The situation
It was meant to connect academia, healthcare and industry. Great. But what exactly does a lab like that do on Monday morning?
Projects · University of Glasgow
Digital Health Validation Lab — everyone wanted to help innovation. Each in a different way.
It was meant to connect academia, healthcare and industry. Great. But what exactly does a lab like that do on Monday morning?
8remote research sessions
3service-testing rounds
3ecosystems connected in one model
6operational process stages
Case at a glance
My responsibility
I led the work from the first stakeholder map to the handover of a tested model. My job was to put conflicting perspectives on the table and turn them into decisions: who the Lab helps, with what, under which rules and what happens to a project step by step. The experts knew medicine and the system. I made sure the whole thing began to work as a service.
What remained
The result was not a presentation or a catalogue of ideas, but a coherent operating model: a clear ecosystem role, service offering, project pathway, qualification criteria, governance, responsibilities and performance measures. Prospective users confirmed that its validation capabilities were both needed and relevant to real market requirements.
The challenge
It made perfect sense on a slide. In reality, everyone imagined a different Lab.
The University of Glasgow was developing the Digital Health Validation Lab as part of its Living Laboratory for Precision Medicine. The ambition was to give innovators access to clinical expertise, infrastructure, trials, regulation and market-adoption support.
Each stakeholder imagined the future Lab differently. Academics, clinicians, NHS representatives, innovators and industry brought different needs, language, priorities and success criteria. In an already crowded Scottish innovation ecosystem, DHVL needed a precise role and an operating service capable of delivering it.
My role
I led the work from the first stakeholder map to the handover of a tested model. My job was to put conflicting perspectives on the table and turn them into decisions: who the Lab helps, with what, under which rules and what happens to a project step by step. The experts knew medicine and the system. I made sure the whole thing began to work as a service.
The work
First we untangled the system. Then we put it back together as a service.
See the whole ecosystem
We mapped the people, organisations and relationships shaping medical-innovation validation across academia, healthcare, government and industry. This revealed whose voice was needed, when to involve them and where conflicts or risks might emerge.
Understand competing versions of the problem
We ran eight two-hour remote research sessions with academics, clinical specialists, innovators and industry experts. The material was synthesised into 18 categories spanning landscape, identity, offering and process.
Build a shared direction
Co-creation was not about finding a painless compromise. We turned divergent interests into a clear vision, defining DHVL's niche, preferred projects, business model and route from concept to launch.
Turn the vision into operations
We prototyped a six-stage service: candidate identification, feedback and recommendations, qualification, validation planning, validation execution and follow-up support. An abstract ambition became something the team could critique and improve.
Test before launch
Across three testing rounds we returned to stakeholders from academia, clinical practice, industry and innovation. Each iteration clarified the target audience, service scope, required resources and project-selection criteria.
Launch and transfer ownership
The model was challenged with prospective users at a public showcase, then strengthened with positioning, market analysis, KPIs and direction for a three-year plan. The fully designed DHVL was handed to its Operational Team and Launch Manager.
Key decisions
A precise role, not a broad promise
DHVL would not become another hub supporting everything. It focused on validation and the evidence medical innovations need to progress.
Value over spectacle
The service kept everyday patient and clinician challenges in scope, rather than focusing only on large and visible innovation programmes.
Selection is part of the service
Clear criteria helped assess project fit and maturity — and redirect innovators when another part of the ecosystem could support them better.
Evolution over perfection
The service was designed to learn. Every project, interaction and feedback cycle would improve the operating model.
The value
We did not make a presentation about the Lab. We helped build the Lab.
The result was not a presentation or a catalogue of ideas, but a coherent operating model: a clear ecosystem role, service offering, project pathway, qualification criteria, governance, responsibilities and performance measures. Prospective users confirmed that its validation capabilities were both needed and relevant to real market requirements.
For innovators
A clearer route to clinical validation, earlier risk discovery and access to expertise and resources previously scattered across institutions.
For the University and NHS
A way to select projects, focus limited resources and build the evidence required for safer healthcare adoption.
For the ecosystem
A practical bridge between research, technology and healthcare reality, with a distinct role alongside existing organisations.
External validation
Then Elsevier decided the process was worth sharing with others.
In 2025, Elsevier published the full project account as Chapter 10 of “The Living Laboratory for Precision Medicine: Solutions for Clinical Implementation”. The chapter documents DHVL and frames the creation process as a transferable model for complex services beyond healthcare.
Read the Elsevier publication ↗