Orphaned Innovations, Part 1: The Missing Middle

Good products, real customers, no path forward

Block Print of Monument Valley made by Everett Ruess in 1934 during his journey with the Rainbow Bridge–National Monument Expedition team. Photo courtesy of the Utah Division of Arts and Museums. Source: State of Utah Alice Merrill Horne Art Collection, Utah Division of Arts and Museums.

Here is something that happens every day at research universities. A scientist, or an engineer, or a physician has an idea for a product. Could be modest: a small improvement to a piece of lab equipment, an update to a diagnostic algorithm. Could be significant: a device that makes a common surgery meaningfully safer, a test that catches a disease earlier, a piece of software that gives a clinician needed information at the right moment. The ideas range from mundane to transformative; most of them share one characteristic: they never go anywhere.

Not because they don't work. Not because there are no customers. Because they're misfits in an ecosystem designed for a very specific kind of product.

I’ve spent much of my career watching valuable innovations get quietly stranded in this way. This is the thing I want to explain. And, eventually, do something about.

The Three Inventions

Let me give you some examples, drawn from patterns I've seen repeat across universities and clinical settings. The details are composites, but the problem is not.

A biomedical engineer builds better equipment for tissue culture. Research labs will pay $50,000 per unit. You could sell five hundred units a year at a healthy profit. The product works, the customers exist, the economics are fine, and if you described this situation to a normal person they would say “Ok, so build the product and sell it to the labs.” But there’s no recurring revenue. No platform potential. No network effects. No odds to achieve the kind of returns that attract venture capital. So it sits.

A computer scientist develops clinical decision support software for a specific surgical procedure. Hospitals need it. It demonstrably improves outcomes. It could save millions of dollars and, more importantly, meaningfully improve patient care. But it isn’t an AI platform with applications across fifty procedures. The sales cycle into health systems is long and grinding. This is a good product for a real market, and a good product for a real market is, we’ll come back to this, not actually what the available funding mechanisms are designed to support.

A physician-scientist creates a better diagnostic test for a condition affecting a hundred thousand people a year. The existing commercial lab networks could pick it up and sell it profitably tomorrow. What they need is someone to develop it far enough that it’s a real commercial asset. But the venture investors who might fund that development want a platform for dozens of tests, not one really good one. (The one really good one is, financially speaking, not very interesting to them. More on why in a moment.)

Notice what these three examples have in common. They aren’t ideas that failed to find customers. They’re working ones that can’t find a route forward. They’re orphaned innovations. The product works. The market exists. Someone would pay for it. And yet.

How Venture Capital Works (And Why That’s A Problem)

To understand why this happens, you have to understand what venture capital is actually for.

Venture capital is not a general-purpose mechanism for funding good ideas with real customers. It’s a specific financial instrument with specific mathematical requirements. A venture fund raises money from limited partners (eg, endowments, pension funds, family offices) with the promise of outsized returns. “Outsized” means something specific: five to ten times the invested capital, in seven to ten years, across a portfolio where most investments fail. The structure demands that the winners be very large, because the losers are total losses, and the math only works if enough winners are large enough to return the whole fund.

Mike Partsch, who runs WARF Ventures, the venture fund of the University of Wisconsin’s tech transfer office, explains this directly. “If an entrepreneur said ‘If you invest in us and we’re wildly successful, you could get a 25 to 30 percent return,’ we’d be like, ‘No, not interested.’” He’s not being unreasonable. He’s describing the actual constraints of his fund’s structure. A 25 percent return is an extraordinary result in most investment contexts. For a venture fund, it’s disappointing. The math requires something different.

So when we say a company’s market is “too small for venture capital,” we don’t mean the market is small in any ordinary sense. A business that generates $30 million in annual revenue at healthy margins, helping a hundred thousand patients, is not a small business. It’s a good one. It’s just the wrong shape for the only growth-capital mechanism that touches early-stage health technology. The problem isn’t the size of the opportunity. It’s that the opportunity is the wrong size for the only financing model available.

(The alternative, licensing the technology to an existing company, works well in exactly one industry: pharmaceuticals, where large global businesses have dedicated teams actively scouting for new assets. In most of healthtech and medtech, the licensing market is thin, the buyers are fragmented, and the transition from university IP to commercial product is murky enough that it rarely happens in practice.)

How Universities Think About This

Here’s where it gets interesting. Universities know this is a problem. Or at least some of them do.

Tech transfer offices, and the accelerators and entrepreneurship programs that have grown up around them over the past two decades, are almost universally organized around a single output: new companies. This makes a certain kind of institutional sense. Startups are legible and easy to count. You can report them to your board, feature them in your alumni magazine, compare your number to peer institutions. When the University of Wisconsin’s working group on entrepreneurship released its 2024 report, Empowering the Wisconsin Idea, it noted that UW ranks eighth in the country in research expenditures but thirty-first in startup formation. The gap is framed as the problem to solve.

A better startup pipeline would be valuable. UW has since appointed Lewis Sheats as inaugural director of a new Wisconsin Entrepreneurship Hub, and the language around it is deliberately ambitious.

But here’s the thing: the same report explicitly sets aside other commercialization pathways (eg, licensing to existing companies, product development outside the startup model) as beyond its mandate. The most self-aware reform effort currently underway at one of the country’s leading research universities has defined success as producing more startups. The solution to the problem of innovations not reaching patients is, per the working group, more and better startups.

This would be fine, or at least less problematic, if most faculty innovations were good startup ideas. Many are not. Starting a company requires a particular kind of founder commitment. You are, typically, leaving or substantially reducing an academic career. And it requires a particular kind of commercial trajectory: A good product that could profitably serve a modest market is not, in most cases, a good startup idea. It doesn’t have the growth dynamics that justify bringing on investors, hiring aggressively, and building toward an exit. Pushing it through the startup model doesn’t make it a better startup. It just adds a layer of expensive institutional overhead to what might have been a straightforwardly buildable product.

The Norway Problem

For a long time, watching innovations stall at exactly these points (eg, promising product, no path, wrong shape for the only available capital) I assumed the explanation was local. Bad luck. Weak management. An inventor who didn’t work hard enough. Then I came across a natural experiment that suggested something more structural was going on.

In 2003, Norway changed its IP laws to transfer ownership of university research from individual professors to their institutions, basically adopting the American approach. The theory was that centralizing ownership would professionalize commercialization and increase spinout activity. Give institutions control over the IP, build out the infrastructure, produce more startups.

What actually happened: university startup formation fell fifty percent. Among science and engineering researchers, startup formation fell sixty-three percent on a per-worker basis. Patenting rates fell by a similar margin, and patent quality declined alongside.

The system designed to encourage commercialization suppressed the commercialization instinct instead. Not because Norwegian professors stopped having ideas, but because the institutional process replaced a decentralized, faculty-driven impulse with a centralized administrative one that most faculty found alienating and most innovations couldn’t survive. And the institutional machinery that replaced it was built, as ours is, around a single output: new companies. It didn’t just produce fewer startups. It substituted an organizational reflex for the real question: whether a startup is the right vehicle for a given innovation in the first place.

You can read this as a specifically Norwegian story about institutional culture. Or you can read it as a canary: a visible version of a dynamic that operates more slowly and less visibly in the American model, where it’s a little harder to observe because the change happened gradually rather than all at once.

I tend toward the second.

What Gets Left Behind

The University of Wisconsin receives roughly three hundred fifty to four hundred invention disclosures per year. About one per day, as Greg Keenan, a senior leader of WARF, describes it. They patent roughly half. A small fraction become companies. The rest find another path, or none at all.

The true cost of this isn’t visible in any annual report. It lives in the distance between what could have reached patients and what actually has. Universities measure patents filed, startups formed, venture capital raised. They don’t measure how many innovations actually reached patients, how many profitable products never got built because the market was deemed too small, or how many faculty inventors gave up after the tech transfer-to-startup process proved too slow or too discouraging to navigate. The metric and the thing you actually care about, clinical impact, have decoupled almost entirely.

Ben Reinhardt, who runs Speculative Technologies and thinks carefully about where innovation gets stuck, calls this the missing middle: the space between what philanthropy will fund and what venture capital finds interesting. Most promising faculty innovations fall into the gap between them. Too commercial for philanthropy, which wants pure research with no financial entanglement. Not commercial enough for venture capital, which needs billion-dollar exits to work. Too early for strategic acquirers. Too dependent on makeshift licensing channels not built for this category of innovation.

It’s not a theoretical construct. It’s an actually crowded space of working innovations with real clinical value and no institutional home or way forward. The device that helps tens of thousands of patients, profitably, at modest scale. The diagnostic test that works and has customers and needs someone to build the business-shaped wrapper around it, just not a venture-backed company. The software that hospitals need and will pay for, just not at the growth rates that justify a Series A.

These aren’t failed ideas. They’re working ones that we’ve forgotten, or never learned, how to handle. Once the Bayh-Dole Act established the university-to-startup pipeline in 1980, we lost the habit of asking what an innovation actually needs, rather than what the system is designed to produce.

In the next three posts in this series, I take up why the system defaults to companies when it should sometimes just make products, why drug development figured out a model for this that healthtech hasn't adopted, and what it might actually take to create something new. Nobody has built that machinery yet. That is what this series is about.

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Citations

Greg Keenan quotes and WARF disclosure figures: John Allen, “WARF Seeks the UW’s Next Big Thing,” On Wisconsin, Fall 2025; and Brittney Kenaston, “Taking Ideas to Market,” In Business Madison, August 2025.

Mike Partsch quote: John Allen, “WARF Seeks the UW’s Next Big Thing,” On Wisconsin, Fall 2025.

WARF Ventures and Accelerator timeline: Brittney Kenaston, “Taking Ideas to Market,” In Business Madison, August 2025.

UW rankings and report: Empowering the Wisconsin Idea: The Future of Entrepreneurship at the University of Wisconsin–Madison, UW–Madison Working Group Report, 2024.

Lewis Sheats appointment: Rodee Schneider, “Lewis Sheats named inaugural leader of UW’s Wisconsin Entrepreneurship Hub,” UW–Madison News, January 20, 2026.

Norwegian IP reform data: Hvide, Hans K., and Benjamin F. Jones. “University Innovation and the Professor’s Privilege.” American Economic Review 108, no. 7 (2018): 1860–1898.