There is a familiar pattern in growing biotechs. The company hires its first quality leader, often from a large pharmaceutical company. That person brings the validation approach they know: thick templates, every function scripted, every screenshot captured. It worked where they came from, so it feels safe.
Two years later, validation is the bottleneck. Systems wait months to go live. A small team spends most of its time producing documents that nobody reads. And the company is still not confident it would do well in an inspection, because the effort went into volume rather than into the risks that matter.
This is the mid-market validation gap. It is not a shortage of effort. It is effort pointed in the wrong direction.
Why large-company habits don't scale down
Large pharmaceutical companies built their validation approaches over decades, often in response to specific findings. Their templates carry the memory of every inspection they have been through. They also have the people to fill them in.
A company with a quality team of six does not. When it copies the same templates, it gets the cost without the context. Every system is treated as high risk because the template assumes it. Every function is tested in full because the template has a row for it. The result is slower, not safer.
The regulators have been saying this for years. FDA's guidance on computer software assurance, finalised in 2025 for device manufacturers and widely used as a reference in pharma, is explicit that effort should match risk and that documentation exists to support testing, not replace it. GAMP 5's second edition says much the same. Nothing in EU GMP requires the volume most companies produce.
Where the effort should go
A mid-sized company has limited validation capacity, so the question is where to spend it.
Spend it on the systems that hold release-relevant data, patient safety data or data that goes to regulators. Spend it on the functions within those systems that could actually hurt product or patients if they failed: calculations, approvals, audit trails, interfaces that move critical data.
Spend much less on configuration that carries little risk, on standard functions a competent vendor has already tested, and on systems that support the business but not GxP decisions.
And spend real effort on staying validated, not just becoming validated. Change control, periodic review and access review are where small teams fall behind, and they are where inspectors find the gaps.
The vendor question
Smaller companies depend more on vendors, especially for cloud systems. That is an advantage if used properly. A good vendor has tested its product thoroughly, and relying on that evidence, after assessing it honestly, is exactly what modern guidance expects.
The mistake is relying on it blindly, or not at all. A one-page "validated" statement is not evidence. Re-testing everything the vendor already tested is not diligence. The useful middle is a proper assessment once, then reliance with periodic checks.
What good looks like at this size
A validation approach that fits a mid-sized company tends to share a few features. Requirements that are short and specific. Risk assessments that actually change how much testing is done. Unscripted testing for low-risk functions, recorded briefly. Scripted testing for the functions that matter. Vendor evidence used and referenced. A release routine for cloud systems that takes days, not weeks.
None of this is a shortcut. It is what the guidance asks for. The companies that work this way go live faster and are better prepared for inspection, because their effort sits where an inspector will look.
The leadership point
Closing this gap is not mainly a task for the validation team. It needs a quality leader willing to say that the template from their last company does not fit this one, and senior management willing to accept that less paper can mean more control.
That is an uncomfortable conversation in a regulated business. It is also the one that frees a small quality team to do the work that actually protects patients.
For the practical detail, see our earlier look at the mid-market validation gap.
Where to go next
Explore GxP Copilot for AI-native validation, TraceDraft for source-traceable clinical documentation, or book a demo to see either on your own data.