Fully automated cell culture workflows: the Automata solution for the future of cultivated meat
Last week’s free-to-attend Future of Protein Production webinar sponsored by Automata, ‘Getting from R&D to scale: the cultured meat commercialization journey’, clearly piqued the interest of a lot of attendees. Following a brief outline of Automata’s solution for the alternative proteins sector from Geoff Dance, Head of R&D at the lab automation specialist, the discussion moved on to the esteemed table of panelists: Orit Goldman, Vice President of Biology at Steakholder Foods, Ed Steele, Co-founder at Hoxton Farms, and Peter Verstrate, Co-founder & COO of Mosa Meat.
After the introduction from Protein Production Technology International’s Editor, Nick Bradley, the floor was handed over to Dance. As Bradley highlighted, the use of mammalian cell culture is rapidly increasing. However, the majority of cell culture operations are carried out manually, even though the core steps of maintaining cells are highly reproducible. Staff are expected to conduct repetitive tasks for hours each day, and often have to come in outside of normal working hours to tend to their cells or adapt their biology to meet working weeks. This emphasis on manual steps limits both the throughput and the traceability of the workflow.
Automata was founded as a lab automation partner to support labs across synthetic biology, drug discovery and molecular biology. “As a company, we started our journey about seven years ago, as a general automation company,” Dance revealed in his Q&A. “And then in 2020, we pivoted to life sciences and healthcare. We had a major Covid project with the University of Southampton Health Care Trust. And we implemented testing at a scale of up to 100,000 lateral flow tests per day. And since then, we've been working on projects as diverse as genomic screening through to mammalian cell culture. And this led us directly to the alternative protein sector.”
No matter where in the automation journey a lab is at, Automata has the technology to relieve lab staff of repetitive tasks and empowers them to focus on the science. “When it comes to cell culture, we are a manufacturer of robotic systems and control and scheduling software to control this process, a process that we refer to as open integrated automation,” Dance explained, demonstrating via a slide a typical cell culture process incorporating incubation, media exchange (including media handling and plate titling), centrifuge, imaging, and protein analysis. “The robotic arms can move between the different parts of the process. When we assess a client process for automation, we look at every facet of their workflow, and look at specific equipment that they use or need for that process. We then design a workflow that takes those pieces and links them together in a way that reduces or eliminates hands-on time for the lab team.”
Automata’s systems have already been deployed in lab applications for cancer research, drug development and cell-based vaccine development, so how do mammalian cell lines differ – and what specifically makes cell culture challenging? “One of the things,” noted Dance, “is just how variable the different types of cells are. Some of the cell lines for drug discovery are really robust and pretty easy to care for. But in the cultured meat sector, stem cells and progenitor cells have a lot of specific needs and can respond quite poorly to being mishandled. One stem cell worker I spoke to recently described it as the ‘Goldilocks’ step – not too little, not too much, but just right. And that can be quite subjective, so learning how to translate that into something automatable is a challenge. A lot of the processes that you see in cell labs are very manual and require a certain dexterity. Part of our challenge is to know when to replicate a human’s movements and when to reconsider and redesign the step for a robot. A decrease in hands-on time for the scientists means they can actually spend more time in thinking and planning and actually doing science.”
Dance suggested that if you have a dozen things that need to be tested, that’s relatively straightforward, but when you scale that up to 10,000 tests, you’ve either got to hire 100 times the number of people or you need to radically rethink how you’re going to assess the enormous amount of both scientific effort and data that comes with it. “We’ve come across a number of labs where they will only initiate an experiment on a Monday or Tuesday because to initiate later in the week would mean it runs over into the weekend. To automate these processes or do them in parallel over a longer work day, or overnight or over weekends, the amount of time this can free up is fabulous.”
Give the delegates listening in last week were from companies of all shapes and sizes, the question about knowing whether lab automation is right for you seemed rather apt. “It’s clear from our market research that the automation of laboratory processes in the biology and novel food sectors is really still in its infancy,” responded Dance. “A lot of times, people are not sure that a process can even be automated. And scientists love getting busy in the lab. But there comes a point where the repetitive nature of the work and the extensive work leaves people with too little time to both get the work done and assess the results of their labor. The simple answer is that every lab could benefit from some form of automation.”
In the context of the overall discussion about commercialization of cultured meats, Dance concluded by putting Automata’s technology into context. “The science of culturing cells for food is well established but the technological position is still very early stage. So, there's a lot of testing and development required – for instance, the testing of many hundreds or thousands of growth factors and nutrients in all combinations to optimize cell growth is required. And it's a highly specific and custom process for every company and every cell type. And this is a huge amount of work yet it's very repetitive and it's very amenable to automation. This rapid testing and prototyping is critical for commercialization. And then once scale for manufacturing production is achieved, there's a significant and ongoing need for quality control (QC) and testing. Again, this step, especially if done in house, is highly automatable. Clear and complete record keeping at this stage is critical to meet local food regulatory requirements. And automation of QC testing will generate a complete and secure document trail.”
The R&D phases and those downstream to QC are the most obvious places to implement laboratory automation for Dance. “As the products transition to the bioreactor phase, there is a switch to the complete and enclosed process environment of the bioreactor or fermenter. But the needs of process development in this interim phase will change. And there are some interesting possibilities that we’re exploring to assist in this early scale up and assist the development team in optimizing their process. Again, though, having data and process monitored and linked by consistent control software has real value here.”
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