5 Ways Simulation in Medical Device Design Accelerates Innovation

Medical device development has always been competitive—recently though, the pace has been quickening. Competition is heating up to get patients higher quality, personalized connected devices that are more usable and affordable.

Clinicians expect devices that simplify and streamline their procedures, cutting treatment time using the latest technology. Medical device giants vie to obtain new technology and intellectual property. As a result, stakeholders demand an increase in speed to market while pushing the boundaries of innovation.

These demands on device development teams must be balanced with reality. Device design is increasingly complex; modern devices frequently incorporate complex electronics, subsystems, and digital connectivity. There’s also heightened demand for access to real-time patient data relevant to a procedure.

This has both technological and regulatory hurdles. Full integration increases the risks of flaws within and between systems. Derisking and optimization exercises are key to managing an effective design process.

Computational modeling and simulation (CM&S) offers a compelling approach to both assess and improve medical devices ahead of physical testing. By providing accurate data of given design change’s impacts, CM&S allows more confident alterations to be made. This includes comparing parametric changes including material properties, geometry, and boundary conditions.

CM&S can inform development pathways with higher confidence before engaging in expensive and time-consuming part fabrication, builds, and physical tests. Not only do development costs decrease, timelines compress by reducing this design-procure-build-test iteration cycle.

All this describes the approach’s merit. Following are some topical examples of computational modelling being applied to medical device design. Several compelling case studies highlight the use of computational modeling in:

• Worst-case determination in articulated assemblies
• Seal testing critical interfaces
• Thermal management
• Structural optimization to reduce failures
• Drop testing medical devices

1. Worst Case Determination in Articulated Assemblies

Articulated assemblies, such as surgical instruments and imaging positioning tools, must function reliably under a range of motion, load, and imaging conditions. Identifying worst-case scenarios—where the device-under-test (DUT) is subjected to maximum stress, strain, or displacement—is critical for ensuring long-term performance and safety. Computational modelling enables detailed analysis of these scenarios without the need for exhaustive physical testing.

In one case study, the script and structural finite element analysis (FEA) of a surgical positioning guide were used to explore thousands of device orientations and configurations. The surgical guide’s complex geometry and highly variable component positioning led to an uncertain worst case. First principles or experimental analysis would have taken more effort and lengthened the investigatory timeline, slowing the project down and raising costs.

Simulation provided an efficient and modular approach. Worst-case scenarios for different components were identified by analyzing the stress distribution and deformation in the full range of possible positions. Limited experimental setups validated model results, creating a clear path for device verification.

This led to higher team confidence during testing and regulatory submission.

2. Seal Testing Critical Interfaces

Many medical devices require sealed interfaces to ensure leak-proof seals, including drug delivery systems, diagnostic equipment, and implantable devices. Seal failure can lead to significant issues and device malfunctions impacting device safety and efficacy. CM&S allows for interface optimization before ordering expensive physical parts, saving time and money compared to physical builds and testing.

Structural FEA was used to simulate the stress and deformation of O-rings and the surrounding interface materials under various squeeze conditions. Some aspects of note:

• Over-compression of O-rings can cause plastic deformation and effect pressure thresholds for leakage.
• Interfacing materials used to retain and squeeze the O-rings are not rigid and bow due to the O-ring pressure. This can reduce contact on the O-ring or undue stress in those materials.
• A non-uniform force profile exists along the O-ring interface which is difficult to approximate using first principles, justifying the use of a model for assessment.

By modeling with accurate material properties and representative O-ring geometry (e.g., a contoured O-ring groove), predictions were made on sealing performance and potential failure points identified. Insights gained from these simulations led to design modifications—selective interfacial material thickening and optimizing percentage squeeze on O-rings. This improved the reliability and durability of the seals and interface.

Using CM&S not only enhanced the safety of the device but also reduced the chance that physical builds and testing would require another iteration. It derisked the approach ahead of in-situ tests and device use.

3. Thermal Management

Effective thermal management is crucial for many medical devices containing electronics, such as high frequency actuated devices, diagnostic equipment, and some implantables. Overheating can compromise device functionality and safety.

Computational Fluid Dynamics (CFD) and thermal simulations (both solid-state and fluid) can play a key role in designing systems that effectively manage heat.

The analysis of a lab-based diagnostic device for breath analysis highlights the application of solid-state thermal and CFD in order to manage thermal effects on the system. First principles approximated the power levels needed to keep the system at a specific temperature, which was needed to maintain gas sensor calibration and prevent internal condensation of patient breath samples.

CFD offered insight to more accurately simulate heat generation, steady state heat at key locations, and dissipation within the device. The simulations identified areas where heat accumulation risked component damage or affected device performance.

These insights identified opportunities to improve system design. Heat sinks and overall material selection were confirmed as adequate to manage thermal loads. CFD insights resulted in higher reliability, reducing failure point potential and improving device longevity.

4. Structural Optimization to Reduce Failures

Structural optimization is critical in medical device development to ensure devices can withstand operational stresses and reduce the risk of failure. Computational modelling allows analysis that enhances structural integrity, leading to more robust and reliable devices.

In a compelling case study, a focused effort was undertaken to improve a brain-surgery cannula’s geometry. As the luminal catheter is tethered at the top of the device, the annular cannula had a higher risk of a clinician catching the catheter as they brushed by the device.

An MRI imaging environment prevented use of robust metallic tubing, so a brittle non-magnetic ceramic was used as structural component, further increasing the chance of breakage. All of this could occur while the device was implanted in the brain and in use.

Originally, the cannula core had an annular cross-section, but different geometric shapes were pursued for higher reliability of use. However, these reduced the polar moment of inertia/overall strength at a variety of orientations, so a question remained about how different forces on the cannula—at the distal and proximal tips during retention with a thumb-screw—would affect strength.

Using structural FEA, various loading conditions and orientations were simulated to identify stress concentrations that could lead to fractures or other failures. By iterating designs, the optimal design was found by comparing maximum stress in geometries and relating them to safety factors against the brittle ceramic’s ultimate tensile strength.

The optimized design demonstrated significantly improved strength and durability. It reduced both the likelihood of failure during insertion/use and the need for subsequent revision surgeries, enhancing patient safety and device reliability.

5. Drop Testing Medical Devices

Drop testing is essential for medical devices that may be subjected to impacts or accidental drops during their lifecycle. Mobility classifications under IEC 60601-1 define what kind of tests and testing conditions.

However, going straight into physical testing risks ordering expensive components, lengthy builds, and testing just to discover a device breaks and is unreliable, leading to another lengthy iteration to assess the assumed design improvements.

CM&S enables drop and impact testing with shorter timelines and lower effort, all while predicting effects ahead and allowing for agile design changes before ordering and building. It also allows far more insight into drop impact effects on components.

Threshold risk of failure effects on materials and components can be reviewed in addition to the physically observed failures of classical testing. Teams then gain higher confidence ahead of formal device testing, reducing program risk, timelines, and costs.


A case study involving a headset device showcases drop testing simulations and their insight. Using explicit dynamics and FEA meshing, a drop of the device was simulated from various heights and orientations onto a rigid floor. Simulations revealed impact-induced stress distribution and highlighted weak points in fastening regions, both between housing and within internal components. This prompted design adjustments to enhance impact resistance and component/enclosure retention.

Stress concentrations in narrow cross-sections, such as hinges, were also highlighted and changes were implemented to improve interface strength and rigidity. By incorporating these changes, device durability was significantly improved, ensuring reliable performance even after accidental drops. This also provided greater confidence in device safety for users.

Conclusion

Case studies illustrate the transformative impact of CM&S to speed medical device development and innovation. From ensuring the reliability of seals to determining worst-case scenarios in articulated assemblies, computational modelling has proven to be an indispensable tool.

By providing detailed insights into device performance and enabling iterative design improvements, these techniques accelerate innovation while reducing development costs and enhanced device safety and efficacy. As computational capabilities continue to advance, the role of modeling and simulation in medical device development will become even more significant, leading to better patient outcomes and mature medical technologies.

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