Funding Life-Extension Research

Abstract

While the worldwide trend in life expectancy continues to increase slightly overall, the trend for the last few decades in developed countries is that more people are spending more years in poor health with multiple chronic comorbidities. These chronic conditions in aging populations consume high proportions of national healthcare budgets. The relatively young field of longevity research, after accumulating insights into the mechanisms of aging and producing dramatic laboratory demonstrations of life extension in some organisms, is entering the translational phase. This phase, through clinical trials, will confirm or refute the “geroscience hypothesis” that drugs can change the trajectory of the processes of aging within cells, and ultimately in living humans. At the same time, traditional funding patterns do not favor such visionary “moonshot” research, which, despite the potential for ultimately providing benefits for everyone, offers little prospect for rapid return on investment and high probabilities for early phase failure. New radical funding strategies incentivizing innovation will have to be called into play.

For fully funding life-extension research, there is no current model. While the goal is surely a grand challenge, one whose achievement can impact every human in the world, it is far from certain that the incentives that fueled the funding of other great medical and technical victories, from the original moonshot to the COVID-19 vaccines, will line up to generate the heat necessary for attracting investors and philanthropic backers to this high-risk venture. The aim of extending healthy human life will need not just highly talented research scientists and clinicians, but also the best minds among risk-tolerant administrators, policymakers, ethicists, and institutions collaborating within entirely new frameworks. It will take a whole society approach. In what follows, we briefly survey serious impediments to success and novel approaches with promise for overcoming all obstacles. We also look at what some key thought leaders have recently contributed to the field.

The time is ripe. Ever since UC San Francisco biologist Cynthia Kenyon doubled a tiny worm's life span by altering a single gene in the 1990s, a newborn field of longevity research has been accumulating insights into the mechanisms of aging. These mechanisms, along with strategies for interdicting them, have arisen from genomics, proteomics, and machine learning and have led repeatedly to dramatic laboratory demonstrations of life extension in worms, mice, monkeys, and other organisms (STAT Reports 2022). The maturing field, now with dozens of companies engaged, is entering the translational phase with its requisite clinical trials. These trials are poised to confirm or refute the “geroscience hypothesis” that drugs can change the trajectory of the processes of aging within cells, and ultimately in living humans.

The rationale for aging as a target for therapies rather than the specific diseases that have been typically warred against by medical research, the STAT report on “The race for longevity” points out, emerges from important analyses. They show that over the last few decades the proportion of healthy years has remained fairly constant. More people are spending more years in poor health with multiple chronic comorbidities such as heart disease, stroke, diabetes, cancer, arthritis, and chronic obstructive pulmonary disease (COPD). The trend is consistent in developed nations, with estimates showing late-life morbidity consuming 16%–20% of people's lives and more than half of total health spending in the United States (in 2019, the 30% of the population over age 55 accounted for 56% of health spending). Baby boomer annual health care spending is projected to eat up 20% of the economy by 2027.

Basic research into the biologic processes of aging pulls down <1% of the National Institutes of Health (NIH) budget, however. But if it is the aging process itself that creates major vulnerabilities to various diseases, for example through increasingly damaged DNA repair mechanisms, a shift toward much greater spending targeting the breakdown of age-regulating pathways with drugs and other therapies is warranted. New therapies, for example, may be directed toward such targets as telomere attrition, cellular senescence, loss of proteostasis (accumulation of damaged proteins), deregulated nutrient sensing, mitochondrial dysfunction, stem cell exhaustion, and altered intercellular communication.

Putting a focus on the economics of longevity, professor of economics at London Business School Andrew J. Scott compared, in monetary terms, the gains from targeting aging itself compared to efforts to eradicate specific diseases (Scott et al. 2021). His analysis showed that a compression of morbidity that improves health is more valuable than further increases in healthy life expectancy. Scott and colleagues calculated the value of a slowdown in aging that increases life expectancy by 1 yr to be US$38 trillion. Expanding that to 10 yr, the value would be US$367 trillion. The authors noted, “The economic value of gains from targeting aging are large because delaying aging produces complementarities between health and longevity….” The gains in aging, they added, affect a large number of diseases because of the rising prevalence of age-related comorbidities, and create synergies arising from competing risks. “Ultimately, the more progress that is made in improving how we age, the greater the value of further improvements,” they concluded.

CURRENT “MOONSHOT” FUNDING MODELS

Complex “moonshots” (e.g., GPS, internet) have generally required mission-driven research models. Traditional government R&D funding has been excellent at moving basic and exploratory science forward. Likewise, industry, especially in developed countries such as the United States, United Kingdom, Europe, and Japan, have made tremendous contributions to bringing products and services to market by leveraging R&D that is nearly or already at translational stages. These countries have excelled at combining multiple technologies and discoveries to deliver products and services and platforms, for example, computer hardware and software, laboratory equipment, diagnostics, and therapeutics (COVID vaccines being the most recent). In the latter case, biotech and pharmaceutical companies leveraged fundamental virology R&D performed and/or funded by the U.S. government (DARPA/NIH, etc.).

With a grand mission that is at once very specific (the aging process), but also enormously broad and complex in terms of its many aspects, it is easy to see that unprecedented levels of coordination and collaboration that are multi-sectional, multi-institutional, and multinational will be called into play—for the research itself and its funding. Today's funding from government focuses fundamentally around individual researchers/scientists, especially those with an established track record. Among the unintended consequences of this funding pattern is relatively advanced age among government-funded researchers. In an NIH posting by Michael Lauer from 2021 (Lauer 2021), the mean age of NIH-funded researchers receiving support on a first NIH R01 award for Principal Investigators both for those self-identifying as men or as women increased from 40 yr in 1995 to 44 in 2020. For MDs, the mean age increased from 41 to 46 yr. With this trend, new entrants are selected against in the competition for funding and with them their potentially groundbreaking new and novel ideas and their perhaps nontraditional disciplines and approaches.

At the same time, the distribution of the vast majority of government funding is focused within the countries and regions providing the funds (e.g., NIH/NSF, Europe, United Kingdom, Japan, and, more recently, China and India). As a result, collaborations are limited and the ability to source the best ideas from around the world is curtailed, and some scientists, especially those early in their careers, are compelled to migrate to where the work is, hence causing local brain drain.

The private sector does provide significant R&D funding. In the United States, total private sector funding exceeds total government funding. As in the case of Airbus, funding can come from sources crossing national boundaries. This scope of funding belongs to late-stage, translational research related to specific products, services, and platforms, with the intent of maintaining market competitiveness.

Historically, there have been exceptions, for example, Bell Laboratories, and more recently, Google. They are few. Also rare is R&D conducted at pre-competitive stages aimed at furthering a field or solving an industry-wide challenge. When technical breakthroughs or first mover success does occur, the market becomes dominated by one or two players (e.g., software systems, social media, e-commerce, commercial aircraft manufacturers, etc.). In this manner, collaboration and pre-competitive sharing and R&D funding for commercial research are all further limited.

In theory, the Pharma and Biotech sectors could devise a way to legally share information or otherwise collaborate on the safety of therapeutics while still competing on efficacy. Sharing safety data, for example, could save time, energy, and resources with the effect of accelerating innovation and shortening the path to market. The result would be safer therapies, avoidance of unnecessary duplication of research, and avoidance of the worst-case instance of uncovering serious safety issues in the post-marketing period.

Nonprofit funding has remained relatively modest compared to public and private sources, and has been directed toward small-scale projects. While the Gates Foundation and Wellcome Trust do represent exceptions, their grants are often spread rather thin across too many fields and are not directed specifically toward grand challenges offering demonstrable scientific benefits. Nonprofits often have a sharper focus on a specific disease (e.g., diabetes, cystic fibrosis, rare diseases, and other conditions). Their missions may include important advocacy work or R&D devoid of commercial interest—although recently this has changed, with royalties or other commercial returns directed to the nonprofit itself. These changes, with their potential for conflicts of interest and mission primacy issues, are not without impact on the perceived roles of not-for-profit organizations.

GAME-CHANGING TECHNOLOGIES

The advent of highly sophisticated communications technologies that offer new dimensions for worldwide conferencing and collaborations is raising questions about the basic infrastructures of research. For example, consider R&D laboratories operated remotely via robotics, dispensing with the need for researchers to have in-house brick and mortar laboratories. When, as the metaverse develops, collaborations cross geographic regions and nations using laboratories “in the cloud,” how will they (the laboratories and the researchers) be funded? How will the collaborations be conducted and funded and how will the rewards be shared? A period of rapid change awaits us. Just as technologies are scaling and being democratized across the developing world, seemingly leapfrogging across developmental stages, so could R&D and academic research. Questions loom about training for acquiring the required skills that science demands—skills for design and analysis versus physically carrying out a specific methodology and conducting the experiments. Models for basic bench, preclinical, and clinical research will change, along with their funding. This journey has already started.

FUNDING COLLABORATIONS AND COMBINATIONS

Today, while governments, nonprofits, venture capital, and public markets all fund R&D, they tend to fund at usually distinct phases of the R&D continuum (i.e., Basic [biology] → Disease [pathophysiology] → Target → Preclinical → Clinical → Market). Investment is also necessary for the development of tools (e.g., molecular probes and biomarkers) and the creation of standards in parallel with the above stages. While institutions like the U.S. NIST (National Institutes of Standards and Technology) perform a critical role in standardizations and metrics, quite frequently development of molecular tools or biomarkers falls between the cracks. In the field of aging and geroscience, this remains a largely unmet need, one that remains mostly unfunded by any sector. Research at the clinical stage, at times, and especially with recent aging trials, does not fall neatly into the purview of any single government agency, as witnessed in the TAME (Targeting Aging with Metformin) trial debacle (see below). The private sector does not see itself as having a role here because investor expectations do not incentivize funding of clinical trials of inexpensive generics or even never-marketed, off-patent, or patent-expired molecules.

Funding policies and patterns will have to be revamped. Among the prominent needs:

• Remove barriers to combining sources of funding from different sectors.

• Incentivize multinational collaborations and funding.

• Invite new disciplines and younger scientists from both developed and developing countries.

• Disconnect, where appropriate, R&D funding from the teaching mission of institutions. More equitable, direct means of funding teaching need to be established.

• Global communications and remote laboratories can facilitate collaborations between senior scientists/faculty and junior scientists. Newly arising questions regarding intellectual property/ownership/authorship will have to be sorted out.

When the aspiration is on a “moonshot” scale with potential to be as disruptive as the creation of the internet or GPS technology, the challenge becomes one of funding an “open-source” approach while allowing competitors to engage in creation of in-market applications out of late-stage R&D. It is noteworthy that with the development of COVID vaccines, for example, Oxford and AstraZeneca saw their role as one of serving societal needs and agreed to zero-net profit/royalties.

Today we recognize and celebrate the “star/hero scientist,” and author of the first landmark published paper. In truth, frequently the data and breakthroughs cannot be reproduced or validated independently, often because of lack of funding or incentives to conduct such research. Furthermore, getting a validation study funded is difficult, as is getting one published in high-profile journals. This also inhibits progress.

Questions arise: Could a focused research organization (FRO) or ideally a network of FROs be created, funded, governed, and coordinated to move the field of aging forward? Could such a network be designed, managed, and funded across geographies and sectors, but still with minimal bureaucracy?

What role can prizes (like the $10 million Ansari XPrize) play in creating incentives toward innovation?

SUPPORTIVE/PRELIMINARY DATA

Today's funding often presupposes the existence of supportive/preliminary data, pushing investigators to generate data before getting funded (“use past grants to generate data for future applications”). The question then becomes, “How can we fund early-stage ideas, even without proof-of-concept data to generate and support early hypotheses?”

Could ARPA-H (Advanced Research Projects Agency-Health) be a model for this ecosystem or an ARPA-Aging model for funding the discovery/development/application/and implementation of research stages? Could it offer a model that answers the often-voiced concern of recent years in the scientific community that R&D funding processes have become too conservative, and in effect encourage only incremental advances in science and technology.

How then can high-risk, high-reward (HRHR) R&D be incentivized? The problem is inherent in the U.S. National Institutes of Health (NIH) HRHR definition. It states that such research tests “ideas that have the potential for high impact, but that may be too novel, span too diverse a range of disciplines, or be at a stage too early to fare well in the traditional peer review process” (Packalen and Bhattacharya 2018). A report published in 2021 (Machado 2021) exploring this question, “Quantitative indicators for high-risk/high-reward research,” identified four main categories of HRHR funding mechanisms:

1. Funding mechanisms specifically designed to support HRHR research and that are supporting such research as a primary goal.

2. Funding mechanisms that have HRHR research as their primary mission within a broader set of objectives.

3. Funding mechanisms in which supporting HRHR research is a secondary goal or an important consideration in the proposal evaluation process.

4. Funding mechanisms geared toward supporting scientific research with multiple possible goals including advancing scientific knowledge, achieving economic outcomes, or advancing societal outcomes, although there are no clear criteria for fostering HRHR research.

The main funding sectors are government, nonprofit/philanthropy, venture capital/financial markets, corporations, and prizes (e.g., the XPrize). For their engagement with HRHR research, key contextual factors and policies play an important role. Political support for risk-taking and commitment for the long term, for example, was found to be both the most important factor and the most challenging. Also, research institution tenure and promotion and advancement policies, powerful incentives for researchers (especially early-career ones), favor conservative research projects that are more likely to be accepted for publication. These institutions, to encourage HRHR research, will have to reconsider these human resource policies. To effect such changes, they will have to actively promote and favor consideration of a “riskiness” factor of a research project or portfolio. In addition, a specific revision of tenure and promotion practices in the direction of rewarding risk-taking and providing seed or bridge funding for HRHR research is needed. The “how” question, in this regard, does stand in sharp outline. The report did not identify a “one-size-fits-all” funding approach, but did state in no uncertain terms the consequences of ignoring the problem: “… failure to encourage and to support research on risky, ‘out-of-the-box’ ideas may jeopardize a country's longer-term ability to innovate and compete economically, to harness science toward solving national and global challenges, and to contribute to the progress of science as a whole.”

Another report, “Energizing and employing America for a brighter economic future” (National Research Council 2007), produced at the request of the U.S. Congress back in 2007, identified factors contributing to eroding U.S. competitiveness in the global economy, and named a decline in support for “high-risk or transformative research,” particularly in the physical sciences, engineering, mathematics, and information sciences. The trend, it said, increases the likelihood that breakthrough, “disruptive” technologies, the kinds of discoveries that yield huge returns, will not be found locally in the United States. Similar concerns have been articulated in Europe and Japan about their own research establishments.

Listing factors fostering R&D timidity, Machado's OECD report included the sense that because funding agencies spend public dollars, they need to show results promising societal benefit and technological breakthroughs. Also, scientific review panels, perceiving the same pressure, reward lower risk, higher certainty projects. Third, influential individuals or parties with vested interests may undermine avenues of original research.

What does constitute worthy HRHR research? Canada's New Frontiers in Research Fund (2018) program sought research that is interdisciplinary, international, fast breaking, and high risk, and looked for projects going in unique directions, challenging current paradigms, and deepening understanding of complex and challenging issues. Also, the program included bringing new disciplines together to solve existing problems and/or taking current frameworks, methods, and techniques and developing or adapting them.

The OECD report devised the following as a working HRHR definition: “High-risk, high-reward (HRHR) research is research that (1) strives to understand or support solutions to ambitious scientific, technological, or societal challenges; (2) strives to cross scientific, technological, or societal paradigms in a revolutionary way; (3) involves a high degree of novelty; and (4) carries a high risk of not realizing its full ambition as well as the potential for high, transformational impact on a scientific, technological, or societal challenge.”

The OECD report listed three categories of funding mechanisms, with the first being dedicated HRHR research programs with supporting HRHR research as their primary goal. These programs are in the minority, the OECD report authors noted, mentioning U.S. (Defense Advanced Research Projects Agency [DARPA]), French, and UK examples.

The second category program has, within a broader objective set, supported HRHR research as part of its primary mission. The U.S. National Science Foundation's RAISE program, for example, aims at supporting bold, interdisciplinary projects. RAISE requires two or more intellectually distinct disciplines to be incorporated within a research project.

With the third category of research funding mechanisms, supporting HRHR research is a secondary goal or an important consideration for the proposal's evaluators. Examples of this most common mechanism were from Europe, the United States, Ireland, Poland, and Norway, with Norway's ENERGIX program aimed at energy breakthroughs that may produce major leaps forward.

A potential fourth category of funding mechanism is geared toward supporting research with multiple possible goals (i.e., advancing scientific knowledge, achieving economic outcomes, or advancing societal outcomes). Here, also, researchers are encouraged to pursue high-risk or potentially transformative approaches.

NONGOVERNMENTAL FUNDING OF HRHR

Although the larger part of HRHR funding comes from governmental sources, other organizations and especially private foundations, because they are under fewer restrictions, can play an important role. They have more freedom in how they define their objectives and achieve them and fewer or less stringent financial accountability requirements. With more freedom, they may better tolerate risk and projects delving into unchartered territory. They may also choose to support specific scientists rather than specific projects, and may provide grants over a longer time period. The OECD report mentions Howard Hughes Medical Institute (HHMI) (www.hhmi.org) as a pioneer in placing “big bets” on people rather than projects. At the opposite pole, targeting ideas rather than people, the Danish Lundbeck Foundation has based some funding on anonymous proposals, forcing reviewers to focus on the project's apparent merit.

The strategy of presenting specific challenges and dangling financial prizes for their achievement has gained currency in recent years. In the United States, the practice, as a spur to innovation, gained congressional legislative support in 2010. One clear advantage, outside of the potential successes generated, is that government does not foot the bill for the “also rans.” They can still gain patents and commercially useful insights. Also, by specifying the desired result but not the way to get there, process innovation may be a valuable byproduct.

The OECD report specifically identifies DARPA, the XPrize Foundation, and Ireland's Future Innovator Prize as users of incentivizing prizes and as being HRHR research oriented. The last example represents a hybrid experiment, with first-stage winners getting a small grant, and later-stage winners getting larger ones.

The portfolio approach, which tries to balance high-risk and reliable financial return projects, has become attractive to program managers and policymakers. It strives to forestall the politically difficult situation of having a very high percentage of no-breakthrough projects by spreading the risk. It allows differing selection processes and, at the national/strategic level (or even multinational level), enables the acceptance of mission-oriented, higher risk use of public funding.

LONG-TERM STRATEGIC FUNDING

While the need to show tangible results works against patience and risk tolerance among government policymakers, there are notable examples of successful HRHR research. Among them in the United States, the National Science Foundation's funding for LIGO (the Laser Interferometer Gravitational Wave Observatory), two laser-based scientific facilities designed to verify the existence of the gravitational waves predicted by Albert Einstein about a century back. At the project onset in the late 1980s, gravitational wave detectors had not yet been designed and failure risks were substantial. The verification did not occur until 2015, and numerous threats to the project's funding in intervening years had to be overcome. International support for CERN's building and operation of the Large Hadron Collider (LHC) faced similar challenges; its discovery of the Higgs boson and the expanding of the understanding of the universe that both LIGO and LHC delivered justified the risk tolerance and patience.

These examples, however, are the exception. The OECD report authors devised a novelty indicator that quantifies the “riskiness” of a research project or portfolio and the level of knowledge of field combination in “more exploratory risky ways” in journal articles, allowing researchers, research managers, and others to adjust risk to an appropriate level. They found that in the years 2005–2017, more than half of all articles scored 0 or 1 for novelty, with few scoring very high (10 or higher). The countries with more articles scoring among the top 10% were the Netherlands, Switzerland, and Denmark followed by the United States and the United Kingdom. The analysis also showed that these countries were the ones scoring very high in terms of scientific impact measured through numbers of article citations. Also, from a long-term perspective, the novelty indicator is positively associated with citations. The overall citation performance of highly novel articles is not initially elevated, but it increases over time, often becoming substantially superior over longer time spans. For research project portfolios, inclusion of high novelty research can potentially help balance risk and reward. In the case of targeting and increasing healthy life spans, the potential return-on-investment (ROI) is massive, as Andrew J. Scott demonstrated.

Many worthy projects, stated Adam Marblestone et al. in a recent article in Nature (Marblestone et al. 2022), wither or fail to get launched because they do not fit neatly into categories attractive to venture capitalists, academic laboratories, or start-up firms—especially in the instance of projects that would create public goods, for example, data sets or tools valuable for making research faster and easier. “These engineering improvements do not fulfil teaching requirements or provide the papers or pizzazz that both senior academics and their trainees need to propel their careers.” Such midscale projects that enable research and are typically overlooked could be taken up by FROs with full-time scientists, engineers, and executives, and funding at the US$20–$100 million level over ∼5 yr. They would pursue definite milestones, such as improving by tenfold a measurement system or gathering pre-specified quantities of data. But unlike the grand, charismatic LHC at CERN, Human Cell Atlas, Hubble Space Telescope, or ENCODE (encyclopedia of DNA elements) in data collection, the FRO model would support a stream of smaller, easier-to-launch projects. First efforts have, as proposed products, high-throughput brain-mapping techniques, tools for engineering non-model microorganisms, and analysis of aging interventions in mice. In a few years, it will be clearer whether the FRO model accelerates neuroscience, synthetic biology, and longevity research in a manner similar to how Bell Labs, Xerox PARC, and other U.S. corporate laboratories merged fundamental research with large-scale product development (examples include laser printers, photovoltaic cells in solar panels, the programming language C++, transistors, etc.) in the second half of the twentieth century. More recently, Alphabet's subsidiary Google DeepMind developed an algorithm for predicting protein folding. Today, though, most industry laboratories cannot pursue projects for which near-term commercial objectives are not apparent. Those that do make sure that what they learn remains proprietary. We propose that funding precludes such secrecy, but with means devised to preserve commercial advantages for the research authors. Otherwise, as with proposed sharing of safety data among pharmaceutical researchers, efforts are duplicated and progress at the scientific community/national/global levels is slowed. Finding practical ways to democratize advancing knowledge and discoveries while incentivizing individual initiative needs priority consideration.

DARPA, held widely as an example of institutional innovation, identifies very specific technologic needs and assembles research groups to meet them. The U.S. government has created DARPA variants to address energy- (ARPA-E) and intelligence-related projects (IARPA).

Some research institutions are set up to take on government- or industry-sponsored applied engineering projects. SRI International in Menlo Park, CA, the Fraunhofer Society Institutes in Germany, and the European Innovation Council Accelerator are examples. Permanent institutes independent from academia such as the Allen Institute for Brain Science in Seattle, Washington, and the Janelia Research Campus (Ashburn, Virginia) of the Howard Hughes Medical Institute, through large-scale data collection, have developed broadly used tools. Similarly, the Allen Institute has established tools that are easily standardized for mapping gene expression in the mouse brain. The stated goal of Marblestone et al. is to develop a playbook model for FROs allowing them to get technologies or data sets deployed rapidly for use across the research community. They want to support an ecosystem of small- to midscale projects less suited for academia and other organizations. An FRO might develop a technology and demonstrate that independent laboratories can implement it. FROs use time-bound milestones and strong project management but are not bound to academic publishing.

In terms of structuring, Marblestone et al. suggest that semi-permanent project manager/administrator groups can be matched with scientific staff at the outset to create a focused scientific leadership team. Alternatives to academia's ladder or the potential financial rewards of start-ups will have to find their strong career progression models. Experience and experimentation will have to refine the FRO model. Marblestone et al. conclude, “We and others hope to develop the model to a point at which governments could set goals to fund a certain number of FROs each year, confident that, although some will fail, others will make research more powerful and efficient.”

A Science article published last year on the ARPA-H opportunities (Collins et al. 2021) often came to similar conclusions about bold research ideas that may fall through the cracks between the traditional NIH support for incremental, hypothesis-driven research and commercial support for return-on-investment-driven research. These traits may be seen as fatal to potential funders: too risky, too expensive, too time-consuming, too “applied,” calling for too much complex multiparty coordination, not enough near-term market opportunity, and too broad a scope. Further, bold ideas around creating platforms, capabilities, and resources helpful across research on many diseases do not attract the attention of potential funding sources.

The authors add that consideration of a project's impact on health ecosystem inequities is generally ignored in the private sector as well. Finding or creating the levers for funding the democratization of technologies for the benefit of all is a present challenge.

A WORD ABOUT FAILURE

The path necessary for coordinating multiple entities and individuals working toward a “moonshot”-type goal has to skirt along and sometimes across many institutional and even cultural boundaries. Nobility of purpose does not inoculate against all such obstacles that crop up along the way. The debacle experienced around the TAME trial of metformin stands out in sharp outline in the narrative of the previously cited STAT report (“The race for longevity”). When in the late 1990s serendipitous observations that cancers, heart attacks, dementia, and Alzheimer's disease were reduced in patients taking metformin, a safe and “dirt cheap” drug, versus those receiving other diabetes medications attracted serious attention among clinical researchers. Nir Barzilai, the Albert Einstein College Institute for Aging Research director, went into action. He had been interested in testing drugs to extend human “health span,” and metformin seemed to be an excellent candidate, good enough to attract, for the first time in history, a National Institutes of Aging grant to conduct a clinical trial that targets aging. The plan was to track 3000 elderly individuals over 5 yr to see whether metformin would forestall cardiovascular disease, cancer, cognitive decline, and mortality.

The biggest obstacle to Barzilai's plan appeared to be the FDA, because federal regulators at the FDA recognize only the “one disease, one drug” model for approvals. Aging, not being a disease, was precluded from FDA paths forward in clinical testing. But when Barzilai and a group of top-tier school academics met with the FDA, to everyone's considerable surprise, the agency agreed to the plan in 2015—leaving only the funding, $30–$50 million, to be addressed. But with metformin being a generic drug, pharmaceutical funding was ruled out. The NIH offered about $9 million to identify aging process biomarkers, but Barzilai's supposition that the rest would be granted by philanthropists and philanthropic organizations proved to be incorrect. And it has stayed incorrect for roughly the last 8 yr, despite the view by some that TAME could be paradigm shifting and create a biotech framework that could be followed into the future by others. While Barzilai still believes that TAME will happen “because it has to happen,” James Peyer, CEO of Cambrian Biopharma, called the TAME story “a particularly tragic one,” and noted, “It should almost be done by now.”

LEAPING PAST LIMITATIONS

Given the limitations on HRHR research funding imposed by commercial and political entities and academia, which groups have the freedom and means to, as Regina E. Dugan and Kaigham J. Gabriel put it in “Changing the business of breakthroughs” (Dugan and Gabriel 2022) “… take an unconventional and optimistic view of what's possible in order to act on behalf of future generations?” Who can see beyond borders, disciplines, and barriers and change the way science is done (and funded)? At this time, according to Dugan and Gabriel, it is independent philanthropy that can drive a network of diverse contributors toward a common goal and that can create the necessary structures while deploying and synchronizing resources. “… [I]ndependent philanthropy can step into this void. And at a time when humanity is in urgent need of action, philanthropy can act quickly, without concern for election cycles or the lengthy process of realigning political will and global economic incentive structures.” Pointing to the recent example of the development of the mRNA vaccines and of the culture fostered by DARPA, they urge that visionary programs with goals greater than any one individual and aimed at breakthroughs need to move quickly, generate a sense of momentum, and have the agility to create cross-discipline collaboration and a unity that pushes past obstacles. While DARPA was designed to serve U.S. strategic interests, Dugan and Gabriel are certain that its model can be adjusted in the service of increasing the number and pace of revolutionary breakthroughs around global challenges. For that, national boundaries, distinctions around basic versus applied research, life sciences versus physical sciences, and perhaps, most critically, between public versus private funding have to be dissolved in the service of a higher good. At the same time, progress toward clearly defined goals must be testable and measurable.

Dugan and Gabriel hold out as an example their organization's (Wellcome Leap) model. Wellcome Leap is a new entity established in 2020 to tackle huge global challenges in health. It hires experienced leadership teams with a mandate to “stack the odds in favor of breakthroughs.” To build a sense of urgency and team momentum, it uses a master funding agreement that allows funding of individuals in days or weeks instead of months or a year. Not requiring a consensus process for evaluating proposals helps create more diverse teams of early- and late-career researchers from diverse quarters—a method that elevates young investigators. Further, the use of contracts rather than grants favors risk tolerance. Staged decision-making regarding going forward allows off-ramps for unproductive lines of work.

The question they are most often asked, Dugan and Gabriel note, is about how they choose programs. Citing Donald Stokes’ Pasteur's Quadrant (Stokes 1997), they choose “use-inspired research”—research that is mission-driven—aimed at new capabilities or specific problems. It calls for advancement of science to create new solutions, and avoids pure curiosity-driven basic science that lacks a target application.

As we look to the future, AI, neural networks, machine learning, and evolution of the metaverse will require large learning data sets. It will require especially those data sets linking molecular laboratory data to phenotypic data from real-world, large, and diverse populations in their “living” environments if we are to understand and intervene in aging.

CONCLUDING REMARKS

Funding will have to come from a combination of government, private, and likely nonprofit sources collaborating in complementary areas. Ownership, the need for a focus on the common good, ethics, inclusivity, and the remediation of inequities all count as critical issues demanding that attention be directed to them proactively. These are key links to funding that successfully attain the scale and duration that this grand vision will inevitably demand.

THE NEED FOR TRUST

Finally, consumer and citizen perception is an increasingly important aspect that all stakeholders, including funding agencies from all sectors, will have to address if science—especially the field of aging/geroscience—is to have a societal license to operate. We need the trust of society.