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Is There a Translational Research Gap?

While I was busy explaining why the industrial research labs won’t return, an exciting thread unraveled on Twitter arguing about how to revive them anyway.

To kick things off, Activate CEO Ilan Gur argues that tech startups are the new Bell Labs, citing Moderna as proof. Then Sarah Constantin jumps in to explain that Moderna was just commercializing research from a university lab, and startups can’t do fundamental research because VCs won’t fund it.

Finally, Adam Marblestone chimes in to plug Focused Research Organizations as the missing gap between fundamental research in universities and applied science in startups.

This is all great, and highlights what I love about Twitter: smart people with diverse perspectives coming together in an ad-hoc way to discuss an important question, while making it accessible to lay audiences. [1]

I’m just not convinced it’s actually right.

Marblestone writes:

Academia’s big, so existence of fundamental research isn’t what we have to solve for (though can push more). Startups deploy well, so also not that, modulo VC risk/return params (1 of 3 proposals there). A gap is between those (another of 3 proposals highlighted).

This is a compelling narrative. Academic handles fundamental research, startups work on commercialization and deployment. What we’re missing is translational research to nurture pre-commercial research and bring it to fruition.

In fact, it’s so compelling that everyone else is already working on it. Off the top of my head, here are some mission statements to consider [4]:

  • Cyclotron Road: “Our mission is to empower science innovators to advance their ideas from concept to viable first product, positioning them for broad societal impact in the long term.”
  • ARPA-E: “advances high-potential, high-impact energy technologies that are too early for private-sector investment.”
  • Sci-Founder: “help early career scientists start companies of their own.”

Not enough? Here’s the diagram from Actuate’s home page:

Okay, so maybe you’re convinced that the gap has been bridged, but it’s only a recent phenomenon, and only as a result of these brave pioneers.

Except here’s Breakout Labs in 2011: “Venture capital firms want research that can be quickly brought to market, and federal funding offers little room for risky, unproven ideas. We are jumping into this funding gap to energize innovative research.”

What’s going on here? Is translational research a great idea who’s time has come? An overcrowded space? A buzzword? A buzz-narrative?

Commenting on a draft of this post, Sarah writes: “I think a handful of funds existing is good validation of the idea rather than evidence it’s already overdone. The gap is probably big even if these guys are doing everything right.”

Similarly, Adam points out that the organizations listed represent a tiny share of all research funding. Gur’s thread mentions that translational research was 10% of Bell Labs’ budget. In contrast, these organizations sum up to around 1% of all federally funded research.

Maybe all of these organizations are good, and we just need to do even more. If that were true, we might expect Breakout Labs to have been an enormous success and raise/deploy more capital. But it’s always possible that while the idea in general is good, the specific implementation still matters, and Breakout Labs just happened to fail. It could also be that while 11 years sounds like a long time, it’s not quite enough to see the effects of what is explicitly pre-commercial.

Or maybe Sarah is right and venture capital, even with an explicit charter, just isn’t well suited to this type of investment.

Thanks to Sarah Constantin and Adam Marblestone for reviewing drafts of this post. Thanks also to Stephen Malina and rkris for their comments.

Appendix A: On the Basic/Translational/Applied Trichotomy

This taxonomy is worth keeping in mind, but it’s ultimately just one axis.

As Arora, Belenzon, et al. detail in section 5.1 of The Changing Structure of American Innovation, and as I summarized earlier, “inventions originating from large corporate labs are different”. Specifically, they are general purpose, practical, multi-disciplinary, and often resource intensive.

Along those lines, Google’s AI research has transformed the entire ecosystem. They:

  • Pay extravagant salaries, driving the world’s best talent into AI
  • Make high profile acquisitions, driving VC funding into AI
  • Create Tensorflow, facilitating future AI research
  • Develop TPUs, reducing the cost of compute, but only for particular applications
  • Own one of the world’s largest datasets

None of this would be possible in startups or universities.

In this view, the gap is not just in “fundamental”, “applied”, or “translational” research, it’s in all the specific niches that industrial research labs could have funded, but can’t anymore. Different work is possible, and without those funding mechanisms, this work won’t happen.

That doesn’t mean the solution is a new government entity aimed at fostering “multi-disciplinary” research or whatever. We should just think about what particular aspects of Bell Labs were praiseworthy, and attempt to create the funding mechanism that will allow them to exist in some new form today.

After writing this, rkris and Stephen Malina told me about Spark, created at Berkeley, and pytorch, created by Soumith Chintala.

Soumith’s contributions to Pytorch seem to have occured mostly in 2016, at which point he already worked at Facebook. Pytorch has 46k stars on Github, compared to 153k on Tensorflow. Spark is at 29k.

Eyeballing the charts, the other early torch contributor as Yangqing Jia who was also at Facebook.

So I may have overstated the impossibility of creating a major ML framework in a university setting, but it does seem like Tensorflow is dominant, and Pytorch was heavily nurtured by Facebook.

Spark really was created at Berkeley. Aside from looking at the Github stars, I can’t really judge how influential it is compared to Tensorflow.

Stephen also notes that there are startups working on ASICs for AI.

Appendix B: Were mRNA vaccines invented by startups or universities?

Gur writes: “Startups are the most vibrant environment today for Bell Labs style intermixing of fundamental research and applied systems. And they are changing the world in Bell-Labs magnitude ways. Just look at @BioNTech_Group and @moderna_tx”

Sarah Constantin rebuts: “This is false. BioNTech and Moderna both commercialized/developed platforms based on innovations from academic labs.”

Who’s right?

In academia, Karikó was “issued an ultimatum, if she wanted to continue working with mRNA she would lose her prestigious faculty position, and face a substantial pay cut.” BioNTech licensed the work she had done with Drew Weissman, then hired her as Senior Vice President. She would go on to lead their work with Pfizer on the mRNA Covid vaccine. (Wired) The article adds that Karikó was considered “not of faculty quality” and that the Upenn admins laughed at her when she announced she was leaving. Another source adds that Karikó “spent the 1990s collecting rejections”.

For his part, Weisman still works in academia, though his lab is funded by BioNTech (MIT Technology Review)

And just to complete the holy academia/industry/government trinity, a third party organization claims Moderna “received approximately $20 million from the federal government in [DARPA] grants several years ago and the funds “likely” led to the creation of its vaccine technology. “

So who deserves the credit? Constantin is right that the innovation originally came from an academic lab, but this should come with the caveat that the university actively attempted to push out the lead researcher. It also seems likely that BioNTech would not have funded the research on their own, had they not seen Karikó publications.

All considered, I don’t walk away feeling like startups or universities are particularly good at fundamental research. Instead, it feels like a miracle that we ended up with commercialized mRNA vaccines at all.

It’s hard to know how much counterfactual impact government funding had, but if the DARPA grants were responsible for Moderna’s success, it’s a promising model for startups working on high-impact long-term technology, funded by someone other than VCs.


[1] It also highlights what I hate about Twitter. Gur provides no evidence for his claims, and is totally wrong on several of them. Constantin makes a vague complaint about VCs based on a single anecdote. [2] Adam’s tweets are confusing and difficult to parse. Everyone is talking past each other to further their own narrative. [3]

[2] Constantin writes:

A startup has to prove it can make money for investors within 5-10 years. The funding model’s not designed for long research projects… At a core level I think this is why my startup failed. I wanted to run a $1-5M experiment that nobody else was doing and seemed like the obvious first step in searching for anti-aging drugs. VC’s weren’t interested. You’re supposed to do that part in academia.

This might be true, but we should be very cautious of the argument “VCs wouldn’t fund my company working on X, so they must not be interested in the category X belongs to.” Per Thiel and Collison, startup failure is overdetermined. Maybe your startup couldn’t raise money because VCs are myopic, but there could be 100 other equally valid reasons.

[3] I’m being polite here, I really hate Twitter. Gur’s thread is filled with distracting gifs to the point of being nearly unreadable. The Constantin thread is over a dozen tweets long, with replies to individual subtweets that branch off, making the conversation impossible to follow.

I don’t know why anyone even tries to use this platform for substantial discourse. My best guess? They aren’t. Discourse was never the goal, just hot takes, dunks, and self-promotion.

I don’t say this to criticize the specific people involved, it’s all endemic to the platform, and not really anyone’s fault. Except for mine for reading the thread, and yours if you participate in this hellscape.

[4] I didn’t have to dig around to cherry-pick those quotes. It’s just the first line of each organization’s about page.