Risky Business: How to Capitalize on the Success of Big Science

By Angelo Kenneth Romasanta, Jonathan Wareham, Laia Pujol Priego, Pablo Garcia Tello, Markus Nordberg

Big science is expensive and ambitious. New research telescopes can cost over a billion dollars to build, a robotic mission to Mars or Jupiter costs two or three times more than that, and large particle accelerators are more expensive still. Thousands of researchers from around the world work together on big science projects and dozens of governments split the hefty bills.

Why?

The pursuit of knowledge for its own sake might be reason enough for scientists to take the money, but given the large sums involved, policymakers need to find other reasons to justify spending it. Big science often requires new solutions to tough engineering problems, which drives innovation: new technologies developed for basic science can then be applied to problems other than those they were devised to solve.

Big science often requires new solutions to tough engineering problems, which drives innovation.

Take White Rabbit, a system for synchronizing clocks that was developed to measure the billions of collisions that take place every second at the Large Hadron Collider, the premier particle accelerator at CERN, the European Organization for Nuclear Research. The system is now deployed in high-frequency trading, telecommunications networks, air traffic control, and electrical grid management.

Breakthroughs such as White Rabbit are often called “deep tech.” Too often, sophisticated technologies like these end up lying dormant within the walls of the labs where they were created. They might be useful elsewhere, but they can be cost-prohibitive to commercialize. And doing so hasn’t historically been a high priority within big science projects where business ventures were long seen as a lowbrow distraction.

This has changed somewhat in recent years, especially due to pressure exerted by policymakers on big science organizations to extend their impact beyond basic research. Nonetheless, bottlenecks exist at every stage of the technology transfer process. Commercializing deep tech is challenging for scientists: the market applications are often far from obvious, normal funding instruments favor quicker returns, and the professional cost of diverting serious research toward business endeavors can be high. Some big science organizations have established technology transfer offices, but they are limited in what they can accomplish; the disconnect between basic science and business is just too big.

Money alone isn’t the answer. Many public and private funding sources have been around for years. For instance, the European Innovation Council Accelerator and the European Institute of Innovation & Technology give companies funding to scale up their innovation ideas, in addition to business coaching and mentoring from investors, corporate representatives, and other entrepreneurs. The Defense Enterprise Science Initiative in the United States supports university-industry collaborations to create defense technologies. The US Small Business Innovation Research program gives grants to small businesses that commercialize technologies in collaboration with nonprofit research institutions. At later stages of business development, the European Investment Bank provides capital to small businesses wanting to scale up. On the private side, there are corporate entities that scout for technology transfer opportunities, such as Bayer’s Grants4Targets. Corporations such as Google, Microsoft, and IBM frequently invest in deep tech to enrich their research and development portfolio.

Although funding is critical, deep tech faces special needs that funding alone cannot address. Nascent technologies need nurturing and time. One effort that we’ve been involved with is the ATTRACT project, which is creating a decentralized structure for big science organizations to support researchers who are trying to commercialize deep tech innovations. The ATTRACT consortium includes leading European research agencies such as CERN, the European Molecular Biology Laboratory, the European Southern Observatory, the European Synchrotron Radiation Facility, the European X-Ray Free-Electron Laser Facility, and the Institut Laue-Langevin.

Commercializing deep tech is challenging for scientists: the market applications are often far from obvious, normal funding instruments favor quicker returns, and the professional cost of diverting serious research toward business endeavors can be high.

ATTRACT is novel in that it brings together these preeminent research infrastructures to construct a deep tech funding instrument to develop and transform the sensing, imaging, detection, and computation technologies built for basic science. These technologies can be applied to healthcare, energy, agriculture, or the Internet of Things. Since it began in 2018, the project has awarded 100,000 euros each to 170 different projects (or 17 million euros in total). ATTRACT is now moving into a second phase that will extend an additional 35 million euros of funding to the most successful projects in order to grow them into full-fledged companies. ESADE Business School and Aalto University are providing training in entrepreneurship, marketing, and finance.

We view ATTRACT as an experiment: Can big science projects be systematically commercialized?

Making wise bets

Implicit in the historical narratives that celebrate innovations emerging from big science is what we call the “de-risking hypothesis.” This is the idea that big science projects develop and test new technologies and operate them at a substantial scale; this demonstration makes the technologies an attractive bet for venture capital firms looking to find innovative applications for technologies, since the development and testing are already complete—increasing the chances of commercial success.

From analyzing the 170 funded projects in ATTRACT­­, we find some support for this hypothesis. Project applications fell into three main domains: healthcare, industrial processes, and scientific applications other than those for which they were originally designed.

Many of the healthcare projects originate in particle physics and astronomy. For instance, the MESO-CORTEX project is creating a brain-imaging device that overcomes current limits in recording brain activity at the millimeter to centimeter scale. At the mesoscopic scale, brain imaging is challenging due to the curvature of the cerebral cortex. This limits the access of traditional imaging techniques to only a small region of the brain. To solve this, the project brings advances from astronomic instrumentation to create a curved sensor system that compensates for the nonplanar shape of the brain. By enhancing the imaging capability at this scale, the technology has the potential to reveal new insights about how the brain’s neurons operate and it may be able to assist in clinical assessments prior to neurosurgeries.

In industrial processes, many ATTRACT-funded projects are building the foundational industrial technologies that manufacturers can harness to create future offerings. The Q-MAM (quantum membrane accelerometer microchip) project aims to create next-generation accelerometers. Previous accelerometer designs were severely limited by thermal noise present in the environment. To exponentially improve the sensitivity of these accelerometers, the project created an opto-mechanical sensor, where the motion of a suspended membrane is measured through an optical readout at a scale “normally reserved for describing the radius of atoms,” according to the project description. This novel design opens new sensing applications for cell phones, airplanes, cars, and space travel.

To exponentially improve the sensitivity of these accelerometers, the project created an opto-mechanical sensor, where the motion of a suspended membrane is measured through an optical readout at a scale “normally reserved for describing the radius of atoms.”

We also saw many projects that very much cater to the scientific community but hope to have wider commercial potential in the future. The HighQE project aims to increase the efficiency of photocathodes, which are crucial components of particle accelerators. Photocathodes absorb photons and convert them to electrons through the photoelectric effect. However, current photodetectors are limited in this conversion, as measured by their low quantum efficiency at around 35%. The project aims to increase this to 90% through an ultrathin membrane that favors the emission of electrons. If successful, this could have the immediate effect of replacing current detectors in the colliders and thus enable greater precision in experiments within the particle physics community. Down the line, by boosting sensor sensitivity to light, the technology could enable better nighttime viewing for smartphones and more robust cameras for self-driving cars.

By the end of 2020, 14% of ATTRACT projects had received additional private funding while almost a third had acquired additional government grants. Looking at the 170 projects in total, we came to the following conclusions:

• We found a great deal of evidence that novel, cross-disciplinary ideas emerged naturally at big science research infrastructures. Thus policies aimed at stimulating ideation or cross-pollination onsite are not an immediate priority. Instead, emphasis should be placed on mechanisms that help these ideas advance in technical and market maturity.
• We found substantial evidence that often the professional practices, norms, and cultures of scientific research infrastructures are distinct from entrepreneurial mindsets and experience. On one hand, this makes it difficult for research infrastructures to commercialize their technologies. On the other hand, this gap can be desirable as it gives scientists the freedom to perform risky, path-breaking research uninhibited by industry demands.
• In the past, research infrastructures have been pressured to be more entrepreneurial, leading them to hold business training, pitch workshops, and networking sessions. Instead of forcing these infrastructures to change their culture and shift their priorities, it may be more desirable to simply pair these infrastructures with natively entrepreneurial organizations. Innovation policy can pursue this low-hanging fruit by focusing on the mechanisms that best bridge the high technical acumen of the research infrastructures with the appropriate business capabilities. However, much more research is needed on what forms of relationships are most effective in addressing these gaps.
• The proposals funded under ATTRACT came from disparate scientific disciplines and solved problems in a wide variety of domains. Each of these fields has its own nuances and trajectories toward commercialization. For example, medical technologies will take different paths to product development than consumer devices. One aspect that many funded projects appreciated was ATTRACT’s flexibility and openness, which allowed project teams to pursue activities that seemed to be the best fit for their field and application.
• Scientists often know a lot about technology trends (e.g., higher sensitivity photodetectors), without necessarily understanding the market conditions that could accept these technologies. Consequently, innovation policy should be further refined to determine the best mechanisms for increasingn knowledge and engagement with downstream applications.
• ATTRACT and related tech transfer initiatives from NASA, the European Space Agency, or other research infrastructures are very much technology-push policy instruments, meaning they are grounded by the philosophy that new technological advances drive the creation of new product development. As such, ATTRACT received many proposals that were at the cutting edge of what is technologically possible, but lack any specific market application. In contrast, demand-pull instruments work in reverse, assuming that the needs of the market inform what technologies need to be developed. Research on how to couple these two instruments can inform how to best leverage the strengths of each type of initiative without excessive distortion to its primary institutional mandate.

The next phase of ATTRACT

Since the earliest days of big science, technologies from research infrastructures have been put to novel uses. Early twentieth-century particle accelerators were deployed to develop radioactive isotopes for oncology research, providing a much-needed source of income for funding basic research during the Great Depression. But such offshoots and spin-offs have been rare, often used as glamorized anecdotes used to embellish the public relations machinery of big science. What’s more, there are many aspects of technology transfer and deep tech entrepreneurship that we simply do not understand.

We found substantial evidence that often the professional practices, norms, and cultures of scientific research infrastructures are distinct from entrepreneurial mindsets and experience.

In the current policy landscape, billions of dollars are invested to fund thousands of scientific and business initiatives. However, policymakers have not been as thorough in evaluating whether and how these initiatives have been effective in spurring innovation. The aversion to experimentation is not surprising; given the complexity of innovation, it is difficult to define proper evaluation metrics. Indeed, an innovation policy’s success is not easily boiled down to simple metrics, such as the number of products developed, patents filed, or jobs created in a region. Given the uniqueness of the individual cases, any rigorous evaluation of the appropriate levers to stimulate and support technology transfer across diverse scientific domains and institutional regimes is elusive. However, despite measurement challenges, public accountability demands that we seek a deep and holistic understanding of how, where, and why such policy levers are effective.  

By design, ATTRACT recognizes its innately experimental nature. By embracing trial and error, it follows a minimum viable ecosystem (MVE) approach. In the start-up world, the term minimum viable product refers to an offering created by a company with just enough features to provide quick feedback from customers. Starting small, ATTRACT pools European research infrastructures together with experts from the deep tech investor and business communities, creating an MVE test bed where big science projects can be screened for commercialization potential. To evaluate whether ATTRACT is effective in commercializing deep tech, 1 million euros has been allocated to fund studies to holistically assess the socioeconomic value of ATTRACT. Such evaluations are not limited to traditional estimation of economic multipliers but include complementary perspectives from sociology, education, psychology, political science, and other disciplines.  

Given the complexity of innovation, it is difficult to define proper evaluation metrics.

Given the quasi-experimental nature of ATTRACT, we hope to begin to answer questions of how best to leverage deep tech’s potential across a diverse sample of research institutions and commercial applications. For example, we hope to better explain how deep tech entrepreneurship coming from one discipline might differ from another (e.g., physics versus astronomy). Does the difference in the size or scope of the research infrastructure affect how deep tech can be commercialized? Does the nature of how science is funded and practiced in one field make it more amenable to entrepreneurship than another field? Do scientific disciplines have meaningful distinctions in the kind of support needed for business training or partnering with funders and entrepreneurs? Does a scientific field’s proximity to business affect what it needs to commercialize deep tech (e.g., life science is close to the pharmaceutical industry; high-energy physics is more distant from potentially relevant sectors such as energy or healthcare)?

Big science will continue to conduct the world’s most ambitious experiments. The instruments used in this research will push the limits of what technology is capable of. As these cutting-edge technologies are being developed, we can employ them to help solve big societal challenges. Through experiments like ATTRACT, we are gaining insight into the levers and support needed to systematize a historically serendipitous process of deep tech entrepreneurship.