A Case for Open-Source Medtech

Consumer Electronics Principles Applied to Healthcare

The difference between consumer electronics and medical devices isn't just philosophical — it's mathematical. When Mary Lou looks at healthcare through her consumer electronics lens, she sees an industry that has rejected the fundamental principles that made modern technology possible.

The Scale and Quality Paradox

Mary Lou's experience as a former CTO at Intel gives her a unique perspective on quality standards. At Intel, "Our sample size was 10,000 units" for quality testing. In medical devices, she encountered a startling reality: "The FDA considers a quality build 10 units a year." 

"Ten units? There's nothing quality about that," she says.

This isn't just about volume — it's about access to innovation itself. Moore's Law, the observation that the number of transistors on an integrated circuit doubles every two years with minimal rise in cost, has driven the consumer electronics revolution. This requires massive scale and the $10+ billion semiconductor fabrication facilities that produce millions of units with rigorous quality control.

"You don't get to be in these $10 billion fabs if you ship 10 units a year for 13 years," Mary Lou explains. "And so you're thrown out of the fab."

The medical device industry's approach creates a paradox: by limiting access until theoretical perfection, it produces devices that are actually less thoroughly tested than consumer products used by billions of people daily. Meanwhile, medical device companies either buy their own expensive fabrication facilities or settle for lower-quality manufacturing — both paths leading to products that cost exponentially more than they should.

Openwater’s General Purpose Paradigm

Consumer electronics thrive on modularity and continuous improvement. Today’s smartphone combines sensors, lasers, cameras, and radios — hardware that once required entire laboratories — into a single device that gets smarter with every software update.

Medical devices, by contrast, are typically single-purpose machines built for narrow indications. They're expensive, static, and often functionally isolated.

Mary Lou wants to change that. “We make general-purpose devices that can be changed in the software layer,” she says. That means a single Openwater unit could be used to diagnose a stroke, treat depression, or destroy cancer cells — all with software-driven protocols. Rather than inventing a new machine for each disease, Openwater’s strategy is to treat the device like a platform — one that evolves over time.

This approach isn’t just more flexible — it’s more cost-effective. The core hardware includes ultrasound arrays, laser systems, and advanced sensors already present in many smartphones. “There’s no reason we can’t scale this to full consumer electronics,” Mary Lou says. Instead of a million-dollar tool for a single disease, Openwater envisions a $500 device that can support dozens of clinical applications.

Unlike most medical device companies, Openwater didn’t pick a single rare disease to target first. While Mary Lou’s investors urged her to start small — “Pick a single rare disease, get that approval first, and go and ship that” — she saw a fundamental flaw in that logic. “Then you’re a million-dollar solution for a single rare disease,” she says.

Instead, the team focused on big diseases but also the “long tail of diseases” — conditions that may not justify a bespoke device, but could benefit from a versatile, lower-cost platform. This strategy requires a business model that prioritizes breadth over exclusivity, and one that assumes scale from the start.

Rethinking the Traditional Medical Device Path

Mary Lou's critique of medical device development comes from watching an industry trapped in "Eroom's Law" — Moore's spelled backwards — the observation that drug discovery is becoming slower and more expensive over time, despite improvements in technology. The name highlights the contrast with Moore's Law's exponential technological advancements.

The current medical device development system creates a fundamental tension between safety and progress, according to Mary Lou. It requires collecting safety and efficacy data serially — one study after another, one indication at a time. While everyone agrees that more data leads to better outcomes, Mary Lou questions the methodology: "We all want more data. A regulator wants more data. Doctors and patients want more data. We want less risk… But why not collect it in parallel with these general-purpose devices?"

Traditional medical device companies rely on regulatory moats — the years and millions invested in approval create competitive barriers. But when development timelines stretch decades, the moat becomes a trap that prevents the very innovation it's meant to protect. Mary Lou's perspective shifts the competitive advantage from exclusivity to execution: "Your moat is providing an innovation engine that's trustworthy." Rather than relying on regulatory barriers, companies could compete on their ability to iterate, improve, and serve patients better.

Perhaps most provocatively, Mary Lou questions whether pre-market development standards actually serve patients. As she puts it, "The healthcare system is anti-innovation. It's 20 to 40 years to ship a product." Current regulations often require custom devices costing hundreds of thousands of dollars to prove their worth before companies can invest in manufacturing scale. "If we get regulatory approval for something that costs a million dollars, we can't make any changes to it," Mary Lou observes. The system locks in both the technology and the cost structure at the moment of approval, preventing the kind of continuous improvement that drives progress in other industries.

This creates a chicken-and-egg problem: devices remain expensive because they can't achieve scale, and they can't achieve scale because they're expensive. Instead of requiring each company to generate its own isolated dataset, what if safety information could be shared across the industry, reducing redundant studies while building larger, more comprehensive safety databases?