Overcoming Connectivity and Scalability Challenges with Gene Therapy Manufacturing Processes

To start with, please could you introduce yourself and tell us a little about your role?

My name is Dan UpDyke, I’m the Strategic Marketing Manager at Rockwell Automation. What I do is, I focus on understanding the industry, customers, their challenges, and build that into our strategy on how to best serve those customers, and the way to best help them best overcome their challenges and problems.

As part of that, we come to events like this (Advanced Therapies Week) to learn as much about the industry as we possibly can. We are members of BioForum and work with manufacturers on solving some of the biggest challenges that are industry wide. We also collaborate with the Advanced Regenerative Manufacturing Institute on tissue generation and tissue therapies.

We really try to get involved with what the industry is trying to do and the real technical challenges that, from an automation and digitalization standpoint, we can help them solve.

What specific obstacles are therapeutic developers currently encountering in terms of speed to market, data connectivity, and scalability in the gene therapy manufacturing process?

With this industry, there’s a big difference in the way the manufacturing processes are done compared to other traditional therapies.

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Scalability is a big challenge that needs to be addressed. Generally, drug manufacturers want to scale up and create as much volume as they possibly can. But in this space, we’re scaling down to very small processes, sometimes batches of one. Having GMP manufacturing systems that can really scale down but give industry standard control and data integrity at that level, is just new for our industry.

Not just scaling down, but also scaling out, because creating one drug at a time is great for one patient at a time, but we need to address challenges or healthcare for multiple patients. Being able to do that is really important: to scale out and have multiple production lines, multiple facilities, in different regions, giving the ability to scale out but still maintain quality and control, is a big challenge in the industry.

Another big challenge is data: data integration, data consumption. You have lots of smaller pieces of the equipment that all have to be integrated into a coordinated single manufacturing platform, so being able to pull all that data and contextualize it and do it at the right levels of integrity for GMP manufacturing, is certainly a challenge.

Another challenge is the lack of a skilled workforce. With a new industry, with new processes, you’re going to be asking people to do things that there aren’t a lot of people with experience, so how do you scale out and how do you have multi-manufacturing systems when you don’t have a lot of experienced skilled workers available?

These are challenges that we can help to solve, some of the biggest challenges that we see in the space.

Could you elaborate on how the challenges of connecting different data sources, removing data siloes, and integrating systems impact the efficiency and reliability of bringing gene therapy products to market?

I think everybody here is focused on, ‘how do we get that data out?’ ‘How do we make it accessible and available?’ One of the keys things is that we can’t lose sight of the process and the manufacturing processes while we’re doing that.

It’s not just data for data-sake or integration for integration-sake, but we’re really trying to create a GMP manufacturing environment. When you look at the integration of these systems, one big challenge is that you’re going to have multiple vendors creating different pieces of equipment that have to be tied together. They can have their own data platforms or their own control platforms, and they may be different across all of those.

As you try to pull all these things together, the ability to have an open architecture that’s able to connect and talk to those systems is incredibly important. The ability for those systems to be designed in a way that they’re intended to integrate those data points and connect to each other, whether that’s having a true ‘plug-and-produce’ strategy so that if I plug in a piece of equipment, my control platform can recognize it and recognize the pieces of data, it provides data in a structured way that it can be consumed.

It’s data-ready and is able to push that data into a unified namespace so that your data platform can see all the pieces of equipment, understand what they are, contextualize it, and be able to use that for things like your electronic batch record, or for data analytics for analyzing your batches post-production.

Shifting focus to solutions, how does the concept of digital tech transfer address issues like data siloes, collaboration with CDMOs, and scalability in the manufacturing process, and what advantages does it offer over traditional methods?

Tech transfer, to be honest, is a very manual process. It’s when you transfer information from one part of your organization to another. A lot of the time, you have Excel files, you have PDFs, which are electronic documents, but they’re not fully digitalized, the data isn’t contextualized, isn’t live. It’s their documents.

The ability to take that information from the development side and to be able to create a true digital record, and be able to structure that record in a way that the control system that you’re going to be manufacturing on can ingest it, the MES system that you’re going to be using to run your processes can ingest that information more quickly to build out those recipes to build your electronic batch records.

It can really expedite the process to be able to perform a digital tech transfer. We see a lot of investment, a lot of development in that space. From the CDMO perspective, if you’re going to have a sponsor organization develop a drug, that tech transfer, like I said, it’s PDFs, Excel files, it’s emails back and forth, it’s phone calls. To be able to understand the rest of these, to be able to develop them, if we can create a collaborative space that they can share a system in a way that protects intellectual property, now we start to collaborate instead of just communicating in transferring files.

That collaboration allows you to not only receive the information, receive fresh updated pieces of information as they come, but to share tacit knowledge about why things are the way they are, what’s important. When you do that, when you have that collaboration, you can shorten the amount of product development batches and product development cycles that you have to do. You can reduce the amount of validation and the qualification burden.

Tech transfer is therefore absolutely critical in this environment to speeding up time to market, to be able to shorten the time through collaboration that it takes to get something to a commercial production, which directly impacts patient’s lives.

The faster we can get to market, the sooner that we can provide cures and treatments for ailments. We think this is a really big key to the success of driving speed to market, by overall reducing costs and availability to patients.

How do MES capabilities, particularly electronic batch records contribute to addressing the identified challenges in the gene therapy manufacturing process, and what role do they play in ensuring real-time monitoring, analysis, and corrective actions?

We really see MES as kind of a central hub for digital transformation for the industry as a whole. In the cell and gene therapy space, the MES becomes absolutely critical to success because you’re going to have all these different data sources that are supplying information, to pull into a single electronic batch record and to view the process and the results as a whole, allows you to expedite batch release and batch review times.

We can’t have an army of quality people – what they’d call a ‘sneaker net’ – running around the building, reviewing paper documents, going through approvals… These drugs, once they’ve completed the manufacturing process, they need to get to the patient, they have a shortened life cycle. We can’t afford to have weeks of quality reviews – they have to get to the patient as fast as possible.

So, having that integrated batch record and making things like ‘review by exception’ possible, I don’t know if there’s an option other than that. We have to get these things out to market as fast as possible. So having the MES provide that single point of view and that unified batch record, and then really focusing on things like ‘release by exception’, I think, is a must for the industry. From our viewpoint, that’s a really critical focus on driving success in the space.

Shifting the focus to impact, how does overcoming these challenges contribute to the primary goal of benefiting patients, delivering more gene therapy products, and ensuring quality in the manufacturing process?

The key to success here, and what we really need to focus on, is to be able to deliver quality product on time to the patient and ensuring that quality.

When we talk about the challenges that we’ve addressed, whether that’s speed to market, addressing the scalability issues, the workforce enablement, and making things easier for operators to consistently, repeatedly deliver, it all comes down to the to delivering as much quality product as you possibly can to meet the needs of as many patients as you possibly can.

I think in this industry, if we don’t solve these challenges, we’re not going to meet that primary end goal of success for the patient.

Looking ahead, how could solutions that enable collaboration, scalability, and real-time data contribute to the overall maturation and development of the gene therapy sector?

I believe that automation, as a whole, is critical to the success of the industry.

First of all, patient outcomes are the primary purpose here, and so having repeatable solutions and repeatable automation to make sure that you have the data integrity, the quality controls, are paramount to success for meeting those patient needs.

When you look at meeting the scalability and visibility of systems across a wide network of manufacturing, whether that’s multiple lines at one site or multiple sites, being able to evaluate and analyze all of those systems to make sure you’re getting quality and repeatability that is going to be critical for volume and for our ability to scale out.

Also, addressing the workforce issues so that your operators are trained properly and we can reduce some of the manual efforts.

All of this will ultimately make it so that we can produce a larger volume of drugs for more patients and drive that patient’s success because now we’re going to make the drugs more accessible and more available to people, but also the automation itself will drive down costs and make things more affordable for the patient population, as if you don’t address availability and affordability, the success of the industry a whole is in question.

So we think automated solutions and bringing things into a true GMP manufacturing environment with the right digitalization and digital transformation of these systems is absolutely key to that availability and affordability.

This interview has been produced in partnership with Rockwell Automation.