Four Ways Computational Modeling and Simulation Reduce Medical Device Design Costs

The high cost of healthcare is a perennial conversation in our society, and doubly so in an election year.  One way for medical device manufacturers to address this challenge is by finding ways to reduce the cost of development for innovative devices.  The use of computational modeling and simulation is emerging as an effective approach reducing development cost and time for bringing devices to market, and this article highlights four ways medical device companies are using it.

One of the main ways that we can save time in medical device development is through virtual prototyping— using computational modeling and simulation to look at the device-tissue interactions before any parts or prototypes are built. Using these virtual methods to predict the device performance allows the research and development team to identify design challenges, tradeoffs, and ultimately the solutions earlier in the design process. Design changes made earlier in the concept and ideation phase are many orders of magnitude less expensive than those made during commercialization and verification testing, so the benefit of virtual prototyping accumulates quickly. This approach also allows for design teams to gain understanding into how different parts of the system work together and identify any interaction challenges early in the process, reducing the time spent correcting design flaws by avoiding them all together.

With increases in hardware capabilities, better sensor options, and more sophisticated methods for design, there are a lot of inputs available in the design of a medical device.  Most inputs are interrelated in some way and keeping track of how a change propagates through the entire system is impossible for all but the most trivial of applications. Using computational modeling and simulation to perform a sensitivity analysis helps to track this complexity and identify the main design inputs that drive the critical result for the patient. By using simulation to vary the inputs and predict the outcome, design teams learn how sensitive the result is to each input and can focus their efforts around the critical few, saving development time and cost.

By Arlen Ward | ASME

Image Credit: Arlen Ward / ASME

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