From Medical Devices to Digital Health Systems: The New Limits of Technology Transfer
Technology transfer is often described as the movement of knowledge from research to application. In simple cases, this sounds like a clean handover. A patent is licensed. A prototype is sold. A technical document is shared. A research result is passed to a company that can commercialize it.
In MedTech and Digital Health Systems, this view is too simple!
A medical technology does not become valuable merely because the technical principle works. It becomes valuable when it can be used safely, accepted clinically, integrated into workflows, reimbursed by health systems, trusted by patients and maintained over time. The transfer object is therefore not only a technology. It is a business architecture around technology.
This is why MedTech is such a powerful field for understanding the limits of technology transfer. Connected healthcare innovation combines medical devices, software, data processing, sensors, artificial intelligence, cloud infrastructure, cybersecurity, clinical workflows, regulatory pathways and service models. Value no longer sits only in one physical product. It emerges across the system. For IP management, this changes almost everything.
The transfer problem begins with appropriability
The first limit is the appropriability problem. Knowledge differs from physical goods. If a machine is sold, the seller no longer has that machine. If knowledge is disclosed, both parties may be able to use it. This is the classic problem of information as an economic good.
In MedTech, this becomes a practical business dilemma. Imagine a company that has developed a method for detecting early signs of disease from sensor data. To convince a hospital, investor or device manufacturer, the company must reveal enough to make the opportunity credible. It must show clinical relevance, technical performance and commercial potential. But the more it reveals, the more it risks losing control over the core insight.
This is especially visible in Digital Health Systems. Software logic, data structures, clinical workflows and platform interfaces may be easier to imitate than complex physical production assets. Patents may protect certain technical features. Trade secrets may protect training data, validation routines, model tuning and deployment know how. Data rights and contracts may regulate access, liability and value sharing.
But no single instrument solves the full problem. The strategic task is to design a protection structure that allows enough disclosure to enable collaboration, while preserving the control points that create bargaining power. This is why IP in MedTech cannot be reduced to filing activity. It becomes part of the transfer architecture.
Documentation is not enough
The second limit is the difference between codified and tacit knowledge. Codified knowledge can be written down, standardized and transferred through documents, patents, protocols, source code, regulatory files or technical manuals. Tacit knowledge is different. It is embedded in experience, routines, judgment and clinical context. MedTech is full of tacit knowledge.
Consider a wearable device for monitoring cardiac risk. The hardware design may be documented. The algorithm may be described. The software may be stored in a repository. But the practical knowledge about how patients actually wear the device, when false signals occur, how physicians interpret alerts and where clinical trust is created cannot be fully captured in documentation. It must be learned through use.
This is why a technology transfer project can succeed on paper and still fail in practice. A university lab may create a promising prototype. An industrial partner may receive the technical package. The patent rights may be licensed. Yet the receiving organization may still struggle to reproduce the validation process, understand the clinical environment or translate the prototype into a certifiable product. The value was never only in the invention. It was also in the routines around the invention.
For IP management, this means that patents and documents must be complemented by training, collaboration, process design and knowledge management. A good transfer structure asks which knowledge can be codified and which knowledge needs people, routines and repeated interaction.
Sticky information shapes the real economics of transfer
The third limit is sticky information. Information is sticky when it is costly to move from one actor or context to another.
In MedTech, sticky information is everywhere. Hospitals know how workflows actually operate. Patients know how devices are used in daily life. Physicians know where trust is created or lost. Manufacturers know production constraints. Software providers know system architecture. Regulators know evidence expectations. Payers know reimbursement logic. No single actor holds the whole picture.
This creates a major transfer challenge. If the technology provider does not understand the buyer’s use context, the technology may be transferred in a form that does not fit. If the buyer cannot understand the technology without receiving sensitive information, evaluation becomes difficult. Both sides need information from the other side before they can commit. This is exactly where transaction costs begin to rise.
Take an AI based radiology workflow tool. The hospital wants to know how the model performs across patient groups, scanner types and clinical scenarios. The start up wants to protect its model architecture, data pipeline and validation logic. At the same time, the hospital’s workflow data may be ethically and commercially sensitive.
Both sides need disclosure. Both sides need protection. Both sides face uncertainty before the agreement even exists. This makes MedTech transfer different from a clean market transaction. It is often staged through pilots, feasibility studies, limited licenses, data sharing agreements and co development structures. These stages reduce uncertainty, but they also create dependency.
Modularity helps scaling, but healthcare needs integration
The fourth limit lies in organizational design. Technology markets work more easily when innovation can be decomposed into separate tasks. If components can be developed independently and connected through clear interfaces, transfer becomes easier. Modularity can reduce costs, shorten development cycles and support customization.
Digital Health Systems clearly need modularity. Sensors, algorithms, dashboards, data layers, cloud services and clinical reporting tools should be structured so they can be reused, adapted and scaled. A platform that integrates different data sources and clinical modules is more transferable than a closed system built for one use case. But healthcare also requires deep integration.
Patient safety, clinical reliability, cybersecurity, regulatory accountability and medical responsibility cannot be managed as isolated modules. A software component may work technically but fail clinically because the alert logic does not fit the workflow. A sensor may collect accurate data, but the data may not support a meaningful clinical decision. An algorithm may perform well in a controlled validation study but become unreliable in another hospital environment. This creates a central tension. MedTech needs modular technical architecture, but it also needs integrated clinical meaning. The strategic IP question is therefore not only what can be protected. It is also what can be separated without destroying the value of the system.
IP becomes a decision architecture
Connected MedTech changes the role of IP. It moves IP away from a narrow protection function and turns it into a decision architecture for collaboration, control, market access, risk management and competitive positioning. This matters because the relevant control point may sit in different places.
In one case, it may be the sensor architecture. In another, it may be the processing of physiological data. In another, it may be the clinical interpretation logic, the software workflow, the user interface, the interoperability layer, the training dataset, the evidence package or the reimbursement related service model.
A patent strategy that only protects the physical device may miss the layer where value is actually moving. A trade secret strategy that protects too much may make collaboration difficult. A contract that controls data access but ignores regulatory responsibility may create future risk. A platform model that depends on third party infrastructure may create hidden bargaining weaknesses.
This is why fragmented advice is no longer enough. A patent filing, a data protection review, a regulatory assessment, a contract template and a freedom to operate opinion may each be correct in isolation. But the company may still lack an integrated answer to the most important question: where does control actually arise?
The real market is a market for usable knowledge
MedTech and Digital Health Systems show that the market for technology is not just a market for patents or prototypes. It is a market for usable, trusted and integrated knowledge.
Breakthrough medical technologies do not travel by themselves. They need transfer structures that carry technical function, clinical meaning, regulatory credibility and economic control at the same time. A successful transfer strategy must therefore ask more than: Can we license this invention?
It must ask which knowledge can be codified, which knowledge requires people and routines, which information is sticky, which parts of the system can be modularized, which control points create bargaining power and which IP instruments support the specific business architecture.
This is the deeper lesson from MedTech. In connected healthcare, technology transfer is not the handover of a finished object. It is the construction of a structure that makes knowledge usable across boundaries. And that structure is increasingly an IP management task.
Excerpt from the lecture slides:
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If you would like to learn more about the latest developments regarding MedTech and IP, you can find our Industry Focus on the subject here:
👉 The Structural Shift of IP in MedTech – IPBA® Connect
Here is a current overview of IP trends in MedTech & Digital Health Systems:
Here is a recent market study on IP in MedTech:
