While the regulatory and validation burden can be high, it's not surprising that the medical device industry is one of the earliest adopters of additive manufacturing (AM, aka 3D printing). This sector already utilizes a variety of advanced manufacturing technologies and, more importantly, relies strongly on product innovation to maintain a competitive advantage.

Medical devices on a build platform: spinal ALIFs, tibial trays, and acetabular cups. (Credit: nTopology)

AM can impact product innovation on a number of different levels, including product-performance characteristics, time to market, process management — and even supply-chain dynamics. With numerous advanced capabilities derived from additive, optimized medical devices that can help improve patient outcomes are now possible and readily achievable. Companies of all sizes in the medical space have made significant investments into AM, not only as a future technology, but as a proven production process being implemented today.

The introduction of additive manufacturing for creating advanced medical implants has brought on new challenges for design software when working with complex parts. Engineering software is a key enabler of product development and innovation, and new computational techniques are quickly contributing to this area. Both small and large medical companies already have FDA-cleared medical devices that were designed in new, algorithm-based computational modeling and field-driven design software as a part of their workflow.

Computational modeling-based software equips engineers with a powerful capability to create products that are impossible to design in traditional CAD. For example, engineers and designers can easily create and control lattice structures, a critical part of advanced device design enabled only by AM. By extending lattice capabilities to a wider range of applications, more advanced device design and workflow development is enabled.

Additively manufactured femoral stem implants with complex surface structures have a performance advantage of improved osseointegration. (Credit: TU Delft)

Advanced Design Tools

Ordered or randomized lattice structures can be easily be created, and lattice unit cell types can efficiently be varied depending upon loads and other requirements. Advanced design controls such as the fillet between the nodes, beams, and connecting body can also easily be achieved. In traditional tools, modifications like these are time consuming, impractical and, more often than not, impossible.

Repeatable Workflows

Utilizing a unique system of engineering notebooks, a computational modeling platform allows anyone to capture and control critical workflows for downstream use and distribution. Created with the intent to expose only the pertinent variables, organization or project-specific workflows can be locked down and checked into the appropriate PLM systems. This integrated ecosystem of notebooks enforces adherence to standard operating procedures and provides an avenue to capture and reduce design guideline-based tribal knowledge.

A computational modeling platform, used above, allows for the rapid iteration of designs, quickly sweeping between ordered or randomized structures that promote osseointegration. (Credit: nTopology)

Repeatable workflows such as applying porous structures across a large part family are easily achievable. The ability to design these repeatable workflows allows engineers to automate low-level tasks and focus on the engineering work that matters, such as design iterations and verification.

This image shows four medical devices, each with distinct lattice-design space geometries, created from the same algorithm. Substituting only the input design region ensures efficiency and repeatability in the design process. (Credit: nTopology)

Data Management

Speed, efficiency, and data management are crucial for the best possible product development process. Combining software architecture, a block system, and back-end implicit modeling technology results in robust data and process control.

Blocks represent functions, which can be useful for precisely controlling the shape of a model, interpretation of analysis data, or manufacturing process control parameters. Functions can be locked down and version controlled. If there is a change to a block or function, the system can be a living engineering document that works with the engineer throughout the product development process.

Algorithms form the backbone of computational modeling software; as the software evolves into new versions over time, care must be made to ensure that the new versions will not invalidate a user's preexisting process workflow. In acknowledgment of what the implications are to a validated medical device, production-ready blocks in the software will each retain their own unique version numbers that are independent of the software version. New block versions can become available as needed but all legacy block algorithms can still be supported and accessible regardless of software maturity.

What does this mean for a medical device designer? It means that FDA validation will no longer be the reason why your software continues to live in the Stone Age. A reference to the block version rather than the software version itself allows the old ways and the new ways to all live under a single roof.

This article was written by Alex Meckes, Solution Architect, nTopology, New York, NY. For more information, visit here .