Most University Innovations Aren’t Meant to Be Startups

“The major tech breakthroughs aren’t coming from universities—at least, they haven’t in a long time.”

I heard this claim at a workshop on the future of the STEM workforce from a panelist, and it gave me pause. It was offered without evidence, but it made me consider: what do we think of as a breakthrough, and where are they coming from? Were the breakthroughs previously coming from Universities? Or is it that expectations have changed?

If the benchmark is a venture-backed startup that scales and exits, then university technologies rarely meet that standard. It’s the exception, not the rule, for academic research to spin out in a way that achieves a lucrative IPO or acquisition. But framing it this way says less about the value of university innovation than it does about the limits of how we define “success” and “impact”. Universities are judged - in the context of local innovation economies at least - as though their job is to produce startups. But their core mission is actually to produce knowledge and educate people. That mismatch distorts how we define success. 

What is success, and how is it measured in this context? 

In the early 2010s, there was a push among leading institutions to measure the success and impact of university innovation ecosystems, in part by the number of startups they produced. And when startups raise significant capital and then exit, they are highly lauded and cited as a major contributor to the institution's prestige. The majority of university inventions weren’t built for that path, but they are quietly advancing their respective fields step by step. Universities are primed to educate and advance knowledge, but they are also seemingly expected to serve as economic engines. Consider “Goodhart’s Law”: when the metric (in this case, the number of startups) becomes the target, it ceases to be a good metric (i.e., a measure of success) because it incentivizes manipulating the system to hit that target. 

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Most University Innovations Are Building Blocks, Not Products

In my work consulting on faculty-led life sciences technologies, most innovations fall into four categories: 

• Research tools
• Platform or component technologies
• Early therapeutic or diagnostic candidates
• Fully developed products. 

The first three are not stand-alone, ready-to-market products. Research tools may eventually be sold through vendors or incorporated into R&D kits. Platform or component technologies usually need an industry partner to become part of a larger product. Therapeutic and diagnostic candidates still require extensive development before they can reach patients. Fully developed products, by contrast, are comparatively rare and most closely fit the venture-backed startup model. When these differences are not recognized, technologies can be pushed down paths that do not fit what they actually are, slowing progress or limiting their impact.

In manufacturing, for example, methods developed by leading university faculty to identify and correct defects in complex assembly processes have been embedded into automotive production systems, thereby improving quality at scale without ever becoming standalone products. In the life sciences, primary research by physicians, who make observations in both the clinic and the lab, has led to the development of meaningful biomarkers that are highly valuable for advancing cancer diagnosis and treatment. The biomarker wasn’t a single product or company. Still, the result of a body of work, including methods, validation, and clinical insight, that became foundational to how disease is monitored and studied. In both cases, the impact came through integration into a larger system, not through the creation of a venture-backed entity.

Consider CRISPR, which is the gene-editing breakthrough from academic labs that has reshaped how scientists study and potentially treat disease. Its impact is widespread as a foundational tool, despite not being a single company. By contrast, companies like Google rapidly translated into a widely used product but still required substantial scaling and business model development to achieve their eventual commercial dominance. Crucially, their impact and value are captured within a single firm, rather than diffusing broadly across the scientific ecosystem as a shared research tool. And even financially, for university inventions going through tech transfer, positive outcomes are rare. In one private analysis that I’m personally aware of, over a decade at a major university, fewer than 1% of disclosures generated more than $1 million in licensing revenue, about 2% exceeded $100,000, and only around 5% produced any revenue at all.

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Rethinking Impact: Supporting University Pathways Beyond Venture Capital

Rethinking what counts as impact doesn’t require abandoning existing models for supporting university output. I’m proposing expanding our perspective of “impact”, communicating it to primary researchers, and then finding innovative ways to measure the successes. If most university technologies are not product-complete, then their pathways to success should be identified and supported accordingly. That means placing greater emphasis on and creating opportunities for early partnership strategies, treating licensing and integration as primary outcomes, and giving scientists clear signals about how different types of innovations are likely to move forward. 

The point is not that university innovation is failing. The point is that we are often evaluating it with the wrong scoreboard. The goal isn’t to produce fewer startups. It’s to ensure universities match their technologies with the pathways that give them the best chance of making an impact. Universities don’t just generate flashy “breakthroughs” in the form of successful startups. They generate the building blocks that enable entire industries. By recognizing that distinction, we can better support their development.

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Ruby Miller is a Biotechnology Regulatory Fellow with the National Academies of Sciences, Engineering and Medicine. She holds a PhD in Chemistry, has worked on the commercialization of cutting-edge biomedical technologies and has a keen interest in how these technologies are funded and come to market.