Table of contents for this page:
Chronic diseases of aging have over the past century taken over from infectious diseases as the predominant causes of death and suffering. The science of aging has shown over the past few decades that certain slow biological changes collectively underlie most (if not all) chronic diseases. This section has 3 main points: The science of understanding aging and biotechnologies to slow or reverse it (1) are more advanced than most people realize, (2) are more imperative humanitarian goals than is widely appreciated, and (3) will be more lucrative as investments than the majority of investors yet recognize.
After millenia of “fountain of youth” snake-oil, hard science has started making real progress against aging. The scientific consensus that aging can be interfered with is now widespread, based on decades of good science. While there are still controversies within the field, some incontrovertible basic facts are now widely agreed and no longer in doubt:
Just some of the respected sources one can consult for more on the above points:
Sarah Constantin’s Why Solve Aging analysis suggests that “Aging research could be comparable or superior in cost-effectiveness to the most cost-effective global health interventions.” This is but one of many arguments attempting to use the techniques of effective altruism to compare different worthy pursuits quantitatively, based on lives saved, or based on DALYs (Disability-Adjusted Life Years) or QALYs (Quality-Adjusted Life Years). Another from Alex Zhavaronkov was published by Forbes. There are others.
There have also been many comparisons between putting resources into anti-aging vs. cures for top-killer diseases, usually in terms of changes to life expectancy. These usually favor targeting aging itself. As just one of several examples:
Stats to put the deaths caused by aging in perspectives:
71% of the ~56Million deaths/year worldwide (~40M deaths/yr, or over 100,000/day) are caused by non-communicable diseases, mostly caused by aging. (Source: https://www.cidresearch.org/blog/which-diseases-cause-the-most-deaths but this page may be gone now---to do: replace with more up-to-date link & stats. Suggestions welcomed.)
For comparison, autonomous vehicles might end only 1.3M deaths/yr from road accidents, and stopping malaria would prevent only 0.4-0.5M deaths/yr.
For the USA, aging causes an even higher % of all deaths: 92% or 2.5M/yr (source: Cell, 2017, "Business of anti-aging science").
Also of interest: “A one-year increase in longevity, for example, has the same effect on national happiness as a 4.3% increase in GDP.” (From the work of Daniel Sgroi of the University of Warwick and Eugenio Proto of the University of Glasgow, both in Britain.)
It should also be noted that common objections to reducing aging do not stand up to careful analysis, simple logic, & basic morals, as summarized in this site’s Objections (and counterarguments) table.
[2024 update: Since this section was originally written in 2019, the consensus within the field has gotten even stronger on the point of this section & the prior one. An example of this is the Dublin Longevity Declaration, now signed by thousands of people including hundreds of experts working in the field, including many of the people at the very top of the field.]
Many people have started arguing in recent years that investing in the commercialization of aging biotechnologies will be an investment boom, much like the internet boom.
Jim Mellon helped lead the charge of these arguments with a keynote talk at the Master Investor conference in 2017 and the follow-up publication of his book Juvenescence: Investing in the age of longevity.
CBInsights released a 2018 report on the future of aging showing sharp increases in funding for aging companies in recent years.
Bank of America said in 2019 that “One of the biggest investment opportunities over the next decade will be in companies working to delay human death, a market expected to be worth at least $600 billion by 2025.”
While not specifically addressing the investment prospects, it is also notable that other big financial institutions are begging to discuss the implications of the potential for greatly expanded lifespans with their clients. As a notable example, Barclay’s Private Bank released a whitepaper in 2018 called Beyond 100.
The aging/longevity field (the understanding of the slow molecular changes that underpin aging, and how to interfere with them) is currently a small part of the overall medical/healthcare/biotech spaces, but the efficiency of targeting the underlying causes of multiple diseases will rapidly cause aging to grow to become a much larger portion of biotech, medicine, & healthcare.
The aging/longevity field has recently grown to the point where it is difficult to follow important developments, even for insiders. There are books, journals, and blogs, but these consist mostly of flowing prose text. There are few sources of structured information to refer to for broader context or to consult for targeted inquiries, particularly few focused narrowly on aging defined as the underlying molecular causes of multiple age-related diseases (operationalized here as described in the next section of this page).
As an especially important example, the internet previously had no reasonably comprehensive and precise list of companies with therapies or diagnostics for underlying aging in the above sense. For a comparison of this site’s list of aging companies vs others around the web, with direct links to these others, see the “Other lists of aging companies” sub-sheet/tab of the Companies table. [In 2019 none of the other lists had even fully ⅕ of the total companies in the field.]
This site provides concise, structured information about the aging/longevity field in the form of tables that are interactive (sortable & filterable) to provide info quickly and to provide broad perspective. A big computer screen makes the tables better. Interactivity (e.g., sorting) doesn’t work on mobile browsers on last check.
All info on this website is public information. Extensive links are provided to sources so up-to-date info on any specifics can be checked with a simple click, as can further details. Information content & functionality have been prioritized over look & feel and typical flashy modern website design. This will be a living site with ongoing updates.
For maximum trust, this site is not only non-profit but strictly non-commercial. Nothing is being sold. There are no sponsorships or affiliate links. No money is received by the maintainer(s) of the site for listings or preferential treatment. There are no subscriptions & nor a Patreon account. (All similar to Wikipedia in these aspects.) Furthermore, no financial donations are accepted. The site is a fully pro-bono effort with hosting paid for by the site creator. The site is for the good of the community, ecosystem, & wider public.
This site was created by and is currently maintained by:
Disclosure Statement: I am an investor in several companies tracked by this website. I am listed in the investorsXcompanies table & that table shows all the companies on this website that I’ve invested in. For full transparency, the list of all my investments, including the minority not tracked by this website, is maintained on my LinkedIn profile. The goal of this website, however, is to be a public good: to collect, synthesize, & summarize objective, unbiased, public information already openly available on the internet. I keep my investing activities completely independent of maintenance of this site. Companies that I have invested in get no preferential treatment here (and in fact some don’t qualify for inclusion on this site based on the criteria described in the next section, which is why some aren’t included in the investorsXcompanies table). And no non-public information that I see or hear gets included on this site until it is publicly available (and links to the source can be included).
This site grew out of my desire to have this information both for my own personal interest and as part of my investing work. Whereas many investors maintain private repositories of some of this kind of info as part of their work, I decided that making a public one was more important than optimizing a private version.
Short answer: A primary (and explicitly stated) focus on aging/longevity/rejuvenation, or a focus on or therapeutic approach capable of addressing a fundamental aspect (sub-area such as Hallmark or SENS damage type) of aging that should therefore be relevant to multiple age-related pathologies.
This section attempts to specify simple, objective criteria for determining whether something (e.g., a company) is part of the biotech sub-field of aging / longevity / biogerontology / geroscience / rejuvenation: the field concerned with understanding and measuring, diagnosing, slowing, treating, or reversing aging & its consequent pathology.
This site excludes palliative efforts to adapt to or compensate for (in a quality of life manner) the underlying biological changes of aging without interfering with the underlying aging itself. (So to use some common phrases, “Age tech”, aging well/gracefully, etc. are out of scope for this site. Here the goal is aging less or undoing it.)
We include as aging anything (eg, any company) that:
Ideally, both of the above should be true, and perhaps future versions of these criteria will change the above ‘or’ to an ‘and’, but for now the default is to include both things that clearly have age-impacting (or measuring) biotechnology even if the outward appearance of their motivation is not aging, and also things (eg, companies) that claim that aging is a key part of the mission, even if it is not possible to judge whether what they are doing really has that potential. In other words, secretive startups that have not yet provided enough details to know what they are doing will be included based on their external messaging until the details become clear. But if most of what a company does is clear and is not aging, then simply self-claiming aging as a focus will not suffice---i.e., claims used to justify inclusion based on point #1 above must at least be credible. (And a stated desire to go after broader aging things at some vague future date does not count if it is clear that the main current activities represent a single-disease or non-aging focus that will dominate the majority effort for the foreseeable future.)
[2024 update: In the future, this may be expanded into a few separate questions: The 2 items numbered above, plus (3) programs or stated intents to address multiple age-related diseases, & (4) presence at core conferences in the field (those listed in the conference table of this site).]
Some areas of biology that are clearly core aging and underlie multiple age-related diseases include senescent cells, mitochondrial health, nutrient/metabolic pathways/signaling (mTOR, AMPK, IGF1, etc.), proteostasis, and epigenetics. If any of these is the core focus, then most likely it qualifies as aging.
Cosmetic companies that use the words aging or rejuvenation to mean making skin look younger do not count if their use of these terms denotes only appearance rather than underlying state of health & they don’t tie the biology back to known aspects of aging.
Big pharma companies do not qualify just from having multiple product lines that treat different age-related diseases, nor even if they have a few lines of work capable of treating an underlying aspect of aging as long as the vast majority of what they currently do is not aging focused.
LifeExtension (lifeextension.com), whose very name suggests an aging focus, which was founded with the desire to do something about aging, and whose founder is involved in the field, nonetheless is excluded because the majority of its business is to sell supplements that have little to do with aging (even if a small % of these are products of aging companies and a small % are important for aging).
Companies with a treatment (or diagnostic) for a single age-related disease do not count if their platform is unlikely to subsequently generate treatments (or diagnostics) for other age-related diseases. A company focused initially only on a single rare disease to get through FDA trials can count if its therapeutic or platform is likely to ameliorate multiple age-related diseases (via subsequent leads and/or via off-label use of, or label expansion of, its narrower regulatory success).
Many examples of things that do and qualify can be found in the tables on the site themselves, especially the companies table. Examples of things that don’t qualify can be found in the subsheets of many of the tables. Most of the small tables have a “scope” subsheet explaining what is in vs out based vaguely on these criteria. The big companies tables has a “peripherally aging” subsheet describing companies that seemed close to qualifying but not quite actually qualifying, for reasons usually explained in the notes column. Close calls that are included in the main list also usually have comments on the decision in the notes column.
A company focused on cancer(s) but no other age-related conditions is excluded for practical reasons since oncology is an entire large subfield of biotech in its own right. There are too many cancer-focused companies to make the inclusion of such companies practical, or useful when analyzing the aging space. They would dominate a list meant to be specific to aging (at least in 2019-2020, the first years of existence for this site).
Some within the aging field argue that the brain is special. Some further argue that Alzheimer’s disease (AD) as the most common dementia should be considered special too. But the number of AD companies is exploding. By default we will still exclude any AD companies whose approaches don’t seem capable of also expanding at least to other neurodegenerative diseases. But there is something to the argument that the brain is special, and there are core aspects of aging that seem to impact multiple neurodegenerative diseases. Thus, we will include companies whose platforms can address multiple age-related neuro/brain diseases even if their focus doesn’t really help with the aging of the rest of the body. We will call these out in a separate category as aging but “only brain” (really meaning neuro or CSF) so that they can be easily filtered if desired. In some cases, judging whether a single dementia focused company has an approach that is capable of generalizing to other neurodegenerative diseases will be a judgment call.
Regenerative medicine is often categorized as its own category distinct from aging, but most regenerated or bioprinted tissues/organs are biologically young, and stem cell therapies (typically categorized as regenerative) are known to affect core aging pathways and transcriptional reprogramming via signaling without any “regenerative” (in the sense of generating new replacement tissue) effects. So unlike the division between the cancer (oncology) industry and the aging space, the line between the regenerative medicine (stem cells, etc.) industry and the aging space is much more blurred. Thus, by default regenerative medicine approaches are included as aging.
3D bioprinting is perhaps the sub-part of regenerative medicine farthest from core aging approaching and arguably bioprinting tissue & organs as replacement parts are quite far from being a whole-body anti-aging strategy since it would require that field to advance to handle all parts of the body. 3D bioprinting is currently excluded for the above reason combined with the fact that the technology and science are quite distinct from most of what the rest of the aging field is doing and thus including them would require more work and result in companies doing technologically even more extremely different things. Expanding the criteria to include bioprinting is a potential expansion for the future.
[2022 update:] Some stem cell and related regenerative medicine companies are a bit of a wild west at the moment, especially in terms of end-patient focused clinics. The site currently (as of 2022) does not comprehensively include everything that would be seen as regenerative medicine. The regen med community & aging/longevity community overlap a great deal but aren’t exactly the same. More comprehensively including regen med area stuff is a clear area for further work.
Feedback especially welcomed on these issues.
Questionable category: Companies with technology that could almost immediately be targeted at an underlying aspect of aging, but who are not currently focused on such a goal.
Questionable category: Should tools & services companies that aren’t developing their own therapeutics be included? Default: if the clients of the company are primarily researchers and other companies who are in turn primarily doing aging, then include, but this is rare. If the clients are primarily broader (drug development more broadly, human health or diseases broadly, etc.) then exclude. For example, a methylation clock company selling its aging-specific biomarker should be included, but a company developing biomarkers or software for general health improvement should not. Nemalife & Vium provide an interesting contrasting example-pair on this issue, with Nemalife’s worm-automation platform primarily useful specifically for aging-related studies and Vium’s mouse-automation having a much broader customer-base (eg, aging was listed as 1 of 6 areas on its website). Nemalife is currently on the main list, and Vium is on the subsheet of peripheral companies.
It’s worth noting that commercial success for the field of aging will likely lead to many aging companies being acquired by broader not-aging-focused companies that would normally not be in-scope for inclusion on this site’s company list. This has not started to happen much yet, but arguably the acquisition of Blue Rock Therapeutics by Bayer in 2019 is an early example. It is difficult to track subparts of companies in many ways, which is why this site did not attempt to include companies that have aging related efforts as a small minority of their work. Acquired companies often maintain their own separate corporate existence, website, executive team, etc. (as is still the case for Blue Rock as of 2022) so we will be able to continue to provide some info over time in such cases and things like the clinical trials columns will still be useful. Employee counts can still be broken out in some cases via LinkedIn. But other information and aggregate counts will not be able to take acquired companies into account. For example, aggregate market cap numbers for the field will undercount due to not including acquired company value. [2022 update: There is now an acquired tab in the companies sheet that lists companies whose separate existence cannot be tracked post acquisition, e.g. because the website of the acquired company is no longer maintained as a separate site.]
There are other ways to track the field besides just lists of companies and this site will start including other tables eventually too. [2022 update: This is now done with many tables now on the site including books, blogs, conferences, podcasts, available diagnostics, etc. But more are coming, such as nonprofits & investors.]
Some of this document is specific to the Aging Companies table, but much of it also applies to any other table on the site, and to Google Sheets in general.
The companies table is meant to encompass as many as possible (approaching all) of the companies in the aging/longevity biotech field. The criteria for inclusion in the table are described above. Some other column headers are also links to more detailed info about those columns.
All the info is intended to be public info sourced from existing public web pages that are not behind paywalls or memberships nor require any kind of special access. No info here should be confidential nor sourced from conversations or similar unverifiable sources. If a company wants a particular piece of information included, it should make sure that info is on its website or on the appropriate other normal public site. Companies should feel free to reach out with any information they think should be included along with links on where to find that info.
Some of the data is incompletely filled in. Not all companies that have successfully raised money have left evidence of the raise on the web. Employee counts sourced from LinkedIn are not precise. Etc. But the data is in most cases still useful. For example, employee counts from LinkedIn still give a good idea of the difference in size between a 1-2 person company, a 10 person company, and a 50 person company. Plus, they are useful when aggregated into sums. Some other per-column data caveats for the companies table are noted in the Counts sub-sheet of that sheet.
When text doesn’t fit into a cell and is clipped, clicking the cell will reveal the full text at the top.
Filtering & sorting is most useful for the big tables and thus at the moment mostly just for the companies table. All tables are Google Sheets spreadsheets, and as such you can sort by any column and filter which rows you see based on the values in any given column by creating a filter view (Date -> Filter views -> Create new filter view, which also happens automatically if you sort by any column). Once you are in the filter view interface, click the horizontal lines at the top of a column to select which values you want to see, or to re-sort. Your sorts and filters will not affect other people’s views of the information. For more details on this interface, see:
Video example: 2min video of sorting & filtering!
Longer video/talk: For a verbal description of some of the sorting and filtering and a longer talk about the Companies table and website feel free to watch the video of a roughly 10min talk on this (which was part of a larger event, but the video link here jumps directly to the start of the 10min talk).
To see public companies with phase 3 clinical trials, sort the “public?” column Z->A, then click the horizontal lines at the right of that column’s header to deselect “no” (and blank/? if there are any such rows), then do the same for the clinical stage header to select only ph.3 trials. Now one can easily click each ph.3 trials link to see the best link to the company’s pipeline, or click the hyperlink number in the clinical trials column to go directly to all of that company’s trials.
To see companies working on senescent cells, sort by the category column then deselect any values other than those that include senescence (or clear all and then select only those that contain senescence).
To see private companies that it was possible to determine have raised at least $1M in funding, sort the total raised column Z->A then click the lines on the column header, select filter by condition and create a filter for greater than or equal to 1. Note that it is not always easy to find public information about how much a company has raised, so this filter will surely exclude some companies that have raised this much, but it will generate a list of companies that have clearly raised at least this amount.
One can click other sub-sheets using the tabs on the bottom. Most of the small tables have a “scope” subsheet describing inclusion criteria & listing kinds of things that were explicitly excluded.
The Companies list has several notable subsheets: “Companies to consider” is as sort of to-do list of companies waiting to be processed and moved to the main list, provide that upon examination they are determined to really be aging companies. “Defunct” includes companies that no longer seem to be operating (eg because their websites have died and the leadership seem to have moved on to other projects). Most companies don’t have obituaries or other unambiguous notifacitons of their ceasing of operations so sometimes these are judgement calls, and we welcome corrections if we incorrectly think a company is dead. “Acquired” lists companies acquired and no longer easy to track as separate efforts from their new parent company. Other sheets should be fairly self explanatory.
The Counts subsheet of the Companies table deserves some extra explanation. Being a spreadsheet allows many interesting counts to be computed and automatically kept up-to-date.
For most columns that use consistent text string values across companies, this sheet computes counts of companies for various values. For example, one can see how many companies there are by geographic area for those with at least several companies, how many companies by clinical stage, by the various categorizations, by delivery modality, etc. How many are public vs private. Even what scientific advisors are associated with several companies.
For most strictly numerical columns, this sheet contains the simple sum total (total # of companies, clinical trials, employees, private investment money raised, and aggregate market cap for public companies). In some cases sums are computed based on useful restrictions, such as the number of companies with various minimum numbers of employees.
A special case of the above allows one to see how out-of-date the table is. Each row (company) in the main sheet lists the date of last update of its info. The right-most column of the counts sheet shows how many companies are out of date by various amounts of time.
[2022 update: June 2022 a big update to the companies table is happening and some cells that have not been looked at in a long time have very slightly grayer backgrounds. Cells that have been recently updated have their backgrounds changed back to pure white, but the date of last update is not changed to the present date until the whole row is updated.]
One limitation of the automatic counts by text string is that to be useful they require consistent terminology across companies (rows). At the moment delivery modality is tricky and a bit inconsistent. Eg, ‘drugs’ usually means small molecules but could mean small peptides. Proteins could mean small peptides or large proteins. Biologics is often used for proteins but can technically mean other body-derived substances. Similarly, no attempt has been made yet to reconcile the way diseases/indications are named across companies, so there is not much point in computing counts based on this column, though it would be useful if it were easy to make the language consistent.
It is also important to realize that the number of companies is not the ideal measurement unit for many kinds of analyses. Total number of employees, total money raised, aggregate number of clinical trials, etc. could be more useful in many instances. A few counts by total # of employees (eg, by geo) are included. More may be added later. You can easily compute your own with the appropriate restricts (see sorting & filtering above) and quickly copy/pasting to a scratch spreadsheet. Note that counts based on amount of money raised are problematic due to the spotty availability of the amount raised number for many companies, so for example a natural analysis one my might want---money raised by category by year---would be only based on very incomplete data. [2022 update: Also, as the field has expanded to Europe more of the figures on money raised are in different currencies, but due to the incompleteness and lag in this info becoming public anyway, it does not currently seem worth it to use extra columns to currency convert everything to a single currency for easier formulaic computations. Though anyone who wants to for any specific analysis could easily do so on a copy/pasted copy of any sorted/filtered version of the data.]
There may be a limit to the number of simultaneous view-only viewers of a “public on the web” Google Sheet or the number of different filter-views that can be simultaneously created by different users. If the interactive (sortable, etc.) interface version of the Companies table fails to work, there is a backup static-HTML version of the table available that should be viewable without limits (but this doesn’t freeze headers when scrolling nor allow sorting/filtering). So far this has never been a problem.
(Updated May 2023)
I’ve thought hard about how to sub-categorize what’s happening in the field. Each company in the sector is somewhat unique, but some are clearly more similar than others. One benefit of a relatively comprehensive list is the ability to categorize in order to highlight similarities, give a sense of resources being applied to different areas, etc. But deciding on a reasonable category breakdown is tricky business.
The main 3 prior attempts to partition the field are the SENS areas (~2002-3), the Hallmarks (2013, expanded 2022-3), & the Pillars (2014), but none of these is quite right for categorizing the full list of "aging" companies. Several investors have come up with slightly different (unpublished) sets of categories. The categories table here creates a superset of the prior 3 published breakdowns of the field plus adds a few extra categories for companies whose activities don’t fit well into any of those. The table also fully maps every SENS area, Hallmark, & Pillar to the single most appropriate analog in the other systems, providing a full mapping (the first such full mapping I’m aware of to be made public anywhere). It is surely imperfect, but there is value even in an imperfect but reasonable categorization that encompasses as much of the field being actively pursued as possible.
Separate from the category column in the companies table, there is also the issue of what should the possible values be for the "is it aging?" column. “Only brain", meaning yes but for only brain/neuro seems an important different value than just "yes". Some companies on the list are often categorized as regenerative medicine, but this label encompasses some things that seem more like the core list of aging companies (eg, harnessing stem cell signals that rejuvenate existing tissue or stem cells pools) and others that seem more peripheral or distinct (eg, 3D bioprinting companies). At the moment, organ replacement type efforts are separated into the list of only-peripherally aging companies. Like cryonics, 3D bioprinting is just too different in terms of techniques, relevant areas of biology, route to clinical approval & market, etc. to include them on the same list.