What Investors Actually Ask About Your Biotech Scale-Up Economics, And Why Most Founders Aren’t Ready to Answer
- Gustavo Valente
- Apr 22
- 10 min read
The Economics of Biotech Scale-Up series
The biotech scale-up economics investors use to judge biotech startups before a raise
A biotech founder can walk into an investor meeting with strong science, a compelling product story, and real momentum, and still lose credibility in ten minutes when the conversation turns to biotech scale-up economics.
Not because the science is weak.
But because manufacturing economics is often where technical promise gets tested against commercial reality.
Cost of production.
CAPEX.
Utilization.
Manufacturing route.
Minimum competitive scale.
These are not just technical details.
They are the questions investors use to judge whether the path to scale is commercially believable, financially realistic, and worth backing.
And many founders are less prepared for that part of the conversation than they realize.
Investors are rarely just asking for numbers.
They are testing whether the company has translated technical progress into a manufacturing story that is commercially credible, financeable, and scalable.
That is exactly where an early-stage techno-economic analysis becomes valuable.
Not because it creates false precision.
But because it helps founders prepare structured, defensible answers before those questions start shaping investor confidence for them.
Short answer: what are investors really testing?
When investors ask about biotech scale-up economics, they are rarely just checking whether a founder can produce a cost number, even if it is only a rough order-of-magnitude estimate at this stage.
They are testing whether the company has a realistic path from technical progress to commercially credible manufacturing.
They want to understand things like:
whether the team understands what will actually drive cost at scale
whether capital requirements are likely to become a funding trap
whether the route to manufacturing has been thought through properly
whether the assumptions behind the model are realistic
whether the process can become commercially viable under real-world conditions
and whether the founders understand what still needs to be true for the business case to work
In other words, the investor is not only asking:
Can the process work?
They are also asking:
Can this become a manufacturable, financeable, and investable business?
That is a very different question.
Why biotech founders struggle to answer investor questions about manufacturing economics
Most founders are not unprepared because they are careless.
They are unprepared because their attention has been where it should be: on the science, the technical progress, and the process itself.
That work is essential.
But fundraising conversations often move one level above technical progress.
Investors want to know whether that progress is actually making the future manufacturing business more credible too.
And this is where otherwise strong fundraising narratives can weaken.
Because a startup can be making real progress in the lab while still having weak answers to:
what cost of production might look like at commercial scale
how much capital the first serious manufacturing step may require
whether the process depends on unrealistic scale, utilization, or purity targets
and what manufacturing path makes sense before full commercialization
The issue is usually not lack of science.
It is lack of readiness for the economic questions that sit behind scale-up.
The questions investors actually ask
The exact wording varies, but in my experience, investors tend to probe the same core areas again and again.
Sometimes directly.Sometimes through diligence.Sometimes through technical advisors or follow-up questions.
Either way, these are the questions founders should be ready for.
1. What is your cost of production at commercial scale?
This is one of the most common questions, and also one of the most misunderstood.
At an early stage, investors do not expect a perfectly accurate answer.
But they do expect the team to have a reasoned view of what commercial-scale cost could look like and what assumptions sit behind it.
What the investor is really testing
They are testing whether the team has:
translated process performance into manufacturing economics
thought seriously about the path to competitiveness
identified the variables that matter most
and moved beyond purely technical optimism
What a weak answer sounds like
“We don’t know yet.”
“It depends on scale.”
“We’ll look at that once we have pilot data.”
“We expect it to come down a lot with optimization.”
These answers weaken credibility fast.
Not because uncertainty is unacceptable, but because they suggest the economics have not yet been pressure-tested.
What a stronger answer sounds like
A stronger answer sounds more like:
We have built an early techno-economic view of commercial-scale cost. The estimate is still directional, but we understand the main cost drivers, the key assumptions around utilization and recovery, and the areas where further technical improvement matters most.
That answer does not pretend certainty.
It shows structure, realism, and preparation.
2. What does your first commercial plant CAPEX look like?
This is another question founders often underestimate.
Investors do not expect detailed engineering too early.
But they do want to know whether the team understands the likely scale of capital required and whether that capital requirement fits a realistic financing path.
What the investor is really testing
They are testing:
whether the process is likely to become capital-heavy
whether the business may need too much infrastructure too early
whether scale-up is likely to be financeable
whether the founders understand the difference between technical feasibility and capital realism
What a weak answer sounds like
“It’s too early to estimate.”
“We haven’t looked at CAPEX yet.”
“We’ll probably outsource first.”
“We assume we can just build a small plant.”
These answers often sound vague rather than prudent.
What a stronger answer sounds like
We have an order-of-magnitude view of what a first commercial manufacturing configuration could require. The number is still approximate, but we understand the main CAPEX drivers and how the answer changes depending on scale, utilization, and manufacturing route.
Again, investors are usually more comfortable with uncertainty than with the absence of structured thinking.
3. What utilization are you assuming?
This is one of the most revealing questions in the room.
Many founders default to high utilization because they are picturing what a mature plant might eventually do.
Investors know that early commercial facilities rarely start there.
What the investor is really testing
They are testing whether the founders understand:
ramp-up reality
how fixed costs behave under underutilization
how fragile the economics become when capacity is not filled
whether the model is commercially believable
What a weak answer sounds like
“Around 95%.”
“We will operate 24/7.”
“We assumed full operation.”
“We used standard industry assumptions.”
These answers often make the economics sound too clean to be real.
What a stronger answer sounds like
We modeled different utilization scenarios, including more conservative early-year assumptions. We know the economics are sensitive to plant loading, and we understand how that affects cost per kilogram and capital efficiency during ramp-up.
That kind of answer signals maturity.
Because utilization is not just an operational number. It is a commercial reality.
4. What happens if yield drops, recovery slips, or energy costs move against you?
This is where sensitivity analysis becomes critical.
Many founders build one base-case narrative and stop there.
Investors usually want to know what happens if reality is less favorable than hoped.
What the investor is really testing
They are testing:
how fragile the business case is
whether the process depends on one or two heroic assumptions
whether the team understands risk concentration
whether the company has room for imperfection
What a weak answer sounds like
“We haven’t modeled that yet.”
“We’re still improving the process.”
“We expect the process to get better over time.”
That is not enough.
What a stronger answer sounds like
We have tested the impact of lower yield, lower recovery, lower utilization, and other key assumptions. We know which variables move the economics most and where the model starts to become commercially strained.
That answer matters because it shows the team understands the limits of the case, not just the optimistic version of it.
And that is much closer to how investors think.
5. Why are you planning to build, outsource, partner, or phase capacity this way?
This question can appear in several forms:
Why not use a CMO?
Why not build your own plant?
Why not phase capacity?
Why does this need to be done in-house?
Why this location?
Investors are not just asking about logistics.
They are testing the logic behind the manufacturing route.
What the investor is really testing
They are testing whether the company understands:
the actual needs of the process
the trade-offs between control and flexibility
capital constraints
stage-appropriate manufacturing strategy
and whether the route has been chosen intentionally rather than assumed
What a weak answer sounds like
“We plan to build because that’s the long-term goal.”
“We plan to use a CMO because it’s cheaper.”
“We haven’t decided yet.”
These answers usually suggest the route has not been pressure-tested properly.
What a stronger answer sounds like
We have evaluated different manufacturing routes, including outsourcing, phased capacity, and future in-house production. The choice depends on cost, control, process specificity, capital requirements, and the stage of scale-up. We understand the trade-offs behind the route we are currently pursuing.
That is the kind of answer that gives confidence.
Not because it is final, but because it is reasoned.
6. At what scale does this become commercially credible?
This is one of the most important questions of all.
A process can be technically feasible and still only become commercially credible at a scale that is unrealistic, overcapitalized, or simply too far away for the company to finance.
This is also where many founders misunderstand economies of scale.
Yes, economies of scale can help indicate the size range at which a facility starts to make economic sense.
But that does not automatically mean the biggest possible plant is the right answer.
In some cases, larger scale genuinely improves the economics enough to justify the move.
In others, the additional scale brings so much capital burden, utilization risk, and execution complexity that the “optimal” plant on paper becomes the wrong first commercial step in practice.
What the investor is really testing
They are testing:
whether the economics depend on unrealistic scale
whether the founders understand minimum competitive scale
whether economies of scale have been interpreted realistically
whether the path to commercial viability is staged or speculative
whether the gap between today and a commercially credible facility has been thought through properly
What a weak answer sounds like
“We should become competitive as we scale.”
“Costs will come down significantly later.”
“Bigger facilities always improve the economics.”
“We haven’t defined that yet.”
Too vague.
What a stronger answer sounds like
We understand the scale range at which the process begins to look commercially credible, and we know how sensitive that is to utilization, recovery, downstream burden, and capital intensity. We also understand that economies of scale do not automatically mean the biggest facility is the best first move, and we have considered whether a smaller initial step still makes sense before the long-term target scale.
That answer shows realism.
And realism is one of the strongest trust signals you can give an investor.
What weak answers usually have in common
Weak answers usually share one problem:
They rely on hope, generalities, or future optimization instead of structured manufacturing logic.
They sound like:
“we’ll know later”
“we expect it to improve”
“we’re still early”
“we haven’t modeled that yet”
To be clear, early-stage uncertainty is normal.
What investors dislike is not uncertainty itself.
It is uncertainty combined with weak visibility.
What strong answers usually have in common
Strong answers do not require perfect numbers.
They require:
an early TEA
explicit assumptions
scenario thinking
sensitivity analysis
awareness of scale and utilization effects
a credible manufacturing route
and a clear view of what still needs to be true for the business case to work
In other words, strong answers come from teams that have already started translating technical progress into manufacturing logic.
That is exactly what an early TEA is for.
Why this matters before fundraising, not after
This is the part many founders underestimate.
By the time an investor is asking these questions in a real fundraising context, it is already late to start building the manufacturing logic from scratch.
Because these questions affect:
the credibility of the pitch
the believability of the cost story
the level of trust investors place in the team
and the perceived risk around scale-up execution
The founders who answer well are not the ones with perfect certainty.
They are the ones who have thought about scale-up economics early enough to answer with structure, realism, and perspective.
How a techno-economic analysis helps founders answer investor questions
A TEA is not just a spreadsheet with cost estimates.
At this stage, its real value is that it prepares founders to answer difficult manufacturing questions before those questions start undermining investor confidence.
It helps clarify:
cost of production logic
CAPEX order of magnitude
utilization assumptions
sensitivity to key variables
minimum competitive scale
manufacturing route trade-offs
and the conditions under which the process becomes commercially credible
That is why TEA is more than a cost model.
It is a decision tool, and in many cases, a fundraising readiness tool too.
Final thought
A lot of founders assume they can answer manufacturing economics questions when they come up.
But by the time those questions come up in fundraising, investors are already using the answers to judge how real the path to scale actually is.
That is why these questions matter.
Not because early-stage startups should pretend to know everything.
But because they need enough visibility to answer with credibility.
And that visibility does not always require waiting until pilot plant trials are complete.
In many cases, an early-stage techno-economic analysis can already provide a useful order-of-magnitude view of cost of production, CAPEX, scale requirements, utilization sensitivity, and manufacturing route trade-offs, even before pilot data exists.
That level of accuracy is often more than enough to support better internal decisions and much stronger investor conversations.
Most investors are not expecting detailed engineering certainty at this stage.
What they want is evidence that the team understands the economics well enough to know what matters, what is still uncertain, and what would need to be true for the business case to work.
If you want to be able to answer these questions confidently before your next raise, this is exactly what an early techno-economic analysis is designed to prepare.
If that is something your team is working through, feel free to reach out. I’m always happy to discuss how to pressure-test scale-up economics before those questions start shaping investor confidence for you.
Gustavo Valente
Director, Sustech Innovation
WhatsApp: +52 55 3405 0552
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 moving from lab to commercial reality.
ScaleUpReady™ note
These are exactly the kinds 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.
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