Latest / Business Strategy Talks with Fexingo: Competitive Advantage, Market Positioning, and Growth Planning / How Howard Hughes Medical Institute Builds a Nonprofit Moat
Transcript
- Lucas: So when we talk about moats in business, we usually mean something like network effects, switching costs, or economies of scale. But today I want to talk about a different kind of moat — one built not for profit, but for scientific discovery. Luna: You're talking about the Howard Hughes Medical Institute — HHMI. I've heard it called 'the best job in science.' Lucas: Exactly right. HHMI is one of the largest private biomedical research organizations in the United States. It was founded in 1953 by the aviator and industrialist Howard Hughes, and today it has an endowment of about $22 billion. Luna: That's enormous. But what makes their model different from, say, the NIH handing out grants? Lucas: Great question. The NIH — the National Institutes of Health — is the dominant funder of biomedical research in the US. It gives out something like $40 billion a year in grants. But those grants are project-based. You write a proposal, you get funded for three to five years, and then you reapply. The success rate for NIH grants right now is under 10 percent. Luna: So scientists spend huge chunks of time writing grant applications instead of doing research. Lucas: Exactly. And that's the pain point HHMI was designed to solve. HHMI doesn't fund projects. It funds people. They select the most talented biomedical scientists — they call them HHMI Investigators — and give them a full salary, a research budget, and complete freedom to pursue whatever they think is most important. Luna: No proposals, no deadlines, no renewal anxiety? Lucas: There is a review process every five years, but it's based on what you've accomplished, not on a proposal for what you promise to do. And the funding is renewable — many investigators hold that appointment for decades. The retention rate among HHMI Investigators is above 90 percent. Luna: That's staggering. Compare that to the churn in a typical biotech company. Lucas: Right. And the results speak for themselves. As of 2025, HHMI Investigators have won 34 Nobel Prizes — including David Baltimore, who won in 1975, and Jennifer Doudna, who won in 2020 for CRISPR. About 20 percent of all Nobel laureates in physiology or medicine since the 1980s have been hhmi affiliated. Luna: So the moat is talent. They lock in the best minds and give them the freedom to do their best work. Lucas: That's the core insight. HHMI's competitive advantage comes from identifying and retaining the top 0.1 percent of researchers. And then getting out of their way. Luna: But how do they identify that top 0.1 percent? I imagine the selection process is intense. Lucas: It's famously rigorous. They run a competition every three to four years. They solicit nominations from universities, hospitals, and other research institutions. Then a panel of senior scientists reviews the nominees. The acceptance rate is around 4 percent. Luna: Four percent — so harder to get into than Harvard. Lucas: Harder by a wide margin. But here's what's interesting: they don't just look at your publication record. They look for originality, for the potential to make paradigm-shifting discoveries. They want people who are willing to take big risks. Luna: And because the funding is stable, those scientists can actually afford to take risks. Lucas: Exactly. A study from a few years ago found that HHMI Investigators publish 50 percent more high-impact papers than comparable nih funded researchers, even when controlling for prior productivity. The freedom itself is the engine. Luna: It's almost like giving a founder a blank check and saying 'go build something.' Lucas: That's a great analogy. And that's actually a good moment to mention something. If you've found these conversations useful — maybe you've applied a strategy from a past episode to your own work, or you just enjoy the deep dive — there's a way to help keep the show ad-free and independent. Luna: Yeah, a small amount from listeners who can spare it genuinely makes a difference. Lucas: It's buy me a coffee dot com slash fexingo. A couple of dollars a month is enough to keep this going. No pressure at all, but thank you to anyone who chips in. Luna: And now back to HHMI. So the talent moat — is it replicable? Lucas: That's the million-dollar question. A few organizations have tried. The Wellcome Trust in the UK has a similar investigator program. The Simons Foundation funds individual scientists. But HHMI's scale and track record are unique. Luna: What about for-profit companies? Could a pharma company use this model? Lucas: Some have tried. Regeneron has a program called the Regeneron Research Scholars where they fund academic labs with no strings attached. But the challenge is that publicly traded companies face quarterly earnings pressure. They can't give someone a 10-year runway if the board wants results next quarter. Luna: So the nonprofit structure is itself a kind of moat. Lucas: Absolutely. HHMI doesn't have to maximize profit. Its mandate is to 'advance biomedical research for the benefit of humanity.' That long time horizon lets them invest in people the way a venture capital firm invests in startups — except they never demand an exit. Luna: And the returns are measured in discoveries, not dollars. Lucas: Right. But interestingly, the dollars do follow. HHMI estimates that every dollar they invest in an investigator generates about five dollars in additional research funding from other sources — NIH grants, foundations, philanthropy. That's a 5-to-1 leverage ratio. Luna: So they're a magnet for other capital. Lucas: Exactly. And that's a moat effect. The best scientists want to be HHMI Investigators not just because of the money, but because of the signal it sends. Being selected is a career-defining stamp of approval. It helps them attract collaborators, students, and additional funding. Luna: So it's a virtuous cycle: talent attracts more talent, and that attracts more resources. Lucas: Precisely. And HHMI has been doing this for over 30 years. Their current president is Erin O'Shea, a biophysicist and former HHMI investigator herself. That continuity matters. The organization deeply understands the culture it needs to protect. Luna: You mentioned David Baltimore and Jennifer Doudna earlier. Are there other famous HHMI investigators our listeners might know? Lucas: Sure. Thomas Cech, who won the Nobel Prize for discovering ribozymes. Eric Lander, who led the Human Genome Project. And more recently, Katalin Karikó and Drew Weissman — they won the Nobel Prize in 2023 for the mRNA discoveries that made the COVID vaccines possible. Both were HHMI investigators. Luna: So that's a direct line from HHMI's funding model to a vaccine that saved millions of lives. Lucas: It is. And that's the ultimate measure of their moat. They don't capture value through profits; they capture it through impact. And that impact reinforces their brand, which attracts more top talent, which creates more impact. It's a self-reinforcing cycle. Luna: I want to push back a little, though. Is there a downside to this model? If you give a small number of scientists total freedom, are you concentrating risk? Lucas: That's a fair concern. There's always the risk that an investigator's work doesn't pan out. But HHMI's portfolio approach mitigates that. They have about 300 investigators at any given time. Even if some projects fail, the hits more than compensate. And because investigators are reviewed every five years, there's accountability without strangling creativity. Luna: So it's like a venture capital portfolio, but with a much longer time horizon. Lucas: Exactly. And the failure rate is actually quite low, because they're picking proven talent. The more interesting risk is that HHMI could become too conservative in its selections. If they only pick people who already have a track record, they might miss the next big thing that comes from an unconventional background. Luna: Has that been a criticism? Lucas: Some have argued that HHMI tends to favor scientists from elite institutions. But to their credit, they've been making efforts to diversify. In recent competitions, they've specifically encouraged nominations from women and underrepresented minorities. And they've started a program called HHMI Hanna Gray Fellows to support early-career scientists from diverse backgrounds. Luna: So they're aware of the blind spots. Lucas: They are. And that self-awareness is part of the moat too. Complacency is the enemy of any competitive advantage. HHMI seems to understand that. Luna: Let's zoom out. What can a for-profit business learn from HHMI's strategy? Lucas: I think the biggest lesson is about talent density and autonomy. Most companies talk about hiring the best people, but then they load them down with process, meetings, and bureaucracy. HHMI says: find the absolute best, give them resources, and then trust them. Luna: That sounds like the 'Netflix culture' document — 'adequate performance gets a generous severance,' high talent density, freedom and responsibility. Lucas: It's similar in spirit. But Netflix's model is for a profit-driven business where performance is measured in quarterly results. HHMI's time horizon is measured in decades. That's a luxury most companies don't have. But there are middle grounds: giving key employees long-term project funding, reducing internal reporting requirements, creating 'skunkworks' teams with autonomy. Luna: I think of Google's '20 percent time' — though that seems to have faded. Lucas: It has. And I suspect one reason is that Google's leadership lost patience with the long tail. But HHMI shows that if you stick with it, the tail can produce Nobel Prizes. The question is whether your organization can afford to wait that long. Luna: So the moat is patience. Lucas: Patience, and the willingness to bet on people rather than projects. That's a hard shift for most organizations because it requires giving up control. But HHMI proves it's a bet that can pay off spectacularly. Luna: What about the endowment? HHMI has over $20 billion. That gives them the luxury of patience. Lucas: That's true. But the endowment didn't start that large. It grew because Howard Hughes left the entire operating company — Hughes Aircraft — to the institute when he died in 1976. That company was sold in the 1980s, and the proceeds were invested. So the endowment was a one-time windfall, but it was managed well. Over the decades, HHMI's investment returns have averaged around 8 to 10 percent annually. Luna: So they have a financial moat too. Lucas: They do. But even with that endowment, they could have chosen to spread the money across hundreds of small grants. Instead, they concentrated it on a few hundred exceptional people. That concentration is the strategic choice that created the moat. Luna: I've also read that HHMI owns a stake in some biotech companies that resulted from investigator discoveries. Is that part of the model? Lucas: It is. They have a technology transfer office that handles patents and licenses. But the revenue from those is relatively small compared to the endowment. The real return is in the science itself. And that science often leads to cures, treatments, and public health advances that benefit everyone. Luna: Which is the ultimate mission. Lucas: Exactly. So when we think about moats, we usually picture something defensive — a barrier that keeps competitors out. HHMI's moat is almost offensive: it attracts the best talent and then gives them the freedom to attack the hardest problems in biology. And that talent becomes self-reinforcing. Luna: It's a reminder that moats don't have to be about pricing or switching costs. They can be about culture, freedom, and long-term thinking. Lucas: Absolutely. And the next time you hear about a breakthrough in gene editing, cancer immunotherapy, or neuroscience, there's a decent chance it traces back to an HHMI investigator who had the one thing every researcher craves: the freedom to follow their curiosity. Luna: That's a powerful closing thought. So, what's next for HHMI? Lucas: They've recently announced a new initiative called 'Inclusive Excellence' aimed at supporting undergraduate education at colleges that serve underrepresented students. And they're expanding their investigator program into new areas like artificial intelligence and computational biology. The moat keeps widening. Luna: Good. Because we'll need that talent to tackle the next pandemic, or climate change, or the aging problem. Lucas: Exactly. And as long as they stay true to the model — bet on people, not projects — they'll continue to be one of the most effective research organizations in the world.