Modeling, simulating, optimizing medical devices

Developing and manufacturing medical devices has never been easy. Patients desire more personalized care. Regulatory agencies are growing stricter. Practitioners, policymakers, and consumers want reduced costs. And competition is fierce – with time to market often determining which products will succeed and which will fade away.

At the same time, medical devices are not only becoming more complex, but also more prevalent. According to the World Health Organization (WHO), roughly two million different types of medical devices are available today, spread across more than 7,000 device groups. That number will only get larger as the population grows older and technology advances.

All medical device manufacturers aim to develop products that are innovative yet safe, low-cost, and high performing. These products must also meet stiff regulatory hurdles. They are often customizable, should be cost-effective to produce and use, and delivered in the shortest time possible to beat the competition.

Climbing the bar

Medical devices range from artificial hearts and robotic surgical systems to stents, skeletal implants, and drug delivery devices. They’re mechanical, chemical, and electrical in nature, boasting complex software systems, advanced fluidic and biologic controls, and heterogeneous assemblies of traditionally and additively manufactured parts. What’s more, each component and subsystem must work in perfect harmony, often reporting data to external monitoring systems nearby or in the cloud. No matter their complexity and function, they all serve to extend, improve, and frequently save lives.

Numerous rollout challenges exist for all medical products, but for designers of implantable and other moderate-to-high-risk devices, the bar is exceptionally high. Chief among these is that conventional testing and validation methods take a long time. After months or years of product development, manufacturers must conduct extensive benchtop testing of physical prototypes, followed by equally rigorous animal studies. Only then is the company allowed to conduct human clinical trials which are even more costly and time-consuming.

Doing it digitally

It’s called computational modeling and simulation, or CM&S. Some may think of it as the digital twin, but this model-based design and manufacturing approach is more comprehensive. It uses complex algorithms to predict how medical devices will react to certain stimuli including heat, friction, fatigue, impact, and contact with various body fluids. It also makes collaboration between teams and facilities easier, simplifies the prototyping and production processes, and eliminates mistakes before they occur.

For example, developers of orthopedic implants might use CM&S to measure the number of cycles a knee or hip implant will sustain before failure. Pacemaker designers can use it to model battery life or predict operating temperatures. Stent manufacturers can analyze biochemical interactions between their products and the surrounding tissues, while oncologists use CM&S to determine the effect an X-ray device will have on a tumor.

In each case, there’s no need to implant the device in a lab animal for evaluation, let alone a human. Benchtop testing requirements are similarly reduced. All analyses are performed virtually, often long before a physical prototype has been constructed. This reduces costs, achieves optimal designs faster, and enhances product performance. And, because CM&S doesn’t carry the burden associated with physical testing, engineers enjoy greater design freedom, with significantly less fear of failure.

Further, in-silico testing goes where in-vivo cannot. For instance, there’s no easy way to measure factors such as blood turbulence or tissue stress once a medical device has been implanted. Electromechanical interactions within the body are largely a mystery. Nor can manufacturers assess long-term device performance without post-mortem analyses.

The path forward

CM&S software eliminates these challenges. With minimal training and readily available computing power, device manufacturers can analyze the entire product life cycle and its many elements. Designers can take their initial concept and walk it through virtual testing, prototyping, product launch, production, and end-of-life scenarios. If they decide that additional enhancement or design changes are needed at any stage, doing so is easy. No retooling, new part orders, endless meetings, and most importantly, no costly product recalls.

CM&S also eliminates the silos of departmental information. All product data from project inception to deployment and beyond is available on a single platform, assuring transparency. The electrical engineers can see what the software engineers see; quality assurance has access to the same information as mechanical design and executive management. This increases collaboration and improves communication while providing the entire company a single source of information.

Of course, none of this is meant to imply that physical testing has or will soon become obsolete. CM&S does, however, minimize dependence on in-vivo and benchtop testing and serves to qualify its results. This tool has become so important that the FDA’s Center for Devices and Radiological Health, in cooperation with the American Society of Mechanical Engineers (ASME) Verification and Validation Committee, has formed a Computational Modeling of Medical Devices subcommittee to help standardize its use.

Today’s medical device manufacturers play a crucial role in developing safe yet robust healthcare products. That role will only become more important throughout the years as products become more capable and connected. While adopting a digital design and manufacturing strategy is the clear path forward for many companies – aerospace, automotive, and commercial product manufacturers among them – for those in the medical industry, it’s critical. This is why Dassault Systèmes will continue to build on its 3DExperience platform, with CM&S a key component. It’s time to take medical device testing digital.

Dassault Systèmes
https://www.3ds.com

About the author: Karl D’Souza is the life sciences industry solution experience director at Dassault Systèmes. He can be reached at kdz@3ds.com.