Better health data creates opportunities throughout medicine. Turning those opportunities into better care requires a chain of contributions: researchers identify meaningful patterns, technology companies develop usable tools, clinicians establish their relevance, and healthcare organisations create the conditions for adoption. For a MedTech business, intellectual property decisions run through this entire journey.

Camille Terfve, Partner and Patent Attorney at Mewburn Ellis, provides a concrete starting point in How data changed our understanding and care of breast cancer, published on 31 May 2024. She traces how expanding access to biological and clinical data has supported more differentiated approaches to breast cancer, including gene-expression tests, genomic analysis and machine learning. Her article closes by connecting innovation with the role of patents in securing funding and protecting investment on the path towards clinical application.

This opens a broader management question: what must a company put in place so that a valuable insight can become a clinically useful, commercially sustainable service?

Several voices from the MedTech ecosystem help explore that question. Their published contributions connect precision medicine, clinical validation, data infrastructure, implementation and patient participation. The IP implications developed below are our editorial interpretation of those contributions.

Jurgi Camblong and the infrastructure behind precision medicine

Jurgi Camblong brings the platform perspective into the discussion. In its March 2025 announcement of two million genomic profiles analysed, SOPHiA GENETICS describes the scale reached by its SOPHiA DDM platform. Camblong connects that milestone with the development of data-driven medicine. The announcement illustrates how analytical capabilities can reach institutions through a shared technology platform.

For an emerging MedTech company, this raises a strategic question about its own contribution. Does its advantage lie in generating a particular measurement, interpreting complex information, combining different inputs or delivering a result within a clinical workflow?

Our IP interpretation is that management should map these contributions before deciding where to concentrate protection efforts. A diagnostic proposition may depend on several complementary assets, each developed or supplied by a different organisation.

Consider a company working with a hospital and a laboratory to develop an analytical service. Its growth plan needs clarity about the technology it brings, the improvements produced through collaboration and the permissions needed for subsequent deployments. Those questions help connect an initial research relationship with a repeatable business.

Mihaela van der Schaar and the evidence behind useful predictions

Mihaela van der Schaar’s research provides a direct connection to Terfve’s breast cancer example. Her laboratory’s overview of its clinical research includes work on Adjutorium, a prognostic tool evaluated against PREDICT v2.1 using internal and external validation. The laboratory also describes sustained collaboration with clinicians as part of its approach to developing medical machine learning.

For the ecosystem, this introduces a crucial distinction between predictive performance in a study and the evidence needed to support use in a particular care setting. A development team must define the decision its tool supports, the population concerned and the conditions under which its outputs are useful.

The management implication is to connect IP planning with the evidence programme. Before beginning a validation partnership, teams should ask who can use the resulting analyses, which findings may be published and how technical improvements will be handled.

These choices influence the next stage of development. A company seeking another clinical partner or additional investment needs to explain what the evidence establishes and which capabilities it can carry forward. Validation planning and commercial planning therefore need a shared view of the intended product.

Rachel Dunscombe and the value of dependable data infrastructure

Rachel Dunscombe adds the infrastructure perspective. In her 2023 openEHR interview, she describes the problems created by fragmented formats and inconsistent data structures. She emphasises preserving meaning and explains how different standards contribute complementary functions across healthcare information systems.

This matters to the journey described by Terfve because useful analysis depends on the information reaching the analytical system in a usable form. A promising application can encounter substantial deployment work when it moves between institutions with different systems and practices.

For IP management, our inference is that integration deserves explicit attention. Which interfaces must remain accessible to partners? Which implementation capabilities distinguish the supplier? What permissions are needed to maintain connections and support future versions?

A company can build its proposition around compatibility while retaining distinctive expertise in processing, quality assurance or deployment. Management needs to identify those boundaries deliberately.

Technical access also needs to be considered alongside the purposes for which information may be used. A connection that enables a clinical service should prompt a separate discussion about any proposed use for further product development.

Tara Donnelly and the work required for adoption

Tara Donnelly provides an operational example in The NHS App: thinking big, starting small, scaling fast, published in 2019. Reflecting on the early rollout, she describes learning from patients and staff, refining the service and coordinating implementation across organisations. She also distinguishes technical connection from staff and patients being able to use the service fully.

Although the NHS App serves a different purpose from a diagnostic tool, the implementation lesson is relevant across digital health. Deployment involves preparation, support and changes to everyday routines.

Our IP interpretation concerns what a supplier learns through that work. A pilot may reveal a better way to configure software, present information or connect a tool with an existing process. Teams should assess which developments can become reusable capabilities and how the collaboration arrangements support their use elsewhere.

For a leadership team, this makes the first deployment a strategic milestone. Alongside demonstrating usefulness, it should help establish a workable basis for serving the next institution. The ability to repeat implementation deserves a place in the investment and partnership discussion.

Bertalan Meskó and the patient’s role in defining value

Bertalan Meskó brings patient participation into the picture. The Medical Futurist Institute’s Digital Health and AI Best Practices report, introduced by Meskó, presents digital health as a cultural transformation. It advocates involving patients as active partners in designing services and decisions that affect them.

This perspective helps sharpen the commercial question. A technically sophisticated service still needs a clear account of what it improves for the people receiving care. Product teams can investigate whether the proposed service makes information more understandable, reduces practical burdens or supports more useful conversations with clinicians.

The IP-management implication is to connect protection priorities with that intended value. Which technical capabilities make the experience possible? Which improvements emerge from collaboration with users? How should contributions and subsequent development be documented?

Patient involvement also makes expectations about information use part of the product discussion from an early stage. A sustainable partnership model needs to account for those expectations as the service evolves.

Connecting the ecosystem back to the IP decision

Together, these perspectives reveal several connected management tasks. Camblong’s platform example raises questions about scale and complementary capabilities. Van der Schaar’s research brings validation into focus. Dunscombe highlights the quality of the underlying information infrastructure. Donnelly shows the organisational work behind adoption, while Meskó places patients within the development process.

For MedTech leadership teams, a practical review can begin with six questions:

  • Which clinical decision or care process does our technology improve?
  • Which technical capabilities make that improvement possible?
  • Which assets and permissions support those capabilities?
  • What must our validation and deployment partnerships allow us to do next?
  • Which improvements can we carry into future products and installations?
  • How does our IP position support a credible route to adoption and revenue?

These questions connect with the broader discussion in our IP Market Study MedTech 2026, which examines the intersection of patents, data, AI and regulation.

Camille Terfve’s article provides the starting point: the development of breast cancer diagnostics and personalised medicine demonstrates the possibilities created by richer data. The ecosystem perspective extends that discussion to the relationships and capabilities required to make those possibilities useful.

For innovators, clinical partners and investors, the shared task is to build an IP position that supports collaboration, continued development and dependable delivery. That is how protection decisions can contribute to the journey from health data to better patient care.