Invetech’s Manager of Cell Therapy, Jon Ellis, was recently featured in TreeFrog Therapeutics’ webcast In the Stem Cell Jungle. Hosted by Maxime Feyeux, Co-founder and CSO of TreeFrog Therapeutics, the webcast features interviews with cell therapy and stem cell industry leaders and experts.

During the episode, Jon and Maxime discussed:

Automating cell therapy manufacturing processes and avoiding common mistakes

Maxime Feyeux: When a client in the cell therapy field comes to you to automate a manufacturing process, what are some of the things you’re most sensitive to when evaluating the project?   

Jon Ellis: If there’s one thing to focus on when starting to plan cell therapy manufacturing automation it is requirements. And not just right now; we need to look at what your needs are likely to be in the first one, two, three…five years so that as you develop your requirements, we know what your expectations are and what the business need is likely to be too. For example, how many patients do you envisage treating? How many batches do you plan to make? and so on.

Also, what are your automation drivers: Is it the number of batches? Do you plan to operate in multiple jurisdictions? It’s one thing having your process experts make some batches in your early clinical trials. But when you plan to disseminate out into other manufacturing facilities using new employees, maybe people with little experience in working in Good Manufacturing Practice (GMP) environment, you really need to make sure you’ve got the process under control.

We try to balance business and technical requirements so we can align the introduction of automation. And that can vary for some companies – it can be aligned with funding, or it could be aligned with an IND (The United States Food and Drug Administration’s Investigational New Drug) application.

Maxime Feyeux: Are there some common mistakes when companies are planning to automate their process?

A common mistake that we see is just not being quite ready to automate. So we focus on making sure you understand your release criteria, your product specifications, your process variability… And then, align that with an automation process that’s not too late to do clinical studies and not too early so that you’re still in flux in terms of what your dose might be or how many batches you plan to make.

Maxime Feyeux: So in terms of mistakes, you would still say the timing of automation should rather be a little earlier than a little later – or is it about finding the sweet spot?

Jon Ellis: The sweet spot varies for different applications. When we say automation, it’s not just pushing a button and then walking away. That’s the vision for the future – but we are still away from that. So, it’s really what’s the right size for now, and how can it grow with you over time.

How much money and time is needed to automate a cell therapy manufacturing process?

Maxime Feyeux: How much money and time is needed to automate a process? What are the key factors impacting the development time and overall expenditure?

Jon Ellis: It’s not going to surprise you to hear me say “it depends”. The real “it depends” comes from how much development you need to do. If you utilize existing technologies, that are used and are proven, it may be an integration exercise. That’s a bit more straightforward than having to develop new technologies, which has an unknown timeline.

There are pros and cons against different approaches. So, off-the- shelf technologies can be arranged in series as part of the production process. We know what they do, those platforms have been around for a number of years. But they’re very limited in terms of scalability, how to use lots of different single-use sets from different platforms and integrate them together.

We know a fully automated system may take longer to develop and be more costly. But ultimately, you can design that around your process, and so you can look at the cost of goods (COGs) and the process efficiency and drive down costs later on.

The ideal model is a hybrid model, where you have technologies you use now, potentially, off-the-shelf, at individual operation level, but then ideally be able to use those same tools in a fully automated system further down the line.

I think one of the things that needs to be considered as well are the ancillary processes such as media or viral vector preparation – people maybe don’t consider those as much. It’s fine to blend media under a hood for one, two, three patients, but, if you start treating in the autologous space, making doses for hundreds, thousands or tens of thousands of patients per year ultimately it becomes a much greater challenge. So automation around some of the ancillary processes can really help drive down your operator costs as well.

Finally, the thing that impacts the cost is scalability. In the allogeneic space for example, how big is a batch. So maybe upstream, you can make a dose for a thousand patients, but can all the rest of your process steps align with that? For example, after your culture phase, you have enough cells for a thousand doses – can you actually formulate and freeze a thousand doses at the same time? It’s a pretty complex scenario for some people, but I think the key to keeping costs and timeline to minimum, again, is really just making sure you understand your requirements.

Maxime Feyeux: Could you give a rough timeframe for a more straightforward automation case study?

Jon Ellis: Relatively straightforward automation steps may take somewhere in the order of 12 months if it’s a case of limited development and aligning off-the-shelf technologies and not a huge integration into manufacturing execution systems. But beyond that, it really can vary quite significantly, depending on the scope.

Maxime Feyeux: And a rough cost for the same thing?

Jon Ellis: There are too many variables to give a baseline cost. With any new project one of the first things we do is to develop the business case and the projected timelines and costs to be upfront about what’s needed so as clients embark on this journey, they have very clear expectations around what it’s going to take.

But I don’t think there’s a “here’s what it would cost approximately” – as it really depends on the individual use case. Things to evaluate include: Is there any technology development required? What is the scope? What kind of scale is needed? Will operations be in multiple jurisdictions? These factors impact the timeline and cost quite significantly.

Key areas to focus on to improve quality and reduce costs

Maxime Feyeux: What are the key areas that need improvement to scale up quality and help reduce the costs of therapeutics?

Jon Ellis: Right now, costs of goods sold are heavily impacted by FT (full-time employee) requirements – people in the process are very expensive. People in the process impacts quality and scale as well. And so, introducing appropriate automation to reduce FT requirements is necessary as there aren’t that many people trained to operate in GMP environments. And as the industry is starting to explode, there’s a real gap in terms of trained people.

Raising quality requires improved manufacturing data capture and, ideally, more automated in-line analytics. Today, if you have to take a sample, go to a separate lab to a different team to get a cell count to figure out what you need to do with your cells, it’s a very manual and risk- driven process. In-line analytics would feed into your manufacturing process and support real-time manufacturing decisions, which would greatly improve quality and reduce risk.

Also there’s been considerable maturity in technologies that can be scaled from process development through to commercial and that’s both in scale-up and scale-out model as well. So, there isn’t a need to do a process for a period of time, and then completely change your process or change parts of your process to operate in large-scale production environment

To reduce costs, one of the things it would be great for the industry to get to is release by exception. The burden to review batch records is enormous; that’s a burden that really isn’t sustainable. So, with more automation, more data capture, more process control, moving to that release by exception level would be very significant to improving quality and reducing costs.

What are some of the new manufacturing technologies we are seeing in the industry?

Maxime Feyeux: There are many technologies available to manufacture cell therapy products. What are some of the drawbacks versus advantages of the key technologies that are available?

Jon Ellis: I’d argue there aren’t enough technologies available to manufacturing therapies. Some have been around for a long period of time, and the advantage is that they’re proven and from a regulatory perspective, not a risk. The drawbacks are that some of those technologies weren’t really developed for the needs of the now and maybe aren’t optimal and don’t always scale easily. I think for those technologies, things that could improve further are the ability to improve connectivity, data management and so on.

For a paradigm shift in manufacturing efficiency, we need new tools and new technologies. There are some interesting things in the works; TreeFrog obviously has something exciting in development and there are other companies out there including interesting acoustic washing and transfection technologies which are looking quite exciting.

But to get those technologies to where they need to be, it’s going to take a collaborative approach. We need to work collaboratively to understand more about technologies and how they can be implemented safely, establish working groups to look at the new tools available, ensure they can be connected from fluidic perspectives and from data gain. Enabling integration is important to give the industry more choices.

Maxime Feyeux: Are there technologies that are promising in the space but need improvements from your perspective?

Jon Ellis: There are new technologies which are exciting but probably do need a bit more development before they’re ready for integration into a fully automated platform, and some we’ve seen that we don’t think perform as well as they could.

With some of the new technologies there is real potential. But they may not work well in the range of conditions that are likely to be experienced in a true GMP manufacturing facility. For example, increment materials in terms of stem cells can be highly variable.

So, with new technologies, it’s important to make sure they can handle that incoming variability and still perform at the same level, and with new tools that’s we’re we often see the gap. We’re very keen to work with those companies to help solve that and bridge that gap and make sure the tools are robust across a wide range of conditions.

Watch the full interview on TreeFrog Therapeutics’ ‘In the Stem Cell Jungle’ website on demand.