Being publicly traded and with a market cap of about $70 billion as of this writing, Moderna is emphatically not an academic institution. While it may seem cynical to say given the extraordinary contribution its mRNA COVID-19 vaccines have made to global public health, its job as a corporation is to provide its shareholders acceptable return on investment. Since the Cambridge, Mass.-based biotech firm went public four years ago, it has succeeded on that front: The company is worth roughly 10 times its offering price.
Yet different as they may be, academic research institutions can learn from Moderna in three key ways. First, know who you are and what you want to become. Second, either lead or join an ecosystem – or do both. Third, let data help you achieve your goals.
1. Know thyself (and thy ambitions)
Moderna recognized early that it wasn’t – and didn’t aspire to be – a diversified life science company, a “big pharma” player, or a drug manufacturer. Rather, the company would dedicate itself to high-velocity research into mRNA vaccines and therapeutics. As Moderna CEO Stéphane Bancel has put it, his company’s corporate mission is to pursue “innovative vaccine solutions to address infectious diseases that post the greatest risk to public health through collaborative research and development.”
Academic research institutions also have much to gain from self-knowledge, and there are many examples of the fruits of such organizational introspection. Among the more ambitious examples is King Abdullah University of Science and Technology (KAUST). It was founded in 2009 with the aim of becoming the MIT of the Middle East. It hired the leader of the National University of Singapore as its first president, the president of Caltech as its second, and the president of Hong Kong University of Science and Technology as its third. All three had extensive previous experience with marquee U.S. academic and federal research institutions. KAUST’s ambition from the outset was to join the global elite, and it has hired accordingly.
Of course, it’s easier to have grand ambitions when you have a $20 billion endowment from the get-go – this would be the sixth largest among U.S. universities, behind only Harvard, Yale, Stanford, Princeton, and MIT. But the National University of Singapore, with an endowment roughly a quarter of KAUST’s, has been no less ambitious – and very successful. Its approach has been to partner with those whose research-outcome and reputational company it wants to keep. And so we have the Singapore-MIT Alliance for Research and Technology (SMART) and the Duke-NUS Medical School.
There are other examples worth noting. Penn State, a state school in a small town north of Philadelphia, has developed longstanding expertise doing military research, particularly with the U.S. Air Force, and has invested in high levels of security to foster that work. Purdue University, a state school in Indiana, has developed a niches as a domestic (rather than global, as is the case with an MIT or a Caltech) engineering-research powerhouse and, interestingly, a “cradle of astronauts,” Neil Armstrong among them. Across the pond, École polytechnique fédérale de Lausanne (EFPL) took the opposite tack to Purdue’s, recognizing the limitations of being a strictly domestic research house in a country with a population only half again the size of Indiana’s. Its strategy was to become an international player, which it has done through partnerships and on the strengths of several Swiss federal research laboratories on campus.
2. Think ecosystem
As the above examples show, partnerships go hand-in-hand with achieving ambitious goals, and Moderna’s May 2022 announcement of its mRNA Access program illustrates the company’s ongoing commitment to developing an ecosystem to speed mRNA development across many fronts. The idea is to create, as Bancel put it, “a community of global scientists who can access our mRNA vaccine technology from anywhere in the world. The world needs novel, innovative approaches to address both known and emerging infectious diseases and we know we can’t go it alone.” The goal is to harness a growing ecosystem to speed up the pace of innovation while simultaneously casting a wider net of vaccine and drug targets.
The mRNA Access program will further transform Moderna into a platform for collaboration in all aspects of the mRNA vaccine and therapeutic supply chain, from research to production to distribution through commercial, academic, and government partnerships. In essence, Modena provides the platform and serves as organizing principle around which ecosystem partners ranging from the Gates Foundation to pharmaceutical giant AstraZeneca to academic research teams give and take.
As the author affiliations of countless research papers show, multi-institutional collaboration is nothing new in academia. The lesson from Moderna has to do with the top-down, strategic nature of those partnerships. These aren’t faculty researchers working ad-hoc with colleagues at other universities – though that sort of collaboration remains indispensable to the march of science. Rather, these are deliberate, formalized, contractual partnerships, ones established and fostered through a strategic understanding of one’s own strengths.
Such partnerships may involve a university establishing itself as the hub of activity, or it may simply be about choosing to participate and apply that institution’s expertise as a partner in an ecosystem established by the likes of Moderna, a government agency such as DARPA or NREL in the United States, or another university. Given that every research institution has its core strengths and areas for growth, the right answer to the hub-versus-spoke question is often “both.”
3. Harness data
Participating in – or serving as the nexus of – a high-velocity research network such as Moderna’s involves more than automating research processes and establishing digital interconnectivity (collaborative research portals, open APIs, and so forth) that specific collaborative research and development programs demand. Harnessing data is increasingly vital in establishing and managing portfolios of research programs as well as amassing the evidence, as it were, to be used to build upon past and current successes.
A recent development of note is the increasing use of artificial intelligence-powered cloud solutions to automate the pre-award process of finding research sponsors and the grants they’re offering as well as amassing the background needed to write grant proposals. That spares investigators and PhD-level research-team members from tedious up-front legwork and time away from their research benches.
Data can also speed the pace of research indirectly in a couple of ways. A University of California system research leader felt her institution’s ranking among research universities should have been markedly higher than it was getting credit for. The problem, she sensed, was that she had no way of knowing what her own organization’s various investigators were working on and had accomplished. She spearheaded the development of a research activity hub cataloging grants applied for and won, papers published, and other metrics. Sure enough, the “business case” that data undergirded has helped the institution move up the rankings.
More broadly, data can indirectly help speed the pace of academic research by letting institutions and their leaders focus on strategic direction and high-value work rather than worrying about the nuances of procurement, finance, HR, and other core systems. Thanks to advances such as robotic process automation, these tools are increasingly relieving academic leaders of necessary but ultimately time-consuming and low-payback administrative tasks.
Moderna is perhaps the highest profile among those pursuing ecosystem-driven, high-velocity research. But the company is far from alone in recognizing that solutions to the complex problems demanding the attention of our best minds involve many disciplines, and that solving those problems entail partnering well beyond the status quo. Recognizing your institution’s strengths and goals, embracing and enabling strategic collaboration, and harnessing data to facilitate researchers and streamline their organizations are imperative in ensuring that our collective scientific investments not only expand the scope of human knowledge to the benefit of society, but also advance the interests of the institutions involved.
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