Fermentation Manufacturing Cost: Why Startups Can Improve the Process and Still Get Surprised by the Economics
Updated: Aug 15
The Economics of Biotech Scale-Up: Understanding Fermentation Manufacturing Costs
What Drives Fermentation Manufacturing Costs?
In many biotech and foodtech startups, the technical team is doing exactly what they should be doing. They focus on improving yield, shortening fermentation time, increasing robustness, enhancing recovery, reducing variability, and making the process more scalable. This work is essential. Without process optimization, there is no credible path to a commercial process.
However, here is the uncomfortable reality:
A startup can make significant technical progress and still move only marginally closer to a commercially viable manufacturing process.
Many teams find themselves caught off guard, not due to weak science or misplaced focus, but because technical progress alone does not always indicate whether the broader manufacturing system is becoming commercially viable.
This is where techno-economic analysis (TEA) becomes invaluable. It does not replace science, nor does it suggest that the R&D team should stop optimizing. Instead, it provides a broader perspective and poses a crucial question:
Is this process becoming more manufacturable, financeable, and commercially robust at scale, or is it merely improving in the lab and pilot plant?
This distinction is more critical than many startups realize.
What Actually Drives Fermentation Manufacturing Costs?
Fermentation manufacturing costs are rarely driven by a single variable in isolation. They are shaped by the interaction between several factors, including:
Scale
Utilization
Downstream burden
Recovery losses
Throughput
Utilities
Labor intensity
Facility-related overhead
Capital intensity
Commercial assumptions about plant operations
This complexity explains why a process can show genuine technical improvements while the cost of production remains stubbornly high or improves far less than expected.
Fermentation cost is not merely a lab metric; it is a system outcome of the entire manufacturing process.
The Real Risk: Lack of Visibility
This nuance is crucial. The issue is not that startups are optimizing too much; rather, not every improvement impacts the economics equally.
A better yield is valuable. A shorter fermentation cycle is valuable. A cleaner downstream step is valuable. A lower-cost feedstock is valuable.
However, from a commercial manufacturing perspective, the real question is:
How Much Does Each Improvement Actually Enhance the Economics Once the Process is Translated into a Real Plant?
This is where surprises often arise. Some changes that seem significant during development may only modestly affect the economics, while other less visible factors can dominate costs at industrial scale. A process can improve scientifically while remaining commercially fragile.
Fermentation Cost: A System Outcome
One of the most important insights early TEA can provide is that fermentation manufacturing cost emerges from how the whole system behaves when accounting for:
Material flows
Bottlenecks
Recovery across the full process
Installed plant requirements
Fixed-cost absorption
Utilities
Labor
Commercial operating patterns
Realistic plant utilization
Thus, early TEA is not just a financial exercise; it connects scientific progress to manufacturing reality.
Hidden Commercial Bottlenecks
Startups often focus on visible variables such as:
Yield
Fermentation time
Feedstock cost
Downstream efficiency
These factors are measurable and closely tied to daily technical work. However, when a process is translated into a commercial manufacturing scenario, the economics are often driven by a wider combination of factors.
1. Scale and Utilization
A process may appear attractive at one commercial scale but much weaker at another.
Plant size affects:
Equipment count
CAPEX
Labor structure
Utility demand
Fixed-cost dilution
Whether the process reaches a competitive cost position
Utilization is equally important. A plant that looks strong at 90% utilization can become economically fragile if the company only fills 30 to 50% of capacity in the early years. This change impacts:
Depreciation per kilogram
Fixed-cost absorption
Overhead burden
The credibility of the COGS story presented to investors
A technically sound process can still be commercially weak if the scale and utilization assumptions are unrealistic.
2. Recovery and Downstream Burden
A process may look strong up to the fermenter but struggle commercially if too much value is lost downstream. Recovery losses affect:
Effective output
Raw material use per unit sold
Upstream burden carried forward
The scale needed to hit target production volumes
Downstream complexity can also significantly impact costs. A process with multiple purification, concentration, polishing, drying, or waste-handling steps can accumulate costs through:
Yield loss
Equipment count
Cleaning burden
Utilities
Labor
Cycle time
Capital intensity
In some cases, downstream burden is not only driven by process complexity but also by unchallenged commercial assumptions.
Startups sometimes replicate the exact form or purity of an incumbent product, forcing a bio-based product into a powder because the conventional version is sold that way, or targeting a high purity that may not be necessary for the end use.
Part of the TEA conversation should include questions like:
Why does this product need to look exactly like the incumbent?
Could a liquid form work?
Could a lower purity still be commercially acceptable due to a different impurity profile?
These questions can radically change the downstream burden and, with it, the economics of the entire manufacturing system. The focus should not simply be on whether DSP is “important,” but on whether downstream complexity is making the whole manufacturing system economically heavy.
3. Utilities, Labor, and Facility-Related Overhead
Utilities are often underestimated early in development because they remain in the background. However, at scale, steam, cooling, chilled water, compressed air, electricity, process water, and wastewater treatment can become significant contributors.
Labor intensity can also exceed expectations when a process involves:
Manual intervention
Complex batch handling
Cleaning steps
Monitoring points
Multi-step transfers
Frequent operational adjustments
Moreover, the broader facility burden includes not just core equipment but also the wider plant environment:
Buildings
Support areas
Utility infrastructure
HVAC
Special warehousing
Maintenance support
Quality systems
Operational overhead linked to running the site
A process can carry a heavy facility burden simply because it requires too much manufacturing infrastructure relative to the output it generates.
4. Capital Intensity and Commercial Ramp
Even when a process performs well technically, a capital-heavy configuration can distort the economics.
The lab can tell you whether the process is improving. TEA helps determine whether the business case is strengthening.
Higher CAPEX typically leads to:
More depreciation
Increased financing pressure
Higher fixed-cost absorption needs
A more demanding commercial ramp to justify the investment
This is why some processes appear viable in principle but become fragile in practice.
A Stronger Process Does Not Always Mean a Stronger Business Case
What matters is not just whether the process can work; it is whether it can operate under realistic commercial conditions.
Misleading Industry Phrases
In biotech and fermentation circles, simplified statements often circulate, such as:
Downstream is 60% of cost
Optimizing DSP will reduce production costs by 30%
Feedstock is always the main driver
Yield is the main economic lever
These phrases gain traction because they sound plausible and occasionally reflect real situations. However, they can mislead when repeated without context.
For instance, in some processes, downstream equipment may represent a large share of direct process equipment CAPEX. Yet, this does not automatically mean downstream dominates:
Total installed CAPEX
Total project CAPEX
Full manufacturing cost
Once utilities, indirect project costs, buildings, waste treatment, labor, and operating assumptions are included, the picture can shift significantly.
The same applies to OPEX. In some cases, DSP is indeed a major economic driver. In others, the larger issue may be:
Underutilized assets
Low throughput
Poor recovery
A capital-heavy facility
Energy demand
A cost structure that never gets diluted properly at realistic commercial volumes
What dominates direct process equipment CAPEX does not necessarily dominate total project cost or COGS.
This is why broad rules of thumb can distort priorities if they replace a real TEA.
Surprises in Economics
Most startups do not get surprised because they ignored technical development. They get surprised because technical progress breeds confidence while the broader manufacturing and commercial logic remains underexplored.
This can manifest as:
A process that performs better in the lab but requires too much capital at scale
A COGS model that appears attractive only at unrealistic plant utilization
A business case dependent on a recovery level not yet demonstrated across the full process
A plant concept that works only if downstream complexity remains artificially simplified
A commercialization plan that assumes cost competitiveness before understanding the full burden of manufacturing
In practice, early TEAs can influence decisions that lab work alone would not reveal. Companies may:
Revisit feedstock sourcing strategies
Recognize the need for feedstock or production partnerships
Identify more viable production locations
Change their original location for the process to work commercially
These are not failures of science. They are not questions the lab can answer alone. They are part of the broader manufacturing and commercial logic that only becomes visible when the process is pressure-tested as a real production system.
Some of the most critical commercial decisions in scale-up are not about improving biology but about creating conditions for competitive manufacturing. These are not failures of science; they are failures of visibility. TEA is designed to close this gap.
A Better Early TEA Conversation
A better conversation does not solely ask:
How do we improve yield?
How do we shorten fermentation?
How do we make DSP more efficient?
It also includes:
Which variables move total manufacturing cost the most?
What happens once realistic plant utilization is factored in?
Are we discussing direct equipment cost, total project CAPEX, or full production cost?
Does the process still appear commercially credible once utilities, labor, waste treatment, and facility burden are included?
Are we improving a technically important variable, or one that genuinely alters the economics?
What must be true for this process to succeed at commercial scale?
This is the value of TEA at this stage. It helps startups differentiate between:
Technical improvement
Commercial strengthening
The best teams excel at both.
Final Thoughts
A startup can be engaged in the right technical work and still be surprised by the economics if the broader manufacturing and commercial logic is not pressure-tested early. This is not a critique of science; it is a reminder that science alone does not automatically reveal the full commercial picture.
Fermentation manufacturing costs are rarely explained by a single variable or slogan. They are shaped by how the entire manufacturing system behaves once scale, utilization, recovery, utilities, labor, facility burden, and capital structure are considered.
This is why early techno-economic analysis is crucial. It does not replace process development; it ensures that technical progress translates into a commercially viable path to scale.
If your team is making real progress in the lab but has limited visibility into what drives the commercial cost structure, this is precisely where an early TEA can help. It can reveal whether the broader manufacturing system is improving or if significant risks remain hidden outside the immediate technical focus.
If this is a question you are actively addressing, feel free to reach out. I’m always happy to discuss how to pressure-test manufacturing cost logic before surprises arise in fundraising, pilot design, or commercial planning.
Gustavo Valente
Director, Sustech Innovation
Series Note
This article is part of The Economics of Biotech Scale-Up — a series exploring the real manufacturing decisions founders and investors face when transitioning from lab to commercial reality.
ScaleUpReady™ Note
These are the types of manufacturing decisions explored through the ScaleUpReady™ approach: using techno-economic analysis not as a static model but as a decision framework that evolves with the process.
Comments