Fragmentation in Longevity Funding and Investment | The Longevity Equation – Chapter 2

Longevity, and its more clinically grounded sibling, healthspan, have moved from niche scientific ambitions to a crowded, high-stakes ecosystem. Capital in interventions and infrastructure that aim to extend healthy years of life is flowing in, but unevenly. According to Pitchbook data, in 2024, global healthspan investment rebounded sharply to about $7.3B after a dip in 2023, with deal sizes getting larger as later-stage assets attracted more institutional money [1]. However, the same datasets show thin early-stage activity, and widening gaps between grant-funded discovery and capital-intensive clinical translation.

This unevenness is what fragmentation looks like in practice. It is a landscape with many motivated actors, but their incentives do not align. Standards are inconsistent and projects repeatedly fail at the handoffs between stages, creating classic valleys of death. The result is tangible. We witness an environment where the biology is exciting but early stage innovations remain underfunded, translation is slow, consumer-facing offerings often outrun the evidence, and too few interventions become scalable, reimbursable, and clinically validated.

This article maps (1) the players, (2) how fragmentation manifests, and (3) quick, possible solutions to reduce fragmentation, without requiring everyone to agree on a single definition of “longevity.”

Public funders support longevity/healthspan for three main reasons: (i) aging populations increase chronic disease burden and costs; (ii) prevention and functional independence have major productivity and care-economy implications; and (iii) foundational biomedical science creates benefits that extend across many disease areas.

The U.S. National Institute on Aging (NIA) is a central anchor for aging biology and age-related disease research. Its budget documentation provides a concrete view of public investment capacity and constraints [2,3]. Meanwhile, the U.S. has also created new funding mechanisms designed to support “high-impact” biomedical breakthroughs, including ARPA-H, funded separately from NIH in appropriations [4,5].

Globally, the World Health Organization’s UN Decade of Healthy Ageing (2021-2030) formalizes healthy aging as a multi-stakeholder priority, a useful context for why governments and multilaterals increasingly view “healthspan” as infrastructure, not a niche [6].

Who receives public funding? Mostly:

Philanthropy is often the first money into uncertain science especially where timelines are long and endpoints unclear, playing a central role in de-risking opportunities while extracting the highest reward for a return on value. It can also act as “ecosystem glue” by paying for shared infrastructure that benefits everyone but is hard for any single company to justify funding alone. This may include long-term human cohorts, shared biobanks of biological samples linked to clinical data, and common measurement standards so studies can be compared and results can be validated.

Strong examples of philanthropic organizations supporting the longevity and healthspan ecosystem include the Longevity Science Foundation (LSF), Lifespan Research Institute (LRI), and the Hevolution Foundation. The LSF is a US based 501(c)(3) nonprofit focused on funding research to extend the healthy human lifespan in three key areas: preventing chronic and age-related disease, the fundamental biology of aging science, and traditionally underrepresented populations in healthcare. The LSF’s funding thesis has an emphasis on early-stage work that is oftentimes too early for traditional venture financing, accelerating the innovation cycle before handing off funding to commercial entities [7]. The LRI is also a 501(c)(3) nonprofit and positions itself as an ecosystem builder that supports cutting-edge research into the root causes of aging alongside advocacy and community-building to accelerate translation and adoption of longevity science [8]. In parallel, Hevolution, a nonprofit based out of Saudi Arabia, has positioned itself as a major philanthropic backer of healthspan science, reporting over $400 million committed/allocated within roughly the past two to three years across grants, partnerships, and impact investments [1].

Prizes can also reduce fragmentation by forcing alignment on measurable outcomes. The $101M XPRIZE Healthspan explicitly aims to incentivize teams to demonstrate improvement in key functional domains (muscle, cognition, and immunity) and help create regulatory credibility through results that are hard to ignore [9].

Who receives philanthropic funding?

In emerging science, private capital concentrates where (i) value can be marked up quickly (platform narratives, AI + biology), or (ii) a visible path to a high-value exit exists (late-stage therapeutics, disease-adjacent indications).

A McKinsey analysis of the healthspan science field highlights that it disproportionately attracts high-risk investors (VC and HNWIs) and that the mix differs from mature therapeutic areas like oncology, partly because regulatory and commercial pathways are less established [10].

From an investment-by-stage view, the ecosystem looks “barbelled”: later-stage VC, PIPEs, secondary offerings, and revived private equity contribute a large share of total financing, while early-stage VC activity can be low or even declining year-over-year [1].

Who receives VC/HNWI funding?

Large pharma and strategic healthcare investment companies can fund late-stage trials and global commercialization, however they typically expect key uncertainties to be resolved first, including: clearer regulatory precedent, validated clinical endpoints, well-defined patient populations, and strong intellectual property alongside practical considerations like manufacturability and scalable production. McKinsey notes that unclear regulatory and commercial pathways have contributed to lower participation by traditional life-sciences investors and pharma compared with more mature ecosystems. They also argue that blended models, pairing philanthropy/healthspan-focused VCs with established pharma and blue-chip investors, could de-risk and scale the field [10].

At the same time, some corporate-backed players deliberately operate upstream to generate that missing de-risking evidence. Calico and Altos Lab are good examples of these hybrid corporate R&D actors. Through collaborations, they have funded and supported external research “from basic biology to potential therapies,” and they have pursued early-stage discovery partnerships with institutions like the Buck Institute and the Broad Institute focused on aging biology and early-stage drug discovery [11-12].

Who receives pharma capital?

In practice, the funding map is far less balanced than the role-based picture suggests. A disproportionate share of capital concentrates in later-stage and “near-clinic” assets, while early translational work such as seed-to-Series A, validation, and first-in-human readiness, remains comparatively thinly funded, creating fragile handoffs from lab to clinic [1]. These gaps are amplified by geography, with the U.S. capturing the lion’s share of deal volume and deeper scale-up capital, which shapes where companies form and where they can realistically finance long, expensive clinical translation [14-16].

Fragmentation shows up first as geographic discontinuity, because the ability to fund and execute the journey from lab to clinic depends heavily on where a project is based.

In the Investment Report 2024 published by Longevity.Technology, the U.S. is the clear center of gravity, with 57% of longevity companies and 84% of total deal volume; Europe is the second hub with ~17% of companies but only ~10% of deals, while Asia accounts for ~9% of companies yet only ~2% of deals, a pattern that helps explain why many teams still look to U.S. capital markets to survive expensive clinical translation [14]. The divergence is grounded in structural finance mechanics: multiple European policy and innovation analyses describe a pronounced late-stage/scale-up funding gap versus the U.S., which makes long timelines and capital-intensive clinical programs harder to finance through to maturity [15,16]. Asia-Pacific is better described as heterogeneous rather than uniformly sceptical. In fact, regional ecosystems (e.g., Singapore, Japan, China, South Korea, India) are active, but the share of global longevity deal volume remains small in this dataset. For example, Singapore has hosted the Founders Longevity Forum in collaboration with NUS Medicine’s Academy for Healthy Longevity, explicitly aimed at building an APAC longevity investment and research community [17,18]. Meanwhile, the Middle East is becoming a visible momentum hub through a mix of mission-driven capital and high-profile ecosystem building. Saudi Arabia has positioned “healthspan” as a strategic priority and hosts the Global Healthspan Summit as a recurring global convening platform, while Abu Dhabi has elevated longevity on the policy agenda through initiatives like the Declaration on Longevity and Precision Medicine at Abu Dhabi Global Health Week, and Dubai has increasingly served as an international convening point where longevity themes show up in major global summits [19-21].

Seen this way, fragmentation is not just “too many players,” it is a problem of broken continuity that geography can deepen or soften. Each stage of the translational and commercialization pathway for a longevity or healthspan project tends to optimize for its own incentives, timelines, and success metrics. Real healthspan innovation requires a single coherent path that carries it from hypothesis to validated mechanism, to a measurable endpoint, to an approvable claim, and finally to reimbursable deployment. Translational science has a name for what happens when that continuity fails: the “valley of death”, where promising discoveries stall because the work needed to turn them into real-world interventions becomes too expensive, operationally complex, or hard to fund with the tools of basic research alone [13]. Against this backdrop, longevity and healthspan projects often face not one valley of death but several, stacked across the lifecycle.

Early discovery has an established funding pathway through public agencies and philanthropy, but aging biology remains materially underfunded relative to the scale of the problem. For context, in the NIA’s FY2025 President’s Budget, the “core aging biology” is budgeted at ~$346M which is roughly 8% of the NIA's total $4.425B budget, with the remainder spanning largely dementia-focused neuroscience [22].

That imbalance matters because it leaves fewer resources for the foundational, cross-cutting work that generates robust, human-relevant mechanisms and measurements. As a result, the first continuity break happens immediately after discovery, when many plausible targets emerge but only a small fraction mature into translationally credible packages that investors and clinical partners can rely on.

A core constraint is that aging is not one disease, it is heterogeneous and multi-system, shaped by genetics and environment, so the “works in a lab model” often does not mean “works in humans” [23]. This challenge is compounded by the broader reality that preclinical findings frequently fail in clinical development, commonly due to lack of efficacy and unexpected toxicity that only appears in humans.

A second bottleneck is data. Longitudinal human cohorts and biospecimens are limited or siloed, yet they are exactly what is needed to validate biological-age biomarkers prospectively across populations and outcomes, which makes validation slower and harder to finance than discovery [24,25].

McKinsey frames this as a field-level constraint, emphasizing the need for richer longitudinal human data and better integration of genetic, phenotypic, environmental, and digital measures to make aging cohorts interpretable and actionable [10].

This is where longevity and healthspan often underperform relative to the hype. Discovery can produce compelling mechanisms and biomarker signals, but the next step demands a different kind of asset: a decision-grade translational package that can survive scrutiny from regulators, clinicians, and investors. This is the classic “valley of death,” the zone where work becomes too applied for most academic funding while still too risky and operationally complex for many commercial funders .

The financing data reflects that brittleness. The 2025 Hevolution report notes that while the field is maturing and later-stage deals are growing, early-stage VC check-writing has slowed, with fewer seed and Series A financings, making the lab-to-market transition “more urgent than ever” [1]. In practice, capital is most available once something looks “near-clinic,” and many teams use disease framing to enter established trial and approval pathways, since aging itself is not a straightforward regulatory indication [26,27].

What breaks is predictable. Early-stage investors hesitate when timelines are long and endpoints are unclear, and teams struggle to price the risk-benefit balance [28,29]. The visible symptom is a glut of persuasive platform narratives and biomarker claims, but fewer programs that connect mechanism, validated measurement, and a clear clinical strategy into a package sturdy enough to reach first-in-human studies and beyond.

Regulatory discussions repeatedly note that aging is often treated as a natural process rather than a disease category, complicating approval strategies for interventions that target aging mechanisms broadly [30]. Aging itself is not a standard drug indication. That matters because drug development is built around indication-specific approvals.

The NIA has published guidance-oriented information on how the FDA reviews geroscience-related IND applications, emphasizing issues like defining indication/context of use and balancing risk-benefit given population heterogeneity [31].

McKinsey argues that the absence of established regulatory reference cases is a key barrier and suggests exploring novel endpoints such as intrinsic capacity or infection resilience, and/or aligning development within established therapeutic areas first [10].

As a result, programs oscillate between “anti-aging” positioning and disease-specific positioning, often changing their story depending on the audience (VC vs regulator vs payer).

Even when something works biologically, the next bottleneck is payment.

Prevention and function-preservation often pay off over years, but many commercial insurers and employer plans operate with meaningful member turnover, which weakens the incentive to invest in interventions whose savings may accrue after the patient has switched plans. This effect is documented both in empirical work showing that insurer turnover is associated with lower use of preventive services [32] and in more recent evidence that churn (disenrollment and reenrollment) is common in U.S. commercial coverage [33].

The problem is reinforced by standard health-economic practices that discount future benefits, systematically making long-horizon prevention look less attractive in near-term budget cycles [34].

As a result, when reimbursement pathways and widely adopted clinical guidelines are missing, adoption tends to default to out-of-pocket markets, where affluent early adopters can pay for intensive diagnostics and “longevity medicine” packages [35,36]. Meanwhile, the broader population, including those with the highest burden of chronic disease and the least ability to pay upfront, is largely excluded from access, reinforcing a two-tier system where the people who could benefit most are the last to receive evidence-based prevention and function-preserving care.

This is where the “parallel economy” becomes destabilizing: consumer clinics and subscription testing can scale quickly, but evidence standards vary and critics warn about overdiagnosis, unnecessary interventions, and uneven quality, which can create reputational spillover that complicates serious therapeutic and payer-facing translation. The fragmentation symptom is therefore predictable: rapid commercialization in services and testing, alongside slow, uneven integration into mainstream care and population-health financing [37,38].

The fastest way to reduce fragmentation is to build continuity across stages so that evidence, data, and decisions can travel reliably from discovery to translation to clinical adoption. In practice, that means making results comparable, making handoffs investable, and incentivizing the generation of credible, real-world learning rather than isolated anecdotes.

Stage A: Discovery (academia, early tool-building). The solution is to turn scattered science into comparable evidence, lowering the cost of diligence for every downstream investor. When measurements, cohorts, and outcome definitions become more interoperable, promising biology stops being “interesting” and starts becoming legible as a translational opportunity [6,10].

Stage B: Translation (proof-of-concept, preclinical packages, seed formation). The solution is to replace ad hoc handoffs with dedicated bridge infrastructure and catalytic capital that neutralizes the valley of death. Translation fails less because ideas are bad and more because the work needed to de-risk them is expensive, operationally complex, and hard to finance with either traditional grants or traditional ventures [39].

Stage C: Early clinical (Phase 1/2, endpoint validation). The solution is to align early with regulators and generate interpretable evidence efficiently, so programs do not stall on unclear endpoints or populations. In geroscience, where interventions may affect multiple age-related pathways, early regulatory clarity about context of use and study design reduces expensive rework later [40].

Stage D: Late clinical and commercialization (Phase 3, approval, reimbursement). The solution is to connect clinical truth to financial truth by pairing approval pathways with reimbursement logic and real-world evidence generation. Healthspan value often shows up as fewer complications, delayed disability, and better function over time, which can be under-credited in short-term decision cycles [41].

Conclusion: fragmentation is fixable, if we treat “healthspan” as infrastructure

Although underfunded compared to other sectors (biotech, oncology, climate tech) [1] the longevity ecosystem is not short on capital or ambition. The problem is stage-to-stage discontinuity: early science remains underfunded, and what is supported inconsistently evolves into translational packages; early clinical validation doesn’t reliably become approvable claims; and even good interventions struggle to become reimbursed, scalable care.

The encouraging news is that multiple credible actors are already building the missing connective tissue:

Reducing fragmentation requires shared endpoints, shared datasets, bridge capital, early regulatory alignment, and reimbursement pathways that reward function and prevention. If those connective pieces mature, the field can transition from a fragmented set of bets into a compounding innovation engine, one that produces both credible therapeutics and scalable prevention.