments, which often have the potential to produce more and more detailed data than a more analog process.

Another key consideration for automated technologies is tied to closing processes. By closing systems where possible and enabling more reproducible materials transfer and handling, operators can greatly reduce contamination risk. Pairing this closed processing with more at-line analytics, as well as pursuing improving cryopreservation to enable more immediate freezing, will serve to safeguard cell quality and improve consistency for these fragile therapeutics. All of these variables must likewise be linked to scalability; for autologous applications, this means focusing on driving down processing time in order to facilitate the production of as many lots as possible within a fixed overhead. To this end, there are two areas positioned for immediate improvement: controlling raw material inputs to limit variability and moving toward achieving allogeneic production for these modalities.

Mitigating Risk In Process Automation

Scalability is important for more than just meeting market demand – done right, it can serve to minimize risk. Often, early development yields a process that is highly customized and reliant on academic laboratory strategies not designed to scale. The holy grail would be to define a construct for an allogeneic manufacturing process that meets the needs of an entire patient population and is poised to produce on demand. But the industry is still far from realizing widespread allogeneic manufacturing, making de-risking autologous applications crucial for the near term. Much of this risk assessment centers on minimizing variability for the patient materials, reagents, and media that go into a process; other considerations, such as operator-to-operator variability and the contamination risks associated with open processing, can be more easily addressed through automation solutions.

Automating the more repetitive unit operations in a workflow can also help improve consistency for the steps that still require manual manipulation. By allowing operators to focus on fewer steps requiring more expertise, programs can train more closely on more critical processes, as well as focus more on early intervention when processes deviate. This increased focus can, in turn, help inform technology improvements for suppliers, facilitating better automation and enabling its expansion into other unit operations as more basic ones achieve optimization.

Pipeline Progress

The degree of automation achievable for a workflow, as well as what that automation looks like, can vary widely depending on the modality or individual asset in question. Certain products cannot be transitioned, or transitioned easily, to suspension processes, for example, and the bulk of the automation for these processes therefore hinges on media handling and distribution. For processes that have been transitioned to suspension, more “classical” automation approaches may be achievable, such as measuring cell densities to determine an optimal feeding or harvest strategy. Other applications designed to enable a more “plug-and-play” approach may be able to work toward a more standardized, robust process from the get-go, so that a universal cell product can be adapted to unique proteins while having the necessary automation and efficiencies to accelerate a molecule to the clinic and the market while improving patient accessibility.

Auto, Allo, And AI

Not every aspect of cell therapy manufacturing today is ready for automation. Organizations should never seek to automate a bad process – that is, processing steps that are not fully understood and for which all significant variables have been outlined are not good candidates for automation. Other, very low volume steps that may have a tight window of process design space are unlikely to benefit from automation until the technologies supporting them improve. Ultimately, the goal of automating a process step is to simplify it and make it more scalable. As a result, this evaluation can be very different between autologous and allogeneic applications: automating visual inspection, for example, may streamline an allogeneic workflow, but for the small volumes and processing surrounding autologous applications, this type of automation is more likely to introduce unnecessary complexity.

Safety And Efficiency Of Source Material Collection

The automation potential for allogeneic and autologous processes can diverge greatly. This is especially apparent when considering source material collection, as allogeneic applications are again more likely to achieve a more simplified materials collection paradigm, owing to the comparative ease of donor material collection. For these programs, the greater focus is on clone selection and subsequent expansion, and progress made in mAbs applications may be beneficial in standardizing and optimizing cell banking. In autologous applications, striking a balance between necessity and simplicity can be more difficult – can you achieve fresh selection for patient materials? Are you able to perform cryopreservation before material is transported? Will you introduce automation solutions at the donor collection site? If so, how can you maximize consistency to ensure that any variability in a selection comes from a patient and not a process? The nature of the materials being collected can limit or prohibit many of the safety measures that typify more traditional modalities, such as filtration or sterilization using heat or radiation.

Conclusion

Automation is likely to play an increasingly important role in reducing costs and enabling greater standardization for cell therapy manufacturing. As more organizations move toward automating highly manual and repetitive tasks, cell therapy workflows are bound to see greater consistency and reproducibility, particularly as a program scales. This trend exists alongside increased interest in artificial intelligence (AI) and machine learning (ML) techniques aimed at bolstering analytics and enabling more comprehensive, targeted automation. The result will be safer, more replicable processes that can be more easily adapted to unique molecules, improving their affordability and accessibility for patients who need them.