I would say that most do have a good level of understanding. They recognize that from the regulatory standpoint, until we have more absolute product characterization, the product is the process. Therefore, changing a part of your process after Phase III will likely result in having to carry out another comparability study to prove those process changes haven’t altered the product.
We actually just published an interview series where we asked several cell and advanced therapy companies and industry leaders to share their perspectives on topics such as obtaining funding/financing, regulatory considerations, and scaling manufacturing. In the regulatory interview, representatives from Celyad, Argos Therapeutics, and Humacyte shared their insights about reproducibility. They all expressed the importance of being able to manufacture product in a consistent and reproducible way and understand the implications variability can have in Phase II clinical trials. In one of the interviews, Bill Tente, Vice President of Quality, Compliance Management & Regulatory Affairs at Humacyte, referenced a company that introduced a manufacturing change in a pivotal randomized trial that had a significant effect on the biological characteristics of the product. The impact on timeline and costs forced them out of business. Although he acknowledged that might be an extreme example, it shows that changes at any stage can increase the risk of delays or a clinical hold that can be devastating.
As with anything, when you become more involved in the details, that’s when it becomes more obvious as to where opportunities for variability lie within a process. While there is often some need for education there, by and large our clients generally recognize what is required in terms of data and reproducibility as we explore automation solutions with them.
As part of the market research survey I mentioned earlier, we asked about the biggest barriers to implementing fully automated manufacturing solutions and the top two answers were costs and process complexity. This presents a very interesting conundrum because they are actually two of the main reasons you would move to automated processes. But it’s understandable that companies look at their processes and assume that the move to automation is just going to be too complex and add costs to their manufacturing. However, as you start to analyze your processes in a more detailed way and you look for where the costs are distributed, it becomes much clearer that in fact introducing automated technologies and processes can not only simplify these steps but bring down your costs at the same time.
One example I would like to share here is our experience in helping a company scale-up an allogeneic process and being able to validate that process. This particular process was a 2D adherent culture and when the disposable system was filled with cell suspension it was around 15 Kg in weight. If you think about the practicality of carrying out manipulation steps such as cell harvest and trypsinization at this scale in a manual fashion, it’s clear that you are going to encounter a lot of challenges, not only physically, but also in ensuring you are carrying out these steps in a consistent way each time. But as you translate this into an automated process, you can replicate these manipulation steps at scale, consistently. That’s a very powerful driver–and actually a relatively simple level of automation would be required here and yet it would transform your process into one that can be validated.
A second example is a cell seeding operation that for early research work uses two operators manually seeding cells (20 to 50 ml) onto a biodegradable scaffold within a 500-ml container and the process takes 30 minutes. When you scale-up and want to seed several hundred concurrently, this creates a large labor requirement that’s just not cost-effective or logistically practical. e solution to automate this process may be costly, but we have found that the ROI for these solutions can be realized in less than a year, even when the implementation (development and replication) cost is significant. Prior to implementing any solution, you need to explore the technologies available and the impact these solutions can have on the cost of goods.