Why
Diagnostics Startups Stall
Seven patterns leaders can recognise early
By Dr. Holger Engel
July 2026
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Seven patterns leaders can recognise early
Many diagnostics startups do not stall because the underlying science is fundamentally weak.
They stall because the path from a promising technology to a robust product is more complex than expected. Scientific progress continues, prototypes improve and teams remain busy, yet the company gradually loses momentum.
Timelines slip, priorities multiply, investors become less confident and development starts to
feel increasingly difficult to control. In most cases, this does not happen because of one major mistake. It is the result of several structural problems that reinforce each other over time.
Having worked across diagnostics, life science tools, product development, system engineering and venture leadership, I have seen the same patterns repeatedly.
They are often visible long before a project reaches a critical point.
The following seven warning signs are particularly important.
A technology can work and still be far away from becoming a product.
A successful experiment, a promising assay or a functional prototype may demonstrate scientific feasibility. It does not yet prove that the solution can be used reliably, manufactured consistently, supported economically or integrated into a real customer workflow.
This distinction is frequently underestimated.
Teams often continue optimising technical performance while fundamental product questions remain unanswered:
When technology and product are treated as the same thing, development decisions become reactive. The team improves what it can measure instead of building towards a clearly defined product.
The result is often a sophisticated technology without a sufficiently clear route to market readiness.
“Stagnation is rarely caused by one dramatic failure.”
It usually develops gradually when science, engineering and business begin to move on different roadmaps — and no one actively reconnects them.
2. The target product is not defined precisely enough
Many development programmes start with a broad product vision but lack a sufficiently detailed target product definition. Statements such as “rapid”, “automated”, “low-cost” or “easy to use” sound clear, but they are not yet development requirements.
Without clear boundaries, every department interprets the future product differently.
Scientists optimise assay performance. Engineers optimise technical elegance.
Business teams discuss different customer groups. Investors hear a broader story than the development team can realistically deliver.
This lack of precision creates hidden divergence.
A strong target product profile does not need to answer every question at the beginning.
But it must establish enough direction to support prioritisation, system architecture and evidence-based decision-making.
3.Science, engineering and business operate on different roadmaps
Diagnostics development is inherently multidisciplinary.
Assay development, fluidics, instrumentation, software, manufacturing, quality, regulatory strategy and business planning cannot be managed as independent workstreams for long.
Yet this is exactly what often happens.
Each team progresses according to its own logic. Scientific teams focus on analytical performance. Engineers focus on technical feasibility. Business teams prepare market narratives and fundraising milestones. All three may appear productive, but the overall programme lacks integration.
The problem becomes visible when dependencies are discovered late.
A change in assay requirements affects cartridge design. A manufacturing constraint limits reagent choices. A user workflow requires software changes. A new market assumption changes the required throughput or cost structure. The central question is therefore not whether each function performs well.
The question is whether all functions are working towards the same product.
This requires active translation between science, engineering and business. It also requires someone who can identify conflicts early and convert them into clear decisions.
6. Milestones describe activity rather than evidence
Developmentroadmaps often contain many activities:
These activities may all be necessary, but they do not automatically define progress.
A strong milestone should clarify what evidence will exist afterwards and which decision that evidence will enable.
For example:
When milestones focus mainly on work performed rather than knowledge gained, teams
can remain busy without materially reducing uncertainty.
This isespecially dangerous in fundraising situations.
Investors are less interested in the number of activities completed than in whether the company has increased the probability of successful execution.
7.Senior leadership is missing at the interfaces
Many startups have strong specialists.
They may have excellent scientists, capable engineers and committed business leaders.
Yet the company still struggles because the most important problems sit between
disciplines.
No single function fully owns questions such as:
These are interface questions.
They require experience across functions and the authority to create alignment.
Not every startup needs a full-time senior executive at every stage. But it does need access to experienced leadership that can challenge assumptions, structure decisions and help the team move from discussion to execution.
This can take different forms: an interim role, a fractional leadership position, a strategic sparring partner or a focused project engagement.
The format is less important than the ability to connect technology, product, organisation and business reality.
Stagnation rarely starts with one dramatic failure
Diagnostics startups usually do not stall overnight.
The warning signs appear gradually:
At this point, the instinct is often to add more activity.
More experiments.
More meetings.
More people.
More parallel workstreams.
But the more effective response is usually to create clarity.
Leadership teams should ask:
The answers are rarely purely scientific or purely commercial.
They sit at the intersection of science, engineering, business and execution.
That is also where experienced external support can create the greatest value.
I work with founders, development teams and investors in diagnostics and life science tools to identify development bottlenecks, structure complex programmes and move technologies towards robust products and viable ventures.
If you recognise some of these patterns in your own organisation and would like to discuss them, contact me at info@holgerengel.com, send me a Whatsapp at +4915256345688 or connect with me on LinkedIn.