Driving Down COGS: Breaking Down Automated Manufacturing
By Life Science Connect Editorial Staff
When it comes to CAR-T applications or other major cell therapy modalities, many organizations tend to focus on improving 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, necessitating a more holistic approach to innovation.
Automating more standard activities, such as media preparation, can allow companies to 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.
In a recent installment of Cell & Gene Live, Craig Beasley, chief technical officer at BlueRock Therapeutics, and Narinder Singh, chief technical officer at Arcellx, sat down to explore how to achieve key improvements to a workflow through automation to greatly improve the consistency of production, bolster a product’s safety and quality, and reduce rework and improve costs.
Enabling Greater Automation For Cell And Gene Therapies
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.
In the larger pharmaceutical manufacturing landscape, automation has transformed the industry. Yet for biopharma, the relative novelty of the molecules in development, as well as the processes supporting them, has resulted in manufacturing that is costly to achieve and challenging to scale. According to Singh, the goal at Arcellx is not only to reach commercialization for its engineered cell therapies, but to do so in ways that make them cost effective and broadly accessible. “The challenge for process people like us is, how can we translate this promise to be broadly accessible to thousands, or even hundreds of thousands, of people? That’s where automation can help us, just as it has helped other industries,” Singh said.
Targeted Automation To Enable Accelerated Outcomes
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, according to Beasley.
“When you’re building a process, what parts of that process are likely not to change? Media prep, pluripotent stem cell expansion, those are things that, once you get it right, you should be able to automate,” he explained. “Conversely, what steps do you just not understand yet? Don’t spend your time there. Really learn the process first and then try to automate, because it’s so much cheaper to do it right the first time than it is reworking that work while you’re launching a product.”
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. “We saw that, in our case, reducing process cycle time by 20 percent for one of our processes had a greater than 30 percent impact on plant capacity,” Singh said. 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, Singh explained. 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.
Looking Toward The Future
For cell therapy manufacturing, the highly custom manual processing that typifies many of the applications in development today has the potential to result in unacceptable variability as a program scales. Addressing this variability requires technology solutions that enable greater automation, closed processing, and a deeper understanding of the foundational science supporting these modalities. By understanding the sources of variability in a cell therapy workflow, from patient materials to reagents to process-level inconsistencies, operators can work toward automation that simplifies the most manual and repetitive tasks. This push toward more standardized, consistent manufacturing will be crucial to enabling the scale, safety, and efficacy necessary to improve patient safety, accessibility, and cost for many of the most innovative cell therapies in development today.