Abstract
With the rise of digital health and the ability to continuously monitor cardiovascular function, a new wave of innovation in medical devices has begun. However excessive reliance on physical, animal, and human testing continues to drive up development time and cost, often becoming prohibitive to innovation. To address these challenges, the Living Heart Project was launched with leaders from academia, industry, clinical practice and regulatory bodies and a mission to revolutionize cardiovascular science - delivering the first fully functional whole heart simulation. A key advantage of this type of model is to cost effectively test a device in a human environment early in its development. Further, an entire cohort of patients representing the target population can be constructed, allowing an in silico clinical trial (ISCT) to be performed, potentially yielding unprecedented insight into the function of the device in the real world while modifications are still possible. For this reason, ISCTs are expected to become an increasingly important form of evidence that will reduce animal testing, and enable the design and execution of real clinical trials with increased likelihood of success.
We discuss a framework for design and execution of an ISCT using an example of an edge-to-edge repair “mitral clip” device to treat Secondary Mitral Valve Regurgitation (SMVR). Beginning with a base model of the mitral valve assembly, a systematic process is defined to build a small but representative cohort of patients to be used for the ISCT, leveraging AI methods trained with the virtual patient models. Using this cohort, we then conduct the ISCT to assess device performance. We conclude by discussing how ISCTs of medical devices can help inform clinical trial designs, identify the most relevant patients to study, and support evidence of device safety and effectiveness.
