My life-saving miracle took twenty years of hard work


Ipilimumab (now branded as Yervoy), which is based on the research of Noble Laureate James Allison, is the first-in-class immunotherapeutic for blockade of CTLA-4 and significantly benefits overall survival of patients with metastatic melanoma.


When I was a sophomore in college, I was diagnosed with melanoma, an aggressive form of cancer. Within 24 hours, I was on a plane home, and 24 hours after that I had surgery to remove the tumor.

That initial whirlwind of activity stood in stark contrast to what happened next: nothing. As my doctors explained, melanoma doesn't respond to chemotherapy, radiation, or any other therapy they had to offer. After surgery, my only option was to wait and hope the cancer didn't come back.

But it did. Three months later I found a lump in my neck. The disease had returned and progressed to stage IIIc. At age 20, survival statistics gave me a 40% chance of making it past my 25th birthday.

However, those statistics couldn't account for a groundbreaking development during the brief window before my cancer returned. Just weeks before I found the new tumor in my neck, a team of researchers published a paper revealing that a drug called ipilimumab improved survival in patients with advanced melanoma. For the first time, oncologists could offer melanoma patients a pharmaceutical therapy.

Although ipilimumab (which is now branded as Yervoy) wasn't approved until the next year, I was able to access the drug through a clinical trial - a development that very well may have saved my life. Had I not received the drug, there's a one-in-five chance that I wouldn't be here writing these words today, according to the study's results.

The movie-like appearance of ipilimumab in my life was the culmination of a multi-decade process that started when I was a toddler. The drug's development is rooted in university research James Allison performed in the early 1990s. (Allison shared The Nobel Prize for Physiology and Medicine 2018 for that work.)

Most accounts of ipilimumab's development fast forward to the successful large-scale trial that led to its FDA approval, overlooking the decade and a half of heavy lifting that is typically required to develop a life-saving drug. Researchers like Allison need to find a corporate home for their breakthroughs (or build one themselves.) They also need to raise capital and negotiate licenses before they can even begin to solve manufacturing challenges and run clinical trials.

These are formidable challenges. Allison told NPR that he was "depressed" by his initial failure to find a company willing to commercialize his research. Fortunately, he worked at Berkeley, in the middle of a major technology startup hub, where he was surrounded by the resources required to overcome those challenges.

Because I survived cancer, I was able to finish my degree in math at Yale, and I went on to work at the Boston Consulting Group and then Google. I'm married now, and I'm able to support my wife as she trains to be an oncologist. (This frequently takes the form of sending her pictures of our dog and cats while she's working in the hospital.)

Unlike my wife, I don't expect to work directly with cancer patients. But as the lead data scientist for Research Bridge Partners, I'm doing my part to identify and commercialize breakthrough treatments. Our non-profit has built a one-of-a-kind data model that lets us search for future James Allisons - only those who don't happen to be next door to Silicon Valley. We use data to find the researchers whose science could save lives, but who might not get the chance to do so because they work in the wrong part of the country.

We use a lot of math and a lot of domain expertise to find these men and women. Then we do our best to ensure that the science behind the next ipilimumab gets bridged to the resources and people who can turn it into Yervoy-calibre impact in the lives of patients - like me - throughout the world.

Demo days and venture labs won’t turn your school into MIT.  That’s OK.  Here’s what you can do that will work.

A 2018 map of MIT’s Kendall Square depicting the concentration of commercial R&D/office buildings (pink) surrounding MIT university buildings (blue).
A 2018 map of MIT’s Kendall Square depicting the concentration of commercial R&D/office buildings (pink) surrounding MIT university buildings (blue).


As a university leader or a department head, you manage and serve creative PIs making world-leading discoveries. The coastal startup clusters have the capabilities - risk capital and (more importantly) commercialization talent - to drive those innovations to market. You need to bridge your most innovative PIs to the people and networks and capital sources that are as good at business as they are at science

Why you can't solve the problem from where you sit

The issue is that the tools that you have in your toolkit, as a heartland university or departmental leader, do not give you enough leverage on the problem. The key is to put your university in position to exploit the massive investment that the American economy makes in startups and entrepreneurship, nationally.

The university commercialization toolkit is limited and not very effective. Demo days (taking opportunities to Silicon Valley and inviting investors to view them) have started to look generic and now attract mostly low ranking investment professionals. Entrepreneur-in-residence programs (hiring business people to help filter opportunities on your campus) can produce a great result if this particular EIR happens to be awesome and happens to hit an innovation where she is a market expert … but the odds of that are pretty low.

Stanford and Harvard and the other schools that are most commonly held up as being "good at" commercialization are not good at commercialization because they do better demo days or have better EIR programs. They are good at commercialization because they are located in the densest concentrations of entrepreneurial capital and translational talent on the planet. Stanford's demo day is every day of every week. Its EIR program is Silicon Valley.

The risk capital available to turn innovation into a successful startup shows the scale of the challenge:

  • For every $1 of research performed by Bay Area universities, Silicon Valley has $15 of risk capital available for investment. For the Boston universities - think about how much university research gets done in Boston - it's $5 of VC dry powder for every dollar of research.
  • In contrast, for each $1 of research performed at The University of Texas, located in a mid-continent tech mecca, there is only about $0.70 of VC dry powder. In The University of Michigan's catchment area, $0.20. In the Minneapolis schools', $0.09.

You could have Harvard's endowment, and you still wouldn't be able to fill those gaps.

But capital is mobile, right? Theoretically, Bay Area money can find opportunities anywhere in the country. And sometimes it does ... but not very often, because venture money is tied to people, and those people value their time highly, and burning two days in transit to and from your Big 10 or Big 12 or SEC campus is an expensive proposition for them, especially given the opportunities that they have at home.

OK, so can you hire translational professionals to do that work locally for your university? You absolutely should invest in great people in your TLO and commercialization and entrepreneurial support programs. But this is table stakes, not a bet.

The market rewards the best people with these skills really, really well. As in off-the-university-pay-scale and with-comp-structured-in-a-way-that-would-be-impossible-at-a-public-school well. So you are looking for people with rare skills who are willing to work below market. That's a tough ask.

Also, it's a question of scale. Think of the diversity of research at your university. Is one person or even one team going to be omnicompetent against that entire spectrum of technologies and market applications? Partners' Healthcare Innovations, the translational group associated with Harvard's affiliated hospitals, employs about 80 people in their innovation group, and that doesn't count their TLO or Harvard's other commercialization programs. Are you going to make that kind of investment?

Even if you do, it won't get you to parity with Partners'. It's geography again. Partners' is in Boston, with its at-scale networks of well-compensated people who can turn health innovation into billion-dollar companies. You cannot build that ecosystem from whole cloth.

As a result, although we have met fantastic and dedicated people in university commercialization programs, they alone will not bridge your commercialization gap. Some of us used to be university-employed translational professionals. We had some good wins. But we did not, in any structural sense, close the gap.

Why doesn't your university "do commercialization as well as MIT?" We have heard this question asked by more than one alumnus and state-level policy maker. A big part of the reason is that you're not in Boston with open access to its industry-specific talent and capital pools. And there is nothing you can do about that.

The solution is to bridge the right PIs at your university to the right commercialization resources nationally

So you can't do it all yourself. Here is what we think you can, and should, do:

First, and above everything else, recruit and retain and resource great faculty.

The other thing about the commercialization success of the Bay Area and Boston schools, is that their PIs are really, really good at creating new knowledge. Stanford alone has 156 members of the National Academy of Sciences on its faculty. Not surprisingly, those PIs attract the most outstanding and ambitious students.

When partnered with strong translational professionals and capital, the innovation from those labs nucleates companies. The students from those labs graduate to help drive innovation into commercial products and services that create economic prosperity and make people's lives better.

If your main initiatives focus on faculty quality, you won't go wrong. Only a few percent of your faculty will end up as scientific co-founders of scaling companies, but that's all you need.

Second, remove barriers to commercialization

High-impact, scaling spinouts based on deep science from research labs: that's the objective.
University leadership can make this objective easier to obtain by breaking down barriers to commercialization. Two areas where you may have opportunities, are these:

  • Clarify or rectify confusing or non-market policies regarding intellectual property and/or conflicts. Common culprits include: Unclear or "non-market" IP ownership policies. Undue restrictions on faculty/student commercial collaboration (this is hard to get right.) Consulting policies that favor income-generating work (e.g., expert witness testimony) over prosperity-creating work (e.g., founding a startup).
  • Align TLO goals and incentives with startup creation and success. Here, be on the lookout for: TLOs measured on revenue, and/or TLOs resourced based on "eat what you kill." (Creates incentives for short-term licenses and against entrepreneurial value creation.) TLOs asked to do significant "marketing" of university IP portfolio. (Very few people or companies want to buy IP; they want to invest in opportunities.) TLOs whose posture has become over-weighted towards compliance vs. faculty service.

We are not advocating using commercial metrics in lieu of academic metrics for hiring or promotion decisions. First, the schools that are "good at" commercialization don't do this, so why should you? Second, it's not clear that it adds much. In our experience, if an assistant professor has created a field-defining innovation that she instantiates in a patent, this will be brought up as part of her tenure review regardless of whether "patents" are a formal review category or not. Third, how good is your P&T committee at evaluating patent quality?

Third, create an atmosphere that celebrates and re-enforces entrepreneurial success among your faculty

Entrepreneurial activity at a university is contagious. To encourage this kind of virtuous contagion, here are some tactics that you should consider:

  • Play favorites by being very clear-eyed about talent. Our analysis indicates that probably 1-2% of your faculty can/should be scientific co-founders of startup companies. You know who some of them are already, and we can help you find others. Don't be shy about providing low-cost, high-value benefits to these people - summer relief, development support, attention from you personally and from the university media.
  • Use your bully pulpit to aggressively celebrate success … and even good failures. Talk about the way that commercialization and entrepreneurship support the research, education, and service missions of the university. Reinforce these messages with emails and lunch invitations.
  • Encourage industry engagement. Ask your SRA partners how you can better facilitate interaction with faculty. (At one school, the answer turned out to be, "make it easier for me to park on campus!")

Many schools now have translational grant programs - catalyst funds and startup grants and the like - that provide $25,000 - $250,000 of non-dilutive grant capital to pre-commercial projects, as proof-of-concept or prototype funding. These seem to be expected now, and so you probably have to do it. On the margin, we would guess that they are positive investments. However, if you have $1,000,000 per year for this purpose, we would bet that you would get more payoff from three no-strings-attached awards to your three most commercially minded, high productivity PIs, than 20 awards intended to specifically drive towards commercialization. A tiny fraction of your faculty will generate almost all of the commercial value created at your university. Double down on them.

Fourth - and this is where RPB comes in - get leverage on scale

RBP is a 501(c)(3) not-for-profit that works with you to identify the faculty - usually about 1% of a university's PIs - who "look like" prospective serial academic entrepreneurs based on our proprietary model. Sometimes our model gives us a bogus target, and sometimes we miss somebody great, so we like to run our results past you. Usually, we end up with targets that have about 50% overlap with the PIs that deans and chairs would pick on their own, but much less overlap with the PIs whom the TLO would pick. The reason for this is that most of the innovation in most of the labs on most campuses is dark (undisclosed) and not visible to the TLO.

We can't replicate the access to startup networks, talent, and capital that those faculty would have if they worked in the Bay Area, but we can approximate parts of it:

  • Provide mentorship. Not from people who just happen to be in our network or who just happen to be in your local community, but from the right people with the right experience to help triage opportunities and sculpt research programs with an eye to application. Since the density of academic co-founders tends to be lower at heartland universities than at universities in the startup clusters, we also create opportunities for PIs to interact with each other directly on these issues.
  • Take off the IP blinders. Universities own the IP, so they tend to focus on IP value. This can lead to commercialization strategies biased towards capital efficient IP flips. Sometimes that is the right way to go … but other times it leaves a lot of value and a lot of impact on the table. We help stakeholders look at opportunities through a value creation and value capture lens: how could this spin-out maximize value, and what corporate organization would need to be in place to capture that value?
  • Launch startups to succeed. Heartland startups receive about 33% of the capital, on about 60% of the valuation, of Boston startups. (These data are for bio, but the trend holds across markets.) This is because the heartland science might be as good as the Boston science, but the heartland deal usually isn't as good as the Boston deal. The reason for this is all of the work that gets done in Boston prepping the deal, before it goes out for funding. We work with PIs and other university stakeholders to do a lot of that prep and build deals that are as good as the science behind them. We want to help your startups get 100% of the valuation, regardless of your location.

Our goal is to get your best startups ready to compete successfully for the national-quality talent and capital that they will need to be successful. Yes, we do write checks through our program-supporting venture fund, and we offer other development in-kind. The way to think about our work, though, is that we bridge your best PIs to the people and networks and capital sources that are as good at business as they are at science.

Paul Romer’s Nobel Prize – Why we do what we do

Paul Romer was awarded the 2018 Nobel Memorial Prize in Economics for demonstrating "how knowledge can function as a driver of long-term economic growth."


Last Monday, 8 October 2018, Paul Romer won the Nobel Prize in Economics for his contributions to our understanding of economic growth. The theory he developed helps explain why we do what we do.

Economic growth is really, really important. From the beginning of human history up until the Industrial Revolution, there pretty much wasn't any. You could take the average person from the Year 1 and put her in 1740, and she would find it in many ways familiar … familiarly grim and hard.

But if you took a person from 1740 and dropped her here, today, it would blow her mind.

The reason is economic growth. Growth is pure oxygen. It's what has given us longer and healthier lives and enhanced opportunities for the flourishing of the human soul without hunger or terror or bondage.

In the 1950s and 1960s, economists like Robert Solow (Nobel Prize, 1987) worked out the theory of economic growth: growth is a function of labor, capital, and ideas. Labor is people, you and me. Capital is stuff like the machine that I am typing this on, tools that make us more productive than we would be on our own. Ideas are ways to do things differently - new ways to organize people, new machines, etc.. Solow and others took these simple insights and rigorously and elegantly modeled them, laying a theoretical foundation for the analysis of economic growth.

This was incredibly powerful. One of the insights of these theories is that growth stalls when we run out of people and out of productive uses of capital. The growth curve inevitably flattens as an economy matures. The way to keep the growth rate up - the only way - is for new innovation to keep being introduced into the economy, increasing productivity.

But although growth theory highlighted the importance of innovation, it did not have much to say about it. Innovation, knowledge, ideas … for the economists of the 1950s and 1960s, they were just sort of out there, floating around, for anyone to use. So even though ideas are the drivers of productivity, in a weird way they were treated as outside of the economic system by the architects of growth theory, rather than as part of it.

Intuitively, that's not right. Inventions don't just happen. Inventions are invented by inventors. We are the authors of ideas, not just their beneficiaries.

The legal and cultural context also matters. Ideas are often owned or private. Patents and trade secrets and know-how - those ideas are not just "out there" and available for anyone to use. Other ideas are not proprietary, but they are built into systems that are really hard to copy, like social customs or legal regimes. Growth theory didn't have much to say about this.

This was a problem for growth theory. Romer solved it.

Romer brought innovation into the longstanding models for economic growth. He described how ideas are both products of the economic system and influencers of that system. Patent rights, for example, increase the incentives for certain kinds of innovation.

Knowledge is cumulative. We can, and do, make more. And we can structure society so that we get more and more knowledge, more and more innovation, more and more growth. We can do things and set up systems and make investments that are likely to encourage people to invent things or systems that make our lives better … and that themselves lead to more innovation.

To me, this is one of the most optimistic findings in all of social science.

It means that our future doesn't have to be a dystopia where all the growth has drained out of our society, with our grandchildren's lives governed by zero-sum competition for a fixed pool of resources. Our future doesn't have to be the human version of the heat death of the universe, whose energy will gradually dissipate until … nothing.

The future can be better. People behave differently when the pie is growing than when it is static or shrinking. In this way, growth enables generosity. We all have to fight parts of our natures in order to be virtuous, otherwise virtue would not be praiseworthy. Growth helps to align virtue a little bit more with self-interest.

Economic growth also builds hope. Hope for the alleviation of poverty. Hope for cures for diseases. Hope for solutions to environmental problems. Hope for more people to be able to freely follow their spiritual course and calling.

Before Romer, economics viewed growth as kind of like a lottery or a cargo cult where society waits passively for a new box of ideas to wash up on shore to fuel the growth machine. What Romer said was, "We can build those ideas ourselves; we can fuel our own growth machine; it's hard work, but with deliberate effort, we can do it." A virtuous cycle of growth driving the creation of new ideas driving more growth … that, not heat death, can be our future.

We heard you, Paul. That's why we do what we do!

The world has never seen a system that produces innovation at the rate of America's research universities. Romer writes about their uniqueness: the combination of the Morrill Act in the 19th century (the Morrill Act created America's distinctive land grant university network) and the post-World War II federal research grant system (which institutionalized federal support for mission-oriented basic research) were two of the great meta-innovations of human history. The land grant schools and federal research funding are innovations that create more innovation.

But that alone doesn't generate growth. We also need tools to drive that university innovation into the economy, or else the innovation will lie fallow. The nation's startup clusters, especially Silicon Valley and Boston, do that amazingly well. These clusters metabolize about 4 out of every 5 dollars of early-stage funding. They are another important, American-made, meta-innovation: a new way to scale ideas rapidly through an economy.

The challenge is that most of America's research doesn't happen in those clusters. 74% of American university research, by dollars invested, happens in states other than California, Massachusetts, and New York. As a result, the rate of startup creation out of most heartland universities is a lot lower than at the universities in the states with technology hubs, and the startups that do get formed are often significantly undercapitalized compared to startups in the hubs, which probably contributes to lower success rates and lower impact of heartland science on the national economy.

This seems like a waste. It's like a whole cargo container of ideas drifting past our island.

So we built Research Bridge Partners as a bridge out to that big container of ideas, to get them into our economy for the benefit of all of us.

Hat tips and further reading: Paul Romer, Tyler Cowen, Alex Tabarrok, Joshua Gans, Ross DeVol