Rethinking Scale in Industrial Fermentation: Why the Largest Reactor Is Not Always the Most Economical
🗓️ November 18, 2025
Fermenter Size, Up-Time, and the Hidden Risk to Profitability
In industrial biotechnology, scale-up is often viewed through a simple lens: larger fermenters = lower cost per tonne = better economics. But unlike petrochemicals or bulk chemicals, fermentation introduces biological and operational risk that increases dramatically with size, including the risk of campaign failure.
In this post we explore:
Why scale-up in biotech is fundamentally different from other industries
How campaign termination impacts cost of goods (COGs) and profitability
Why maximising up-time, not vessel size, is often the real optimisation challenge
How multi-fermenter designs can outperform single mega-reactor strategies
Economies of Scale in Fermentation: The Theory
Classically, scaling up reduces cost by; a) spreading fixed CAPEX over more production volume, b) increasing equipment efficiency & c) allowing bulk feedstock sourcing at lower price per unit. Many biotechnology companies have done this successfully in the past, but concept to production can take many years to achieve success in such large fermenters.
Because of the financial logic, biotech investors and technical teams often push toward the largest feasible fermenter volumes, with target nameplate capacities defined before full biological risk is understood.
Why Biotech Scale-Up Is Different
In chemical engineering, scale-up follows largely predictable physical rules.
In fermentation, the “reactor” contains a living biological system, sensitive to; shear stress (especially in stirred tank reactors), feedstock concentration gradients, mixing inefficiencies, heat and mass transfer limitations and generally time spent outside the optimal process envelope.
As fermenters grow larger, these variables become harder to predict, model, or control.
It only takes one parameter to be outside the process envelope to reduce growth rate, reduce productivity or kill the culture entirely resulting in full campaign loss.
The Real Cost of Campaign Failure
At lab or pilot scale, failed batches are expected and even useful. At commercial scale, every failed run materially reduces profitability. This can be proven in a simple thought experiment. Imagine a Biotech production plant with the following assumptions…
● 100m3 volume production fermenter
● ~ 4,000 tonnes/year nameplate capacity
● Designed COGs: $3,500/tonne
● Market price: $4,000/tonne
● Turnaround time between runs: 2 weeks
How many failed campaigns per year are required before the plant loses profitability? See the figure below…
Figure 1. Different models of the effect of campaign failures on uptime, net profit (top left, bottom right), COGs (top right), tonnes of product produced/year (bottom left).
The result is surprisingly small for a new technology at scale. Approximately 4 complete campaign failures per year can push the business into a financial difficulty (< 5 % operating profit). This is rarely factored into early investor material, but it should be.
Up-Time as a Design Variable
The bigger the fermenter, the higher the biological and operational risk. This insight leads to a counterintuitive design truth:
The most cost-efficient industrial fermentation plants are not always the ones with the largest reactors; they are the ones that keep running.
A plant with 3 × 33,000 L fermenters may have higher CAPEX (~20–30% increase as a rule of thumb) but lower risk of full-capacity loss, faster commissioning and more similarity between pilot and production scale. That means less severe up-time impact when one campaign fails and greater operational resilience.
For investors, this translates to:
➡ Reduced volatility in production output
➡ Fewer catastrophic COG excursions
➡ Much higher probability of achieving pro-forma economics
Conclusion — Scale Is Good, Stability Is Better
Biotech scale-up strategy should never be a single-variable optimisation based solely on vessel volume. Larger fermenters improve theoretical COGs. But they also carry hidden biological, operational, and financial fragility that can destroy profitability if campaign failure frequency is underestimated.
Up-time is the real economic driver.
The smarter question is not:
“How big can we build the reactor?”
but rather:
“What design gives us the highest probability of stability?”
For many industrial biotech processes, moderately sized multiple fermenters with built in redundancy rather than single ultra-large vessels, strike the best balance between economics and resilience.
Want more?
We help companies model this exact problem, from up-time simulations to CAPEX vs COGs design trade-offs.
✉️ Contact us at A&A Biotech Consultancy Ltd.
Turning fermentation insight into industrial success.