How do you solve a problem like scaling up microfluidics?

Culturing cells using microfluidics offers several advantages over traditional cell culture techniques – the main one being the ability to precisely control the microenvironment. This means the availability of nutrients, oxygen levels, and pH can be finely tuned to the cells’ needs, resulting in more accurate and reproducible results with optimized reagent consumption (1).

Microfluidic cell culture is well-suited for online analytics. Microfluidic devices can be equipped with sensors to allow continuous, real-time monitoring of cells as they grow and respond to various stimuli (2). This enables detailed data collection on cell behaviour and responses, which can provide valuable insights and facilitate the development of new therapies. Microfluidic devices can also be easily automated, making them the perfect next generation bioreactor platform for cell research – more precise and controlled processes, automatable, low usage of reagents, and compatible with online analytics.

But what about scale? Getting 100,000 perfect cells doesn’t help patients. Millions, often billions of cells are needed to make a dose. And that’s were microfluidics stopped being relevant… until now.

At MFX, we have parallelized dozens of microfluidic bioreactors onto a larger array that forms our manufacturing bioreactor, producing up to 6 billion cells. Our parallelization strategy is inspired by the semiconductor industry and adapted to incorporate fluid and cells, ensuring homogeneous distribution to each bioreactor. The benefit of this is that everything remains the same from the point of view of the cells – densities, nutrient and metabolite concentrations, shear stress, gassing, and even analytics. The cells experience the same controlled environment, and the throughput of the system is clinically relevant. Voilà! 

(1) Ram, K. R., Pang, K. K., & Thian, E. S. (2013). Microfluidic platforms for in vitro cell culture and analysis. Lab on a Chip, 13(2), 252-268.

(2) Lai, C., Kim, J., & Wang, L. (2016). Microfluidic cell culture platforms for studying cell-cell interactions. Lab on a Chip, 16(2), 199-212.

Make your cells feel at home with microfluidics

It can be easy to forget just how alien an environment in vitro culture is when culturing cells. In vivo, cells exist in a multi-faceted micro-environment made up of a carefully regulated biochemical milieu combined with cell-to-cell/matrix contacts and specific physiochemical properties. Yet culture vessels have evolved over the years, often with little consideration of what is actually best for cells. Historically, cell culture vessels looked like they had been taken straight out of the kitchen (and they probably were): simple bottles of reagent with rudimentary agitation systems. When research needed something smaller, basic plates and flasks were utilized for adherent culture.

More recently, innovative cell culture vessels such as stirred tank bioreactors have been developed – optimized for things such as gas transfer and mixing. 3D cell culture techniques have enabled cells to be grown in three dimensions, replicating some in vivo interactions, whilst the introduction of cell culture cartridges have taken this approach one step further. However, most of these innovations have been focused automation and cell culture for non-mammalian cells. A truly cell-friendly vessel for mammalian cells is yet to be developed.

We asked MFXs VP of Microfluidics, Césaré Cejas, PhD what makes microfluidic cell culture so very different; “Microfluidics  offers a new approach, allowing for an unprecedented level of control of the cell micro-environment. Microfluidic cell culture has been around for less than 30 years but is already revolutionizing the field of mammalian cell culture. In addition to higher cell densities, a significant improvement in transduction efficiency and better and more persistent phenotypes can be achieved.”

The fact that microfluidics is highly automatable, reduces manufacturing costs, and allows the flexibility to easily fit channels with sensors is an added bonus!

MFX’s Cyto Engine™ is leveraging microfluidics to create the best possible environment for mammalian cells. By putting the cells first, we deliver incomparable process efficiency and control.

Microfluidics- the perfect meeting-place for viruses and cells

Viruses get a bad press. SARS-CoV-2 did little to improve matters, but those of us working in gene and cell therapy are only too aware of the critical role lentiviruses, adeno- and adeno-associated viruses play in the manufacture of these life-saving medicines.

Viral vectors are super-effective at inducing gene expression in cells and conferring T-cells with therapeutic properties such as tumor detection; but the production of these biomolecular tools is complex and expensive, and yields are often incredibly low. A typical process requires culturing CHO cells to produce plasmids, which are used to transfect HEK293 cells, which in turn produce the viral particles, all under GMP conditions. A few microliters of virus can cost several thousand dollars to manufacture, so when using large volume conventional bioreactors things quickly become prohibitively expensive.

Infecting target cells with the viral vector presents further challenges. The objective is to achieve optimal interaction between cell and virus particle so that as many cells as possible are infected within the bioreactor, whilst minimizing multiple infection of cells (regulators typically specify <5 infections per cell). Conventional bioreactors are not well-designed for homogeneous interaction between virus particle and cell: some cells may get infected multiple times, others not at all.

But there is another way. Both of these problems (non-uniform cell infection and low viral yield) can be overcome by the use of microfluidics. As Césaré Cejas, PhD, MFX’s VP of Microfluidics explains; “Microfluidics require significantly less virus, and co-localizing target cells and virus particles within microfluidic channels enables fine control of the interaction between cells and the virus. The cells are homogeneously distributed across a thin film of fluid ensuring that every cell is in contact with the fluid – not buried under other cells. The viral particles, moving by Brownian motion, do not have to travel far to encounter a cell and all the cells are equally likely to be infected.”

Microfluidics requires around 10x less virus, shortens the viral transduction process by several days, and ensures a homogeneous number of infections per cell. Our proprietary Cyto Engine™ platform is harnessing the power of microfluidics to transform viral transduction processes for cell and gene therapies.

Scale up, look sharp – why analytics in large-scale cell therapy manufacture is so difficult

CAR-T and other cell and gene therapies represent an exciting new paradigm in how we approach previously untreatable diseases. But as ‘living drugs’ where the cell is the product, QC / analytical testing is more important than ever to ensure safety and efficacy. Analytics can be thought of in terms of:

• Process analytics – collecting data on variables that affect the quality of the cells, like temperature, pH, dissolved oxygen, and metabolite concentration, throughout the process to analyse and refine the process
• Product analytics – collecting data through or at the end of the process to analyse and characterize the product (in this case the cells), including cell count, cell viability, and flow panels

As per GMP guidelines, analytics that are critical to the manufacturing process and not measured automatically, ‘Critical Quality Attributes’ and ‘Critical Process Parameters’, are measured by the QC team. While batched QC analysis is achievable in traditional pharma manufacture, it isn’t optimal for production of complex advanced therapies. In order to scale production of cell and gene therapies and reduce the all important vein-to-vein time developers need to:

• Limit people-intensive manual measurements and recording which are laborious and error-prone
• Minimise manual sample and data exchanges between manufacturing and QC teams

The obvious solution would then be to have online measurements and sample analysis. But how can this be achieved across multiple bioreactors without significant capital outlay? Fitting an array of different analytical technologies all measuring different things on each and every bioreactor is expensive (usually being restricted to just a few bioreactors at a time), and the unfortunate truth is that current technologies can barely automate pH and dissolved oxygen measurement reliably. Automated cell count is often only an estimate, only a handful of early-stage technologies are looking at measuring online cell viability, and no one can do label-free flow cytometry at scale.

“From an engineering perspective, we knew we had to think about things differently to solve the challenge of making online analytics a reality as we designed the Cyto Engine platform. So we came up with the concept of mutualising the analytics we integrated, i.e. one set of analytical tools that can make measurements on multiple bioreactors. We also looked to build in flexibility on what we can integrate  – that allows us to add to the system as analytical technology improves as well as allowing customization on what analytics come built in,” says James Davies, VP of Engineering at MFX.

What’s more, the mutualisation contributes negligible CapEx, making manufacturing cost-effective in the long-term.

Why successful cell therapy processes need to scale both ways

When it comes to cell therapy manufacturing, much of the industry is focussed on optimizing large scale manufacture – whether that’s scaling up larger batches for allogeneic therapies, or scaling out more batches for autologous therapies. This makes sense if the only issue in delivering cell therapies was the lack of manufacturing capacity. But with over a third of clinical stage cell therapies reporting issues ranging from safety and efficacy to CMC, and batch failure rates reportedly in the low double digits at commercial scale, understanding the whole development process is crucial.

To gain this insight Process Development (PD) teams often use Design of Experiment (DoE), varying process parameters in a combinatorial way to understand the impact on cells and determine critical process parameters. But there’s a problem.

Most cell culture tools are either designed for research OR manufacturing, meaning a process in a research tool won’t translate through to a larger volume manufacturing process and vice versa. Therefore, PD teams need to decide whether to continue with (often) manual research tools or jumping to (usually) automated manufacturing tools. And there’s pros and cons with each:

Optimizing a process with research tools

Pros

• Experiments can be kicked off quicker
• Reagent costs can be kept low
• Several experiments can be run in parallel

Cons

• Manual interventions generate variability
• There’s a lack of process data
• There’s a lot of re-work needed to translate the process for large-scale manufacturing

Optimizing a process with manufacturing tools

Pros

• Future proofs the process for large-scale manufacturing
• Can capture more data than manual processes

Cons

• High costs to run – one experiment can cost up to $30k in reagents because of the large volumes
• Can only run one experiment per device
• In-process analytics are basic at best

So what’s the solution?

We asked Lindsey Clarke, the latest member of the MFX team what was on her wish list.

“We need cell culture tools that can translate seamlessly – you won’t believe how many times I’ve been asked for this over the last decade. So many potential therapies work great at the research bench when you’re only thinking about getting the best cell, but then you try and scale them up and the biology doesn’t like it or you’re limited by what you can do at GMP, its improving as more tools companies realize this but it’s by no means seamless, especially when it comes to what you grow your cells in”

And what does it look like?

“An ideal research tool for me would be a perfectly scaled-down version of the manufacturing tool, capable of automatically running several dozen experiments, requiring very little reagents, and outfitted with live in-process analytics, so you can really understand the biology that’s happening when you change parameters.”

At MFX, we’ve been working on making this ideal world a reality. Our Cyto Engine™ performs automated cell culture in a research setting by multiplexing the exact same microfluidic chambers used in automated manufacturing, with each chamber carrying out a distinct experiment. This way, the cells are exposed to the same environment, no matter the scale. 

Is innovation in automation enough to drive cell therapy manufacturing optimization?

Moving away from manual handling in large-scale cell therapy manufacturing is undisuptably the next step in optimization. Manual operations are often tricky to replicate between different operators and sites. Ensuring reproducibility is challenging and very expensive, especially in light of the lengthy training needed for GMP manufacturing. With the 20% Compound Annual Growth Rate (CAGR) of the cell and gene therapy industry, we’re likely facing a shortage of these skilled operators in the future. On top of all of this is human error- people unavoidably make mistakes.

So is automation the answer?

Several companies are currently developing automated bioreactors for cell therapy manufacturing. Previously, the approach to automation involved simply taking traditional cell culture vessels such as bottles or flasks and adding some level of automation to them – such as tubes for automated media change. Nowadays more sophisticated devices focus on improved systems that are purposely built for automation, such as cartridges or integrated valves and chambers.

This may remove the cost of manual operators, but is it enough to revolutionize the whole manufacturing process? Here’s 3 reasons why automation alone won’t cut it.

Number 1 – cells don’t care about automation

“Cells need to thrive in the culture system they are being grown in, regardless of whether this is automatic or manual”, says James Kusena, VP of Bioprocessing and Applications.

Currently, cell batches that don’t meet the quality threshold can reach up to 10% during manufacture. And that’s for commercial-stage batches that come from years of optimization. Automation won’t fix this.

Number 2 – automation is not process control

Automation allows for feedback loops but it doesn’t fix quality of measurement. “You don’t know if what you are measuring on one end reflects what is happening on the other,” explains James, “and when you try to course-correct your process, you might course-correct one end and make the other worse. This leads to very heterogeneous cell populations, the opposite of what cell therapy needs”. Once again, automation won’t fix this.

Number 3 – scientists need to be able to go up or down the ladder

Automation won’t fix the scale-down issue James explains; “While scaling up is often the focus and the ultimate goal for translating to large-scale manufacture, when scientists need to optimize the process scaling down is necessary to save on costs and allow large datasets to be gathered”. Therefore, we need bioreactors that allow scaling down and this is independent of whether they are automated or not.

Instead of focusing on automating a slightly improved version of cell culture setups, we need to start from the ground up and build sustainable systems to really revolutionize cell therapy manufacturing. At MFX, we are developing the Cyto Engine™, a microfluidics-based bioreactor where cells can thrive, be controlled precisely and, thanks to highly parallelized microfluidics, be truly scaled up and down. And yes, it is automated.