The new framework filters potential harms through three questions: Is the harm relevant to the regulatory decision? Is there a plausible causal pathway linking the design change to the harm? Can simulation add evidence that complements bench tests and clinical studies?

For each selected harm, the framework then asks how much the decision relies on the model and how serious a wrong decision would be. The answers determine how thoroughly the model must be checked — whether it is built correctly, whether it matches real-world measurements, and how certain its predictions are when assumptions and natural variation between patients change the results.

The team tested the approach through a hypothetical redesign of a transcatheter aortic valve implantation (TAVI) device, which replaces a diseased heart valve via catheter without open-heart surgery. The exercise, run under UK CEiRSI's In Silico Regulatory Airlock, examined three questions modeling could answer: how the valve expands and sits in place, whether it disrupts the heart's electrical signals — which can leave patients needing a pacemaker — and whether blood leaks around its edge.

What do the researchers say?

Alejandro Frangi, lead academic scientist and executive director of UK CEiRSI, said: "Medical devices are becoming increasingly complex, but the tools used to evaluate them have not always kept pace with that complexity. Through UK CEiRSI, we are working to provide a practical route for using advanced computer simulations in a way that regulators, manufacturers and clinicians can all trust."

First author Dr. Yidan Xue, a BHF/UK CEiRSI transition fellow at the University of Manchester, said the work helps establish when digital evidence is credible and how it should be assessed, supporting "safer innovation, help reduce development costs and improve access to new technologies for patients while maintaining the highest safety standards."

Co-author Mark Grumbridge, head of clinical investigations at the MHRA, said larger and more diverse virtual patient groups "could ultimately reveal risks missed by conventional studies while reducing the number of people exposed to unproven medical devices." He added that future work will focus on scaling up virtual populations that better reflect real-world diversity.

Wil Woan, executive director of the patient charity Heart Valve Voice, commented that computer modeling, used alongside clinical and real-world evidence, "could help us develop safer devices and bring important innovations to patients more efficiently."

The framework remains a proposal, and the TAVI example was hypothetical rather than a real submission. The researchers believe the risk-informed approach could also support international efforts to let regulators in different countries accept the same evidence.

Publication: Yidan Xue et al., "Risk-informed framework for in silico regulatory evaluation of medical devices," Device (2026). DOI: 10.1016/j.device.2026.101303