Contributed Commentary by Ian MacGregor, HiArc
February 20, 2026 | Precision medicine is often described as the future of healthcare. But from an engineering standpoint, it’s already here, and it’s forcing diagnostic instruments to evolve faster than most development cycles are comfortable with. We’re asking instruments to do more than confirm a suspected diagnosis. We’re asking them to deliver specificity, speed, and confidence in environments that aren’t always predictable. That’s a major shift from the days when “good enough” screening could drive clinical decisions.
In many cases, the value of precision diagnostics comes down to a simple question: can you identify exactly what you’re dealing with, quickly enough to act on it?
Precision Starts with Specificity
One recent project I led as the system engineer and technical lead centered on that exact challenge. The instrument is used to help diagnose patients infected with an unknown or only partially known pathogen.
In a typical workflow, a clinician might have a sick patient and a sample that suggests infection, but not a clear answer. A system designed for precise microbial identification, however, can not only determine the microbe family but also identify the exact subspecies in many cases. That level of specificity supports a more tailored clinical path.
In fact, in this case, the instrument sits within a broader diagnostic ecosystem. Once a specific microbe is identified, follow-on susceptibility testing can help confirm whether a particular treatment will be effective before it’s administered. That’s one of the practical ways precision diagnostics supports personalized medicine: fewer assumptions, more evidence.
Smaller, Easier, and More Usable
One of the most significant shifts in diagnostics engineering today is the push to make complex instruments smaller and more accessible, bringing advanced capability closer to point of care or near point of care. In this program, the predecessor device was large: six feet tall, floor-standing, and difficult to work with and service. The new system we developed was designed as a countertop device: smaller, easier to use, and with higher uptime and lower cost.
From the outside, that might look like a straightforward product improvement. From the inside, it’s a deep engineering challenge. Shrinking a platform changes everything: thermal behavior, service access, component arrangement, manufacturability, user interface assumptions, and the overall reliability strategy. When you make a device smaller, you don’t eliminate complexity, you compress it. And compressed complexity is where engineering discipline matters most.
Manufacturability Needs Precision
The core measurement approach in this instrument is mass spectrometry, which means the system includes extremely precise internal components commonly referred to as ion optics. These parts are complex, sensitive, and difficult to manufacture consistently.
And consistency matters. When your instrument is used to make microbial identifications, small variations in manufacturing can translate into variation in results. For a precision system, that’s unacceptable. One of the biggest challenges in this program was making those ion optics “as close to perfect as possible,” but doing it in a manufacturable way. That required a lot of iteration to refine processes that could produce the required precision repeatedly.
A major strategy was removing as much of the human element as possible from the assembly and manufacturing process. In other words, if a critical alignment depends on craftsmanship and you don’t have a scalable instrument, you have a fragile one.
Serviceability is a Design Driver
Another requirement that shaped the entire architecture was serviceability. The system needed to be serviceable within a few hours, only from the front of the instrument, and only using small hand tools that could be carried in. That requirement drove how we arranged components and how we designed access. It also revealed something that’s often true in diagnostics engineering: when you design for serviceability, you frequently improve manufacturability at the same time.
We brought a manufacturing engineer into the program at the beginning, during requirements, concept, and early architecture, specifically to make sure the plan was something a manufacturing line could support. We made several small changes as a result, and those changes paid off later.
As we moved into detailed design, we also involved supply chain early and often. Many components weren’t standard off-the-shelf parts, and we wanted to make sure we had a clean supply chain before finalizing the design. We made changes based on those discussions too.
This is a pattern I’ve seen repeatedly: the earlier you integrate manufacturing and supply chain thinking, the fewer painful surprises you face during scale-up.
What’s Next: Smaller, Cheaper, Closer to the Patient
Looking ahead, I believe generalized processing power will continue to get smaller and cheaper and so will many electronic and detection systems. That will open the door to smaller, more portable diagnostic devices, potentially down to handheld form factors in some applications.
As that happens, I expect a gradual shift: a slow reduction of large, centralized lab diagnostic dominance, replaced by more local, near point-of-care capability. That transition will change everything from software and user interface expectations to service models and validation strategies. It will also push engineering teams to think differently about robustness, manufacturability, and usability.
Precision medicine isn’t just a scientific revolution. It’s an engineering one. The diagnostic instruments that succeed won’t only work in ideal conditions, they’ll be engineered to deliver precision in the real world, at scale, where care actually happens.
Ian MacGregor is a lead systems engineer at HiArc, where he serves as technical lead for the development of complex diagnostic instruments from concept through commercialization. His work focuses on systems design, integration, manufacturability, and building high-performance platforms designed for real-world clinical reliability. He can be reached at Ian.MacGregor@hiarc.inc.