By Sean Fenske, Editor-in-Chief

Personalized medicine has been the goal of healthcare for years. As technology inches closer to assist in reaching that mark, aspects of the effort are slowing or have even stopped making progress. When this occurs, a new way of thinking or a different approach may be required. Sometimes, the technology exists but it’s not being used as efficiently or effectively as it could.

Within the orthopedics sector, patient-specific implants are viewed as the outlier. Someone needing a joint replacement, for example, is more likely to get an off-the-shelf solution than one developed specifically for their anatomy. In this instance, the technology exists to develop these implants, but the protocol used takes much too long to ever consider attempting to accomplish this at scale for the majority of patients.

To explain how this process could be done differently and more efficiently, Daniel Crawford, Founder and CSO at Axial3D, responded to several questions in the following Q&A. He describes the tools that could be leveraged to fabricate patient-specific implants at the scale required to provide custom implants to more people. He also addresses the obstacles and bottlenecks associated with the more traditional process of creating these solutions and how to resolve them.

Sean Fenske: What innovations and industry forces are driving the interest in patient-specific implants?

Daniel Crawford: On the innovation side, we’ve seen decades of advancements in orthopedic implants; improved alloys, enhanced osteointegration, and specialized coatings have pushed traditional materials to their limits. However, we’ve reached a point where further progress lies in tailoring these innovations to individual patients. The real game-changer in recent years has been the widespread accessibility of advanced computing and machine learning. What once required massive investments in hardware and infrastructure can now be achieved through democratized cloud computing. This shift allows companies, even smaller ones like ours, to develop powerful algorithms that automate complex tasks like data segmentation, making patient-specific solutions more accessible and scalable.

From an industry perspective, the most powerful driving force is the patient. Personalized care leads to better outcomes—patients are more informed, surgical time is reduced, and risks like infection or implant failure decrease. A perfectly fitted implant can last a lifetime, reducing the need for revision surgeries and improving overall patient satisfaction. As more clinical evidence highlights these benefits, the industry will inevitably move toward more customized, patient-specific solutions, especially in orthopedics.

Fenske: What are the most significant challenges involved with producing patient-specific implants?

Crawford: One of the most significant challenges in producing patient-specific implants is scaling production to meet high demand. For example, over 800,000 knee replacements are performed annually in the U.S. alone. Transitioning all these procedures to patient-specific implants using traditional manufacturing methods is extremely difficult at scale due to the resource-intensive, linear workflow.

Currently, the process involves several time-consuming steps: data acquisition, image segmentation, CAD modeling, and manufacturing—all typically handled by engineers in a sequential manner. As demand grows, this linear approach creates bottlenecks, leading to longer wait times for patients. Reducing the time from scan to implant production to just a few days is a major industry goal, but achieving this with current methods is nearly impossible. Meeting that demand would require an impractically large workforce of engineers.

The solution lies in breaking apart this linear process and introducing automation and parallel workflows. By leveraging AI and advanced software, companies like ours can streamline critical steps, enabling engineers to focus on validation rather than manual design. This shift toward automated, scalable solutions is essential for making patient-specific implants widely available without compromising speed or quality.

Fenske: How can patient-specific implants be produced at the necessary scale to meet industry demand rather than with current methods where significantly fewer are manufactured?

Crawford: To produce patient-specific implants at the scale needed to meet industry demand, the production process must be reimagined and optimized for efficiency. The traditional, linear workflow—where each step is handled manually and sequentially—creates bottlenecks that limit scalability. The solution lies in breaking down this process, identifying key inefficiencies, and introducing automation and advanced technologies to streamline production.

One major bottleneck is image acquisition. Accessing patient data from hospital PACS systems can be slow and fragmented, often relying on outdated methods like CDs, USBs, or manual file transfers. Implementing secure, cloud-based infrastructure allows for seamless, compliant data retrieval, drastically reducing delays and accelerating the start of the design process.

The next critical step is segmentation—extracting patient-specific data from medical scans. This process is still largely manual, taking hours of meticulous work by engineers. By integrating AI-assisted segmentation, this time can be reduced from hours to minutes. Rather than replacing skilled engineers, AI enhances their capabilities, enabling them to focus on quality control and complex cases while routine tasks are automated.

Beyond segmentation, the design and production of surgical guides and implants can also benefit from automation. Using machine learning and generative AI to handle repetitive design tasks ensures consistent, high-quality outputs at scale. This shift from manual to automated workflows dramatically increases production capacity and reduces lead times, making it possible to meet the growing demand for patient-specific devices and implants.

By combining cloud computing, AI-driven segmentation, and automated design processes, the industry can move beyond current limitations and deliver personalized surgical solutions on a much larger scale.

Fenske: What’s the answer for a company that may not have the latest computing hardware to handle all the data inputs associated with patient-specific implants?

Crawford: For companies that don’t have the latest computing hardware to handle the data for patient-specific implants, the solution lies in cloud computing. Hosting applications in the cloud gives you access to powerful computing resources—like high-performance CPUs and GPUs—without needing to invest heavily in hardware or build out a dedicated team to manage it all.

Traditionally, getting started with patient-specific implants has required a significant upfront investment in both hardware and software. This has often been a huge barrier, especially for smaller companies, and has slowed the widespread adoption of these technologies. Big upfront costs create bottlenecks, making it harder for innovative solutions to become readily available across the industry.

But cloud computing is changing the game. It’s not just about the tech; it’s also unlocking new business models. Instead of paying massive upfront costs, companies can now adopt a pay-as-you-go approach. You only pay for what you use, which makes it much more affordable and accessible.

At Axial3D, we’ve fully embraced this model. None of our software comes with high upfront costs; everything is usage-based. By leveraging the cloud, we’ve eliminated the need for expensive hardware, large teams, and costly desktop-based software. This drastically lowers the barriers to entry, making patient-specific workflows accessible to companies of all sizes—whether you’re a start-up or a large, publicly traded company. It’s about making innovation scalable and available to everyone, without breaking the bank.

Fenske: Do you have best practices for companies in handling the data being submitted for each patient? How does the company keep track of all the imaging files/data for each patient’s implant?

Crawford: When it comes to best practices for handling patient data and keeping track of imaging files for patient-specific implants, there are a few key things we recommend.

First and foremost, establishing a protocol is critical. Having a standardized method for imaging patients, especially in repeatable procedures like joint replacements, ensures consistency and quality. Repeatable imaging inputs help set the criteria for creating accurate patient-specific implants. That said, we understand that in more complex cases—or situations where no clear protocol exists—this can be a challenge.

That’s where our technology comes in. We apply our tech stack to work with existing protocols or even a minimal viable imaging protocol for patient-specific implants. For example, our system can check whether the necessary anatomy is visible in the scans, identify any missing slices, or flag issues like noise or metal artifacts. All of this can be automatically validated through a cloud instance upfront to ensure the data is suitable for that specific case.

The second critical piece is tracking the data. When imaging files hit our servers, they’re assigned a unique identifier that ties everything together—whether it’s a design history file or a unique patient ID. This ensures the patient’s anatomy is consistently linked throughout the entire process, from manufacturing to the creation of a patient-specific device or plan. It’s all about maintaining traceability and ensuring the data stays organized and secure every step of the way.

At Axial3D, we take data security seriously. We ensure our processes are fully compliant with regulatory bodies and industry standards, safeguarding patient data and maintaining confidentiality. By leveraging secure cloud infrastructure, we also adhere to data sovereignty regulations, ensuring data is processed and stored in the appropriate regions. This means the handling of patient information is secure, traceable, and compliant with the necessary legal and regulatory requirements.

Fenske: Before embarking on developing patient-specific implants, what must companies keep in mind or consider? What aspects are often overlooked?

Crawford: When companies begin developing patient-specific implants, there are a few key considerations—and some common aspects that often get overlooked.

First, the quality management system (QMS) and regulatory approvals are crucial. Patient-specific devices often have nuanced differences compared to off-the-shelf technologies. For instance, transitioning to a patient-specific workflow or creating customized plans can involve specific regulatory requirements—such as annexes in FDA approvals—that aren’t always immediately obvious. At Axial3D, we’ve built robust QMS and regulatory frameworks into our technology, and we often help medical device companies navigate these challenges during their transition.

Another critical aspect is surgeon interaction. With patient-specific implants, surgeons or interventionists usually need to review, tweak, and sign off on the plan or device to ensure it aligns with their preferences and the specific needs of the patient. Many companies overlook the importance of providing surgeons with an intuitive toolset that allows them to make these adjustments asynchronously, rather than relying on outdated methods like video or phone calls. Streamlining this process can significantly improve the overall workflow and manufacturing efficiency.

Finally, the regionalization of data is a major factor that can be missed. If a company is sending patient-specific devices around the globe, they’ll encounter varying data sovereignty rules and regulations on how data can be stored, processed, and shared in different regions. Often, the surgeon’s location and the jurisdiction where the data is processed don’t align, which can create bottlenecks. Leveraging cloud infrastructure to ensure data is stored and processed locally, within the same region as the surgeon, can simplify this process and ensure compliance.

By keeping these considerations in mind, companies can avoid common pitfalls and set themselves up for success in patient-specific surgery.

Fenske: Do you have any additional comments you’d like to share based on any of the topics we discussed or something you’d like to tell orthopedic device manufacturers?

Crawford: I think there’s a lot I could add to the topics we’ve already discussed, but the key message I’d like to share is this: the shift to patient-specific implants and solutions isn’t just on the horizon—it’s happening right now, and it’s moving fast.

In the next three to five years, I predict many high-volume orthopedic devices will incorporate some element of patient-specific customization. Whether it’s a tailored surgical plan for robotic systems or physical guides designed specifically for a patient, these personalized elements are going to become a standard part of the process. This marks a significant shift from the off-the-shelf devices we’re familiar with today toward a much more patient-specific landscape.

One of the biggest drivers of this change will be the need for orthopedic device manufacturers to evolve. Many companies are rooted in hardware-based technologies, but the future is going to demand a transition to software-driven solutions—or at least a hybrid of the two. This shift isn’t easy. Companies that are strong in mechanical or physical engineering often find it challenging to build the software capabilities needed for this new direction.

That’s where we come in. Over the past nine or 10 years, we’ve developed the cloud infrastructure and expertise to help bridge this gap. We work with companies to integrate software into their workflows, enabling them to move toward a more patient-specific, technology-driven future. By embracing this shift now, orthopedic device manufacturers can position themselves to not only keep pace but lead in this rapidly evolving market.

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