The lab-to-fab gap is not a technology problem. It is a process ownership problem.
Most diagnostics ramps fail not because the science is wrong or the machines are inadequate. They fail because nobody owns the transition. That is a solvable problem. But only if someone stays in the room long enough to solve it.
I have been in a lot of production ramps that failed. Not as an observer. As the person called in to fix them after they had already gone wrong. And what I have seen, consistently, across industries and countries and company sizes, is that the problem is almost never the technology.
The technology is usually fine. The assay works. The machine is capable. The dispensing precision is there. What is not there is somebody whose job it is to make sure the lab version and the production version are actually the same thing. That gap, that moment of handoff where nobody is standing, is where diagnostics launches go to die.
I want to talk about that honestly. Because I do not think the industry talks about it honestly enough.
12-24 months of market time lost to ramp failure on average
37 countries where we have seen this pattern repeat
3 days vs 30 minutes.
The gap between a broken ramp and a patient diagnosis
What actually happens in a failed ramp
Here is the sequence I see most often. A diagnostics company develops an assay. The science is good. The R&D team validates it at the bench, probably using a high-quality dispensing system that gives them excellent coefficient of variation, sub-percent, everything looking clean. The product gets signed off for production. Then it moves to the line.
And on the line, a different instrument is used. Or the same instrument type, but different parameters. Or the production team makes small adjustments because the R&D specs do not quite translate to the higher-volume environment. Nobody makes a bad decision deliberately. But the result is that the assay that worked perfectly in development now behaves inconsistently at scale. QC batches start failing. You go back. You re-validate. You lose six months. Sometimes twelve.
I have seen this in Finland, in Germany, in the US, in the UK. The geography does not change the pattern. What changes the pattern is having someone who owns the transition and will not let go of it until the line runs.
"The distance between a good technology and a working production line is enormous. And almost nobody in this industry talks about it honestly."
Why ownership is missing
The R&D team's job ends when the assay is validated. That is how most organizations are structured. They hand it over and go back to the next development program. The operations team picks it up and they are accountable for production output, not for understanding every parameter decision that was made in the lab. So there is a gap. A structural gap. Nobody is accountable for what happens in between.
This is not a criticism of the people involved. They are doing their jobs correctly within the structure they have been given. The problem is the structure itself. It creates a seam, and seams are where failures accumulate.
Automation vendors often make this worse, not better. The vendor delivers the machine, commissions it, trains the operators, and leaves. They have fulfilled their contract. But the real work, the work of making the production process behave like the development process, that work has not been done. It cannot be done in a two-week commissioning visit. It takes someone who understands both sides deeply and stays through the problems.
The three things that actually close the gap
I have rebuilt enough operations to have a view on what works. Not theory. Observed pattern.
The first thing is technology continuity. If the dispensing technology in R&D is the same fundamental system as the dispensing technology in production, you eliminate the most common source of transfer failure before it can happen. The parameters transfer. The process data transfers. The team does not have to re-learn anything about how the fluid behaves. This sounds obvious. It is almost never what companies do, because R&D equipment and production equipment are typically purchased from different vendors with different criteria by different teams at different times.
The second thing is data continuity. Lab data and production data need to speak the same language. If you cannot look at a dispensing run in development and compare it directly to a dispensing run in production, you are flying blind during the transition. You do not know what is different until something fails. And at that point, you are already behind.
The third thing is what I would call accountability continuity. Someone needs to own the outcome, not just the handoff. That person needs to understand the chemistry, the engineering, the regulatory requirements, and the commercial deadline. They need to be in the room when the line is not running and stay until it is. In my experience, this person almost never exists within the customer organization. That is why the vendor relationship matters so much. Not the vendor who delivers the machine. The vendor who stays.
"A CEO who cannot do the work cannot lead the people who do it. The same principle applies to vendors. If they have never stood on a production floor at 11 pm with a line that is not running, they cannot help you when yours is not running either."
What this costs when it goes wrong
I want to put a number to this, because I think the industry systematically underestimates the true cost of ramp failure.
The direct costs are visible. Re-validation work. Failed QC batches. Equipment modification. Delayed regulatory submissions. These are real costs, and they are painful. But the indirect costs are larger. If your diagnostics product was supposed to reach the market in Q2 and the ramp failure pushes that to Q4, you have lost two quarters of revenue in a market that may already be moving toward consolidation. If a competitor reaches clinical customers six months before you, you are not just late. You are potentially locked out of accounts that have already standardized on someone else.
And if the product is something like a sepsis diagnostic, the cost is not just commercial. A test that can reduce time to diagnosis from 72 hours to 30 minutes, which requires a precision production line to deliver that performance reliably at scale. Every month the line is not running is a month in which clinical results do not reach patients who need them. I do not say that to be dramatic. I say it because it is true, and because I think it should be part of how the industry measures the cost of getting manufacturing wrong.
What good looks like
I bought Ginolis in late 2023. 25 people Team, a factory in Oulu, 15 years of precision dispensing technology, and a market thesis I had spent enough time in this industry to believe in. The reason I believed in it was exactly this problem. The lab-to-fab gap is real, it is large, and very few companies are built specifically to close it.
We have delivered 150 production lines across 37 countries. That number matters not as a marketing claim but as evidence-based. We have seen what works and what does not across a very large number of ramps in a very large number of operating environments. That experience is not replicable from a brochure.
What good looks like in practice: the same dispensing platform in the lab and on the production line. Process data that flows from bench to factory floor in a connected system. A team that does not hand off and disappear but stays accountable through qualification and first production. And a vendor relationship that starts before the design freeze and does not end at commissioning.
That is not complicated. It is just rare. And it is rare because it requires the vendor to take on accountability that most vendors prefer to avoid.
The question worth asking your vendor
If you are evaluating automation vendors for a diagnostics production ramp, ask them one question: What happens when the line is not running six months after commissioning, and it is a Friday afternoon?
The answer tells you almost everything you need to know. Not the technical answer. The accountability answer. Who calls who? Who gets on a plane? Who stays until it works.
I have put on the work clothes myself and serviced a customer's power plant in Germany because nobody else was available. The customer looked at me a little strangely. But I think it built more trust than a hundred sales meetings. That is what accountability looks like in practice. Not as a value statement. As a behavior.
The microfluidics market is going to be five times larger in five years than it is today. That is not a trend. That is a production challenge. Every new point-of-care diagnostic, every new drug delivery device, every new organ-on-chip platform requires a manufacturing automation solution that can take a lab process and make it work at scale without losing what made the process work in the first place.
The companies that will lead that decade are not the ones with the best R&D. They are the ones that close the gap.
Kauko Väinämö is CEO of Ginolis