Towards a framework for a new research ecosystem

Savona, Roberto et al. Working Paper Towards a framework for a new research ecosystem JRC Working Papers in Economics and Finance, No. 2024/2 Provided in Cooperation with: Joint Research Centre (JRC), European Commission Suggested Citation: Savona, Roberto et al. (2024) : Towards a framework for a new research ecosystem, JRC Working Papers in Economics and Finance, No. 2024/2, European Commission, Ispra This Version is available at: https://hdl.handle.net/10419/299593 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Towards a Framework for a New Research Ecosystem R. Savona C. M. Alberini L. Alessi I. Baussano P. Dellaportas R. Guerra S. Khozin A. Modena S. Pecorelli G. Rasi P. D. Siviero R. M. Stein 2024 JRC Working Papers in Economics and Finance, 2024/2 This publication is a Working Paper by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking process. Working Papers are pre-publication versions of technical papers, academic articles, book chapters, or reviews. Authors may release working papers to share ideas or to receive feedback on their work. This is done before the author submits the final version of the paper to a peer reviewed journal or conference for publication. Working papers can be cited by other peerreviewed work. The contents of this publication do not necessarily reflect the position or opinion of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication. 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The European Union does not own the copyright in relation to the following elements: - Cover page illustration, © stock.adobe.com How to cite this report: Savona, R., Alberini, C.M., Alessi, L., Baussano, I., Dellaportas, P., Guerra, R., Khozin, S., Modena, A., Pecorelli, S., Rasi, G., Siviero, P.D., and Stein, R.M., Towards a Framework for a New Research Ecosystem, JRC Working Papers in Economics and Finance, 2024/2, European Commission, Ispra, JRC134830. 3 Executive summary The global COVID-19 pandemic provided a “natural experiment” that demonstrated how international public-private collaborations can be not only feasible but also effective for addressing worldwide emergencies. The medical and scientific communities have been brought together and rallied to address a global health crisis, and have produced a number of effective treatments and prophylactics to control COVID-19. A similar coordinated approach, postcrisis, could be applied more generally, to help increase investments in science, innovation, and technology (SIT). However, there remain significant challenges. In particular, the high costs and risks of investing in transformative “long shots” – initiatives with sometimes unattractive individual investment profiles, but which produce outsized returns on success – require discipline and patience to be successful, which can further complicate decisions to pursue these investments. As a result, society as a whole has often missed potential opportunities to reap massive tangible and intangible benefits from long-term scientific research, due to a relatively shorter-term investment focus coupled with a lack of motivation to pursue unorthodox, often risky, approaches to supporting scientific progress. Moreover, aggregate global government investments in basic and translational science is generally channeled towards supporting incremental progress, and undertaken largely with-out the benefit of substantive coordination at an international level. Finally, since the economic value that results from innovative projects is typically not fully appropriated by developers/inventors, the private sector tends to underinvest in ambitious large-scale scientific projects, even when they are characterized as having attractive payoffs for success, because of the corresponding high up-front development costs, high risk of failure, incompatibility with standard work-flows, and long gestation periods. As an alternative to one-off independent investments in SIT, strategies that encouraged international coordination, along with public-private collaboration that would combine public funding with additional private capital from investments by institutional investors, hold the potential to increase the scale and efficiency of R&D investment in SIT. The key to such strategies would be to create systems and incentives that would serve to catalyze investment in early-stage and translational R&D, by using the experiences of the COVID-19 pandemic response to inform more collaborative models. In this short paper we outline 4 of the key issues that we have identified as critical challenges that must be addressed in order to develop an environment conducive to collaboration across organizations and governments, while also preserving commercial rewards for investors and innovators: 1. Increasing funding incentives through lower risk financing models; 2. Researcher collaboration through various physical and virtual cross-disciplinary laboratories that create both incentives and infrastructure for sharing novel research results at all stages of the scientific process 3. Demarcating specific roles and opportunities for governments and public institutions (GPI), and 4. Revising regulatory and legal frameworks for governance and control of research, including those for protecting and sharing rights to IP. 4 Towards a Framework for a New Research Ecosystem Roberto Savona*,a, Cristina Maria Alberinib, Lucia Alessic, Iacopo Baussanod, Petros Dellaportase, Ranieri Guerraf, Sean Khozinh, Andrea Modenah, Sergio Pecorellia, Guido Rasii, Paolo Daniele Sivieroj and Roger M. Steink, l This draft: 5 February 2024 Abstract: A major gap exists between the conceptual suggestion of how much a nation should invest in science, innovation, and technology, and the practical implementation of what is done. We identify 4 critical challenges that must be address in order to develop an environment conducive to collaboration across organizations and governments, while also preserving commercial rewards for investors and innovators, in order to move towards a new Research Ecosystem. Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization. *Corresponding author. Roberto Savona, Dept. of Economics and Management, University of Brescia, C/da S. Chiara 50–25122, Brescia, Italy. roberto.sav[email protected] aUniversity of Brescia; bCenter for Neural Science, New York University; cEuropean Commission–JRC; dInternational Agency for Research on Cancer (IARC/WHO), Early Detection, Prevention and Infections Branch, Lyon, France; eUniversity College London & Athens University of Economics and Business; fNational Academy of Medicine, Italy; gUniversity of Mannheim; hLaboratory for Financial Engineering, MIT, iUniversity of Rome Tor Vergata; jFarmindustria; kStern School of Business, New York University; lNYU Center for Data Science. 5 “You may ask … How can I be a millionaire and pay no taxes …?” “FIRST: Make a million dollars …” Steve Martin 1 Introduction‡ The global COVID-19 pandemic provided a “natural experiment” that demonstrated how international public-private collaborations can be not only feasible but also effective for addressing worldwide emergencies [1]. A coordinated, collaborative work approach was instrumental in securing social and economic pandemic resilience at an international level [2]. We learned how clearer and more coordinated scientific advice would reflect on more efficient policy decisions and public communication. We also “measured” the potential of public-private partnerships, which were essential in the battle against the pandemic. Winston Churchill has been quoted 1 as admonishing that one should, “never let a good crisis go to waste.” Churchill was commenting on the unique set of events that took place during and immediately following World War II that brought world leaders together to form the United Nations. The medical and scientific communities are now in a similar position, having been brought together and rallied to address a global health crisis, and having produced a number of effective treatments and prophylactics to control COVID19. Could a similar coordinated approach, post-crisis, be applied more generally, to help increase investments in science, innovation, and technology (SIT)? Perhaps. But there remain significant challenges. A significant challenge that hinders structured investments in SIT is often the absence of a pressing crisis that would justify transformative objectives. Furthermore, the high costs and risks of investing in transformative “long shots” – initiatives with sometimes unattractive individual investment profiles, but which produce outsized returns on success [8] – require discipline and patience to be successful, which can further complicate decisions to pursue these investments. As a result, society as a whole has often missed potential opportunities to reap massive tangible and intangible benefits from long-term scientific research, due to a relatively shorter-term investment focus coupled with a lack of motivation to pursue unorthodox, often risky, approaches to supporting scientific progress. ‡We are grateful to Michael Spence and to a former government official for detailed comments and suggestions on earlier drafts. All errors are our own. 1 Though Churchill does appear to have said this, it is not clear that he was the first; the provenance of the original quote is ambiguous. 6 Indeed, investments in visionary research and development (R&D) projects that hold the prospect of enormous social and economic value are often curtailed due to the empirical record of investments in which the returns on such projects can potentially take years or decades to emerge. At the same time, the long-term and variegated benefits of basic scientific discoveries, though hard to predict ex ante , can have significant economic, environmental and social benefits across a wide array of applications and fields. Historically, many basic scientific discoveries have ultimately resulted in outsized impacts on social welfare, while conferring catalytic effects on other research and investment opportunities (and generating attractive returns for investors). In many cases, the future impact of a scientific discovery is only envisioned vaguely, if at all, at the time the related research is undertaken. Some recent examples include applications of CRISPR gene-editing technology [3], Tesla’s leveraging of battery and solar technologies [4], and the production of mRNA vaccines for COVID-19 and other conditions [5]. Despite these proof cases, aggregate global government investments in basic and translational science is generally channeled towards supporting incremental progress, and undertaken largely without the benefit of substantive coordination at an international level [6]. Moreover, since the economic value that results from innovative projects is typically not fully appropriated by developers/inventors, the private sector tends to underinvest in ambitious large-scale scientific projects [7], even when they are characterized as having attractive payoffs for success, because of the corresponding high up-front development costs, high risk of failure, incompatibility with standard workflows, and long gestation periods [8]. While the returns on successful innovations can be extraordinarily attractive, the very high probability of failure and the long development time-horizon have made such investments attractive to only few specialized private investor classes, whose funding collectively represents only a small fraction of investment capital more broadly. Furthermore, due to regulatory uncertainties and the potential for future competing innovations, it can be uniquely challenging to estimate the commercial viability of long-term development projects accurately. The 2015 Report of the Scientific Advisory Board of the UN Secretary-General [9] reported that many governments espoused the view that a target funding allocation of as little as 1% of global GDP for R&D was still too high. Nonetheless, the subset of countries with the strongest SIT systems actually invested as much 3.5% of national GDP in science, innovation and technology research. As an alternative to one-off independent investments in SIT, strategies that encouraged international coordination, along with public-private collaboration that would combine public funding with additional private capital from investments by institutional investors, hold the potential to increase the scale and efficiency of R&D investment in SIT. The key to such strategies would be to create systems and incentives that would serve to catalyze investment in early-stage and translational R&D, by using the experiences of the COVID19 pandemic response to inform more collaborative models. 7 In this short note, we outline 4 of the key issues that we have identified as critical challenges that must be address in order to develop an environment conducive to collaboration across organizations and governments, while also preserving commercial rewards for investors and innovators: 1. Increasing funding incentives through lower risk financing models; 2. Researcher collaboration through various physical and virtual cross-disciplinary laboratories that create both incentives and infrastructure for sharing novel research results at all stages of the scientific process 3. Demarcating specific roles and opportunities for governments and public institutions (GPI), and 4. Revising regulatory and legal frameworks for governance and control of research, including those for protecting and sharing rights to IP. While these challenges are prevalent in various organizational and institutional settings more generally, they also present particular opportunities for global research efforts in the scientific domain due to their unique characteristics and nuances. Rather than offering definitive solutions, our intention in what follows is to present a positive (i.e., nonnormative) perspective on these challenges, and to outline a basic set of signposts to stimulate dialogue among experts in various fields including science, medicine, computer science, finance, law, policy, and academia. Our goal is to encourage global discussion, debate, and ultimate action that can contribute to the design of a new research ecosystem. 2 Four Challenges 2.1 Challenge #1: Accelerating Funding Although funding is often discussed as the primary challenge to precipitating long-shot investments, it is ironically the challenge for which we already seem to have many of the most well-developed solutions. We describe many investment in SIT projects as being “long shots” in the sense of Hull, Stein and Lo[8]. Long shot investments are characterized by (a) a very low probability of success; (b) long investment horizons; (c) substantial upfront capital requirements; but which also enjoy (d) outsized commercial returns upon success. Empirically, the majority of retail and institutional investors prefer more traditional, less risky investments that enjoy shorter return horizons and lower expected returns, with much lower outcome uncertainty. Despite these seemingly less attractive features, long shot investments can often offer attractive returns when successful. Science-focused investment vehicles can potentially mitigate this long shot problem by employing results from modern portfolio theory, which provides guidance on structuring portfolios of investments, such that the volatility (risk) of the portfolio is reduced, while still maintaining attractive return profiles, relative to the individual investments in the portfolio. Properly structured portfolios of long-shots can greatly reduce the risk to investors, while still maintaining a comparable return. 8 Recent work by financial economists has demonstrated that risk pooling structures can serve as the basis for effective funding vehicles that provide longer-term capital for research, while also delivering marketrate returns for investors. Said differently, such structures can achieve substantial social and scientific impact, without requiring that investors give up investment returns. Most notably, a new class of securities, called Research-Backed Obligations (RBOs) – namely, debt and equity securities backed by the pool of underlying drug assets issued by ‘mega-funds’ to raise capital and finance the development of pipeline drugs in its portfolio –, are designed to fund portfolios of pooled longshot research investments in candidate medical therapies for cancer and rare genetic diseases by taking advantage of portfolio diversification to issue high-quality (and thus lower cost) portfolio-level debt [10], [11], [12]. Similarly structured financial vehicles could play a key role in increasing investment in other areas of scientific research. Importantly, these new structures do not require that investors trade return for impacts . Rather than forcing investors to give up investment return to achieve social impact, RBOs can offer attractive risk/return profiles, while also generating impact. However, not all R&D challenges are suitable for vehicles such as RBOs. For example, the current stateof-the-art in Alzheimer’s research, along with the dearth of viable AD (Alzheimer Disease) therapy projects appears to make funding research in that area via an RBO structure difficult due to an extremely high probability of failure and a lack of appropriate diversification options at the present time [18]. Thus, while the RBO approach has wide applicability in a many scientific domains, and has demonstrated some early successes in biomedical research, there remain other areas which are not suitable to such an approach. In such settings, given the enormous scale of investment required and the exceedingly low ex ante probability of success, it may be that only a well-funded socially motivated entity, like a government agency, can ensure sufficient capital and investment discipline to fund research. [8] Between these two different sources of funding – public vs. private – there exists a middle ground, in which projects representing “ultra-long-shot” research may still be attractive to private investors, but may not necessarily require public funding. For such investments, hybrid financing approaches have also been introduced in the economics literature. For example, an approach suggested by [13], may offer tools that support the creation of vehicles to fund “ultra-long-shot” R&D projects by combining investments in both highand low-risk research projects, along with investments in traditional low-risk financial instruments such as government bonds (albeit with potentially lower expected portfolio returns). Under such a hybrid strategy, a portfolio manager follows a search and ‘wait or invest’ approach: projects are ordered according to a specific scoring formula, defined by the portfolio mandate or investment policy (potentially augmented with a strategic consideration of the knock-on contribution to other or future portfolio projects of the research). These investment strategies require that (a) investment decisions be interconnected across time, geography, and research domains; and (b) portfolios are structured into sub-portfolios that differentiate between connected lead (riskier) projects and backup (less risky) projects that serve to reserve capital for future development. In some settings this coupling approach may reduce the risk that lead projects fail due to a lack of interim funding. Of course, the expected return on a sub-portfolio of less 15 companies, and even the U.S. Army; and (iii) a small, efficient and politically-independent unified governance structure to take decisions quickly. This governmental intervention was essential to vaccine development, first, by providing massive support to private enterprise, second, by mitigating scientific as well as manufacturing and market risks related to possibly low demand [24]. It will also be important to recalibrate research incentives for both government agencies and academic institutions. It is natural for research centers to push back on collaborations that require coordination with other institutions because many researchers value “autonomy” highly, both for intellectual reasons and political and organizational ones. Furthermore, creating incentives that encourage interorganizational collaboration can be especially challenging in academia, where data sharing is often inhibited by virtue of “publish or perish” merit systems at many academic institutions. This reward structure can overshadow many other motives. This incentive structure can also skew research quality and follow-through, since researchers may rewarded much more for producing “high quality” publications than for facilitating pragmatic applications of their scientific output. [25] Universities and other academic and commercial research organizations that choose to participate in collaborative research initiatives and virtual labs will have the opportunity, and the imperative, to rethink, at a fundamental level, how collaborative research is recognized and rewarded at their institutions, as well as the degree to which translation of research ideas is weighed alongside innovation and breakthroughs when researchers are evaluated at different points in the research lifecycle. 3 Operationalizing a Research Ecosystem The purpose of this article is to outline what we have identified as key impediments to the formation of multi-disciplinary pan-geographic collaboration projects to address critical and, in some cases, existential societal challenges. We have specifically not attempted to propose omnibus solutions to any of these. Such solutions require many more eyes and ideas that we can bring to bear in a single article, and will sometimes demand resources and legal frameworks which we have no standing to allocate. However, there are things that can be done to start this process. For example, one way to begin such efforts is to create a research ecosystem architecture (see Figure 2). As an initial, much less demanding foray into such planning and discussions, it is reasonable for smaller groups of researchers and other participants to undertake a set of pilot studies to explore what is currently feasible for addressing the four challenges we have outlined in this article. Such pilots would include experts from various relevant parties – academic, industrial, government and finance – with the goal of rigorously exploring – and perhaps competing – theoretical, technical, and institutional frameworks for the addressing specific aspects of the challenges we outlined earlier. 16 Because such an approach would require new contexts, such groups could be made more productive and agile by creating sandbox-based processes that would permit them to experiment in live environments, but with safeguards in place to ensure that such experiments did not result in unintended consequences in society and the economy more broadly. It seems both productive and feasible to consider exploring several broad sets of questions in parallel. For example, different pilot groups might undertake topics relating to:  Marketplace of Ideas and translational IP: The mandate of this pilot would be to realize a decentralized market where innovators would be able to sell ideas to entrepreneurs and institutional investors using financial structures and instruments whose profitability was contingent on those ideas. (challenge #1 and #4). Existing examples are EIC Marketplace (https://eic.ec.europa.eu/eic-communities/eic-marketplace_en), InvestEU Portal (https://ec.europa.eu/investeuportal/desktop/en/index.html), Innovation Radar (http://innovation-radar.ec.europa.eu), etc.  Research Collaboration Platform: The mandate of this pilot would be to create a framework for building “knowledge maps” that would allow researchers across disciplines to more easily understand how innovations outside of their core field might be valuable to achieving a specific scientific goal. This would naturally precipitate scientific collaborations across researchers and ideas (challenge #2).  Regulation and Supervision: The mandate of this pilot would be to draft a formal set of feasible options, both within current frameworks that could be achieved by introducing or modifying regulation and laws. This prolog would also enumerate and identify the roles and actors required to effectuate a research ecosystem supervision mechanism (challenge #3 and #4). Table 1 summarizes this example of the different pilots and how they fit together as part of the ecosystem. In addition, it gives examples of how each main actor (University Presidents, Research Labs, Researchers, Investment Funds, Funding Agencies, Technologists, Governments) might participate, and how they should interact with each other within the main challenges (Market for Ideas, Research Collaboration, Regulation & Supervision). Again, our intention here is not to set out a prescriptive formula for achieving a research ecosystem. Rather it is to stimulate dialogue among experts in various fields, encouraging global action and contributing to the design of a new research ecosystem. In that regard, we take the position that local stake-holders in their own of geographies and institutions, will attenuate the scope and scale of a pilot in the manner appropriate to their geography, institution and discipline. 4 Conclusion At the end of 2020, UNESCO estimated that global spending in R&D normalized by GPD (R&D/GDP) was roughly 1.9% worldwide. If instead, all countries were to invest on par with the most advanced countries recorded, i.e., at 3.5% of GDP, then based on global GDP at the end of 2021 (around 96 trillion USD) nations would need to close an R&D funding gap of around 1.5 trillion USD. However, even if there were 17 the will to do so, it is still unclear, without more robust coordination, whether the 3.5% observed is the right target, or is too low (or too high); and whether the additional capital would be deployed in an even moderately efficient manner. In the past half century, a number of rigorous theoretical results have emerged in the economics literature, and provided explanations for why investments in novel, ground-breaking scientific projects drive increases in overall welfare [26]-[27]. However, transitioning from normative theoretical results to concrete operational measures is not straightforward, since the trajectory from constellations of often disparate discoveries and theories to the explicit economic growth they produce is complex, non-linear, multidimensional and slow. Furthermore, a major gap exists between the conceptual suggestion of how much a nation “should” invest in core R&D, and the practical implementation of what is done. (Consider again the gap between the 3.5% of GDP invested in SIT by the most advanced countries vs. the average of only 1.9% across national governments overall [9]). One key reason for this gap is the difficulty that investors (and the public sector) have in trading off shortterm costs against long-term planning and investing benefits. A related issue, known as ‘the tragedy of the horizon’[28], has already been identified as a gating factor in the context of climate change, where the devastating consequences of policy and investment decisions made today will, tragically, not be felt by society until times that extend well beyond the horizons normally considered by investors and politicians. In order to reorient investors, more work must be done to articulate the financial risks that are posed by climate change and other SDG (Social Development Goals) related shortfalls. In parallel, we need clearer articulation of the opportunities investing in such initiatives can provide. In this short note, we have offered a coarse roadmap to some of the issues that we see as critical, and which must be driven to consensus in full or in part to motivate a more aggressive and fulsome scientific and financial transformation and redeployment of resources. Our roadmap only provides of a guide to the hazards in this rough terrain, rather than a course through them. Nonetheless, if these issues can be resolved, and initiatives of the sort we have sketched here were adopted on a larger multinational and multidisciplinary scale, a massive science-oriented portfolio allocation could potentially open the door to new ways of research collaboration. Achieving such scale will require that private investors are (financially) motivated to channel their capital towards science-based funding by investing in financial vehicles that can achieve adequate (i.e., marketlevel) risk-return profiles while also providing positive societal impacts. While these financial issues and structures appear to be relatively easier to address, compared to those of governance, and so forth, this financial structuring itself is by no means trivial. 18 For policymakers in government and at academic institutions, the message is similarly clear: collaborative thinking and planning involving industry, academic and government decision makers is a precursor to developing regulatory, policy and academic incentives that enable such broad investment vehicles to form and operate at scale. However, with these vehicles in place, capital from private sector investors will naturally flow towards funding scientific research in order to achieve attractive risk/return profiles, while also providing assetclass diversification. Such investment, in concert with public allocations, may well enable public-private partnerships that would encourage investment at levels that today appear practically viable for only the most advanced economies. Coming full circle then, we conclude by revising the joke at the beginning of this article to reflect our conclusions about the current state of play for the four challenges we discused: “How can we create an infrastructure that solves the problems of organizing large-scale scientific research communities and then fund it? FIRST: Create an infrastructure that solves the problems of organizing large-scale scientific research communities …” 19 5 References 1. Corey, L., Mascola, J. R., Fauci, A. S. & Collins, F. S. A strategic approach to COVID-19 vaccine R& D. Science 368, 948–950 (2020). 2. Harris, J. A. et al. Time to invest in global resilience. Nature 583, 30–30 (2020). 3. Adli, M. The CRISPR tool kit for genome editing and beyond. Nat. Commun. 9, 1911 (2018). 4. Hulac,ClimateWire, B. Tesla’s Elon Musk Unveils Solar Batteries for Homes and Small Businesses. Scientific American https://www.scientificamerican.com/article/tesla-s-elon-musk-unveils-solar-batteries-for-homesand-small-businesses/. 5. Pardi, N., Hogan, M. J., Porter, F. W. & Weissman, D. mRNA vaccines — a new era in vaccinology. Nat. Rev. Drug Discov. 17, 261–279 (2018). 6. Gersbach, H. & Schneider, M. T. On the global supply of basic research. J. Monet. Econ. 75, 123–137 (2015). 7. Aghion, P., Dewatripont, M. & Stein, J. C. Academic freedom, private-sector focus, and the process of innovation. RAND J. Econ. 39, 617–635 (2008). 8. John Hull, A., Roger M. Stein W. Lo. Funding Long Shots. vol. 17 1–33 (2019). 9. https://plus.google.com/+UNESCO. Science, Technology and Innovation: Critical Means of Implementation for Sustainable Development Goals. UNESCO https://en.unesco.org/news/science-technology-and-innovation-critical-means-implementation-sustainable-development-goals (2015). 10. Fernandez, J.-M., Stein, R. M. & Lo, A. W. Commercializing biomedical research through securitization techniques. Nat. Biotechnol. 30, 964–975 (2012). 11. Fagnan, D. E., Gromatzky, A. A., Stein, R. M., Fernandez, J.-M. & Lo, A. W. Financing drug discovery for orphan diseases. Drug Discov. Today 19, 533–538 (2014). 12. Stein, R. Roger Stein: A bold new way to fund drug research | TED Talk. https://www.ted.com/talks/roger_stein_a_bold_new_way_to_fund_drug_research. (2013) 13. Childs, P. D. & Triantis, A. J. Dynamic R&D Investment Policies. Manag. Sci. 45, 1359–1377 (1999). 14. Bloom, N., Jones, C. I., Van Reenen, J. & Webb, M. Are Ideas Getting Harder to Find? Am. Econ. Rev. 110, 1104–1144 (2020). 15. Marblestone, A. et al. Unblock research bottlenecks with non-profit start-ups. Nature 601, 188–190 (2022). 16. Gowers, T. & Nielsen, M. Massively collaborative mathematics. Nature 461, 879–881 (2009). 17. Woelfle, M., Olliaro, P. & Todd, M. H. Open science is a research accelerator. Nat. Chem. 3, 745–748 (2011). 18. Caliskan, A., Bryson, J. J. & Narayanan, A. Semantics derived automatically from language corpora contain human-like biases. Science 356, 183–186 (2017). 19. Evans, J. A. & Foster, J. G. Metaknowledge. Science 331, 721–725 (2011). 20 20. Fortunato, S. et al. Science of science. Science 359, eaao0185 (2018). 21. Fagnan, D. E., Fernandez, J. M., Lo, A. W. & Stein, R. M. Can Financial Engineering Cure Cancer? Am. Econ. Rev. 103, 406–411 (2013). 22. FinSMEs. OrbiMed Closes Israel Life Sciences Fund at $222M. FinSMEs https://www.finsmes.com/2012/04/orbimed-closes-israel-life-sciences-fund-222m.html (2012). 23. Dewatripont, M. Which policies for vaccine innovation and delivery in Europe? Int. J. Ind. Organ. 84, 102858 (2022). 24. Lee, P. PATENTS AND THE PANDEMIC: INTELLECTUAL PROPERTY, SOCIAL CONTRACTS, AND ACCESS TO VACCINES. Wash. J. Law Technol. Arts 17, 193 (2022). 25. Baker, M. 1,500 scientists lift the lid on reproducibility. Nature 533, 452–454 (2016). 26. Romer, P. M. Increasing Returns and Long-Run Growth. J. Polit. Econ. 94, 1002–1037 (1986). 27. Romer, P. M. Endogenous Technological Change. J. Polit. Econ. 98, S71–S102 (1990). 28. Breaking the tragedy of the horizon - climate change and financial stability - speech by Mark Carney. http://www.bankofengland.co.uk/speech/2015/breaking-the-tragedy-of-the-horizon-climate-change-and-financial-stability. 21 Table 1: Example high-level plan for topics and actors in Research Ecosystem Implementation Working Pilots Market of Ideas Research Collaboration Regulation & Supervision University Presidents IP agreements: joint ownership and foreground. Forming special independent vehicles for selling ideas in the market Forming and participating in domain-specific academic research consortia Forming stakeholder groups within the Market of Ideas Board and contribute to define market regulation protocol. Interact within regulatory sandbox platforms (Governments) Research Labs Forming Consortia of Research Labs Researchers Create and test framework for Virtual Labs for pilot working research projects (perhaps selected and evaluated by Governments) Propose requirements for and structure of Virtual Labs, potentially forming small scale proof-cases. Investment Funds Structure and launch investment vehicles such as megafunds or Science-Based Funds, perhaps through private-public initiative Networking with solicited and unsolicited researchers (meetings, on-line platforms, open contests) to detect new forms of research combinations and start with new curiosityor mission-driven projects Funding Agencies Provide funding for Market of Ideas infrastructure Provide funding for realizing Virtual Labs. Defining mission-oriented projects. Provide funding and scientific coordination of meetings and activities Governments Draft feasible mechanisms for providing various forms of downside protection for investors (direct guarantees, direct investments, etc.) Providing independent project evaluation. Realizing project pooling. Designing appropriate IP agreements Design potential structures for regulatory sandbox platforms, including appropriate safeguards to contain inefficiencies and maintain the overall safety and soundness of the research ecosystem 22 Figure 1: Science-Based Fund Note: The Figure depicts the organizational structure of a Science-Based Fund. Investments are diversified between Private Assets (Pure and Secondary Market of successful Venture Capital, namely Private Equity and Start-up) and Low Risk Assets (investments in liquid assets to provide interim returns to the fund and reduce the overall portfolio risk). Private Assets are investments in healthcare and engineering sectors, spanning from Alzheimer, Cancer, Chemistry, Genetic Diseases, Vaccines, on the one hand, to Nanotechnology, Electronics, Robotics, Energy, on the other. High and low risky research projects are combined with low risky financial instruments under a cross-funding approach in which returns from financial vehicles and backup (low risky) investments together with rotational portfolio reallocations are used to successfully fund lead (high risky) projects. •Low Ri sk Assets •Private Assets •Engineering•Healthcare Alzheimer Cancer Chemistry Genetic Diseases Vaccines Nanotech Electronics Robotics Energy Liquidity Infl-linkedBonds Impact & Gvt Bonds Private Equity St art-up Venture Capital 23 Figure 2: A Hypothetical Research Ecosystem Architecture Note: The Figure shows a hypothetical Research Ecosystem Architecture with the 3 main actors: (1) Universities & Research Labs; (2) Science-Based Fund; (3) Government & Public Agency. Universities & Research Labs realize domain-specific academic research consortia and through advanced technology (AI Instruments) detect and cluster research ideas thereby forming Virtual Labs. Research Projects come from Virtual Labs, are evaluated by a Public Agency and incentivized (R&D Incentives) by the Government. SBased Funds invest in Research Projects, benefit from government incentives and collaborate with the Virtual Labs. A possible action plan to operationalize this Research Ecosystem Architecture is reported in Table 1. Virtual Lab Universities Research Labs Government Research Projects Public Agency R&D Incentives AI Instruments Science-BasedFund 24 GETTING IN TOUCH WITH THE EU In person All over the European Union there are hundreds of Europe Direct centres. You can find the address of the centre nearest you online (european-union.europa.eu/contact-eu/meet-us_en). On the phone or in writing Europe Direct is a service that answers your questions about the European Union. You can contact this service: — by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls), — at the following standard number: +32 22999696, — via the following form: european-union.europa.eu/contact-eu/write-us_en. FINDING INFORMATION ABOUT THE EU Online Information about the European Union in all the official languages of the EU is available on the Europa website (european-union.europa.eu). EU publications You can view or order EU publications at op.europa.eu/en/publications. Multiple copies of free publications can be obtained by contacting Europe Direct or your local documentation centre (european-union.europa.eu/contact-eu/meet-us_en). EU law and related documents For access to legal information from the EU, including all EU law since 1951 in all the official language versions, go to EUR-Lex (eurlex.europa.eu). Open data from the EU The portal data.europa.eu provides access to open datasets from the EU institutions, bodies and agencies. These can be downloaded and reused for free, for both commercial and non-commercial purposes. The portal also provides access to a wealth of datasets from European countries.