The future is in fermentation, but what does that mean to benchtop scientists who want to produce consumer or therapeutic products at industrial scale? During the IndieBio-produced event, Unexpected Biotech, IndieBio NY Managing Director Stephen Chambers spoke with Stuart Wilkinson, Co-Founder and Technology Director of BioBrew. The conversation broke down several myths of startup scale up.
Myth 1: There is no such thing as a universal best microbial fermenter.
Question: What is the best microbial system to produce biological products via fermentation?
Answer: There isn’t one ‘ideal’ system.
Instead, the best microbial host for recombinant expression must be decided for each use case. “Being locked into a certain host system because of familiarity with it is the wrong approach,” says Wilkinson.
All hosts have strengths and weaknesses: for example, bacteria grow quickly but are susceptible to phage infection, especially at the industrial scale. Slower growing hosts like filamentous fungi require more time to ferment but also more time to develop the ideal production strain. Startups should consider expression levels and determine the titers that they want to produce.
Myth 2: Scale up is much more complicated than most people appreciate.
“Microtiter plates are great for screening and high throughput experiments, but not really representative of industrial scale,” says Wilkinson. “Industrial food biotech and yeast systems are 100,000-500,000 liters; microtiter plates have very little in common in the process or dynamics that mimic those systems.”
If one’s aspiration is to go from a microtiter plate to industrial scale, the best strategy is to use a downscaling system. Rather than going upward in incremental steps, decide the aspirational scale. This will help define the physical/chemical parameters that are the constraints, and incremental experiments can be planned backwards for a pilot scale, lab scale, and (“if you’re capable and clever enough,” says Wilkinson), the microtiter scale.
Downscaling helps ward off the glass ceilings that many startups see when upscaling: technical problems that they can’t break through that can be amplified into potentially big problems when reaching industrial scale.
Myth 3: Downstream processing is more than an afterthought.
When people start to design strain and process combinations, it’s often strain engineering first, then fermentation, and then downstream processing to collect the product. “You’ve really got to look at this more holistically and think of the entire process as one,” says Wilkinson.
Myth 4: The ‘scale-up savior syndrome.’
Many startups assume that equipment and processes will be more efficient at higher scale. Wilkinson says, “ultimately, if your strain and process don’t work at a lab scale, it’s highly unlikely it will work at industrial scale.”
Think of scale-up as the opportunity to fine-tune and optimize processes, rather than solve problems. Have a line-of-sight techno-economic viability at the lab and pilot scale before considering demonstration and industrial scale.
Ultimately, “this goes back to the modeling,” says Wilkinson. Bring in the cost of goods at the scale you aim to produce. This provides a baseline and if your theoretical practice fails to meet the breakpoint, you can expect challenges ahead. “Models are fantastic, and I wouldn’t do any work without strong models,” says WIlkinson, “but models are only as strong as the assumptions you make and the data you plug into those models. There’s no substitute for real-world data.”