Money in Aging Research, Part II

Part II : A Survey of For-profit Research Centers

How much money is going into aging research? The information is not so easy to come by.  This interview estimated that companies working on medical solutions to aging have a market cap of $300 billion as of 2018.  I’m guessing this number is rather too optimistic. This Business Insider article counted $850 million in venture capital funding in 2018.  That’s million with an m–a lowball estimate, it seems.  It’s safe to say the answer lies somewhere in the vast ocean between these distant shores.

I have not found comprehensive data on startups in anti-aging medicine, so this survey is incomplete and biased according to my own familiarity with the companies and their programs.  And the more important disclaimer: I have strong ideas about what the end of aging will look like, and this has colored the view I present of each company below. If you know of companies that you think should be on this list, please make suggestions in the Comments below.

Partial List:

Mature drugs

Geron is ancient by present standards, founded in Silicon Valley in 1990 by Michael West, who was already an advocate of telomerase therapies.  They are long established, with market cap of $260 million but only 15 full-time employees. Clearly, their mission is research rather than production. Over the years, they have turned their telomerase expertise into drugs that block telomerase, useful as a cancer treatment, since most tumors cannot continue to grow without telomerase.GRN163L (Imetelstat), is a drug under development that targets telomerase.  They apparently made the decision years ago, when they sold the IP for their best telomerase promoter to Noel Patton that telomerase was too dangerous to let out of the cage.  I wonder if even now they realize that was a mistake.

Elysium Health is Len Guarente’s company selling a formula of NR and pterostilbene.  Pterostilbene is a “better resveratrol”. Interest in both resveratrol and the NADH pathway grew out of Guarente’s long-time study of sirtuins.  I believe that modest health benefits have been established from this approach, but NADH is so well studied that if there were dramatic results, we would have seen them by now.  And NR treatment is not without risks.

Telomere therapies

Sierra Sciences (Bill Andrews) is focused on small molecules that promote expression of telomerase, lengthening telomeres and preventing cell senescence.  Screening hundreds of thousands of chemicals in vitro for telomerase activity, they came up with TAM 818, which is now for sale in New Zealand as a skin cream.  In an unrelated approach, they are offering a clinical trial (in a South Pacific island where regulatory agencies permit) using gene therapy to add copies of telomerase.  My personal opinion: Several years ago, I believed that telomere shortening was an aging clock of primary importance, but then a large Danish study demonstrated that the scatter in telomere length is greater than the consistent drift toward shorter telomeres with age.  I still think elongation of the shortest telomeres is an anti-aging strategy, but no longer regard it as centrally important.

Telocyte (Michael Fossel) is experimenting with telomere elongation to prevent Alzheimer’s disease and even to restore neurological function.  Fossel understood aging and had the vision to appreciate the role of telomere erosion more than 20 years ago, and I have the highest respect for him, but from what I know, AD as a target seems to be mismatched to the biology of telomeres.  Telocyte has recently announced a strategic partnership with Maria Blasco, a Spanish researcher whose lab has produced most of the biggest milestones in telomerase therapy.

Gene therapy

Rejuvenate Bio The Harvard laboratory of George Church was early in recognizing the potential for CRISPR technology to bring gene therapy into mainstream medicine.  Rejuvenate Bio is offering a gene therapy program to dogs who are at genetic risk for mitral valve disease, a congenital heart disorder. It’s cheaper than human trials, with less liability when something goes wrong, and it’s a viable lab for gaining experience and honing technique. [Writeup at FightAging!]

Stem cell therapy

Stem cells are among the most promising technologies we have for regenerative  medicine.  I’m surprised not to find more companies doing basic research, but there are lots of companies bringing the present (hit-and-miss) state of the art to patients.  Advanced Cell Technologies, a leader in the field, is now a part of Astella Therapeutics. Apceth Biopharma delivers stem cell technologies in the health marketplace but doesn’t seem to do much research.  Pluristem Therapeutics and Brainstorm Cell claim to have active research programs.  I have found no companies focused on the potential of stem cell therapies for extending lifespan.

Clinics and personalized medicine

AHNP (Apollo) acquired MPI, which was Dale Bredesen’s vehicle for bringing his Alzheimer’s protocol to the medical public.  I give AHNP special mention because I believe that Bredesen’s program is not only the first credible treatment for bringing brains back from AD; further, I think that Bredesen’s Alzheimer’s preventative program doubles as a comprehensive program to slow aging.  With individualized programs based on a battery of diagnostic tools, it’s a new model for how to do preventive medicine. I believe the program has transformative potential, but translation to the clinic has led to growing pains at AHNP. They can’t train new staff fast enough, and they’ve fallen behind explosive demand from new patients. Their software interface is buggy and there’s a backlog of requests for personal support, but they’re aware of the problems and building capacity as fast as they can.

Leucadia Theraputics has a diagnostic and treatment model for Alzheimer’s Disease based on drainage of amyloids from the brain, and physical blockage of the drainage pathway.

L-Nutra is Valter Longo’s company, offering programmed, packaged meals that provide some of the benefits of fasting with less of the hunger and deprivation.

Data Mining

Human Longevity is mining hospital records and genomic data to look for correlations. They offer testing and counseling to customers, then base their study on their customer base.

ASDERA is Knut Wittkowski’s small but important New York think tank.  Like other math geek operationss, they are using computers to mine data for patterns that lead to new drugs.  But unlike the others, they are not relying on the black box approach of neural networks. Wittkowski is an old-school statistician, familiar with an arsenal of classical statistical tests, choosing with judgment and expertise applied to the caseat hand.  Both approaches are computationally intensive. The difference is whether computations are guided by expertise and experience or by an algorithm that directs its own search toward a human-defined goal. Think of it as Artificial Intelligence vs Human intelligence, if you like.  Supervised learning vs a purely algorithmic search. Time will tell which approach yields more leads to actual treatments. I’m rooting as usual for the underdog, the classical against the avant garde.  Neural networks may yield a prescription, but you don’t know if it’s a fragile artifact of the particular data you used or a robust new truth about biochemistry, and the computer can’t tell you what it’s thinking.  With more human participation in the process comes more understanding of where the result comes from and (at least) a guess as to what it probably means.

 Acturx is another data mining project, headed by Edouard Debonneuil.  Debonneuil’s background is in actuarial science for insurance companies, and he is mining insurance records of millions of patients.  By correlating prescription records with health outcomes, they look for unknown benefits from known drugs.

Senolytics

Everon Biosciences was founded in 2010 by Andre Gudkov, with awareness of programmed aging built into their strategy. Gudkov believes that endogenous DNA damage in somatic cells is a primary clock driving diverse aging phenotypes.  A prominent kind of DNA damage is the duplication of regions of DNA that contain no genes (retrotransposons, including LINEs and SINEs).  NRT1 is a drug in development that inhibits the enzyme that makes the copies.  Another locus of research is senescent cells as emitters of signals that drive inflammaging.   But while other companies are racing to find agents that selectively kill senescent cells (leaving normal cells undamaged), Everon has focused on the innate immune system, including neutrophils and macrophages.  Their hypothesis is that the innate immune system takes care of senescent cells when we are young, but the system has a fixed lifetime capacity, and once its limit is reached, senescent cells accumulate and the vicious cycle of increased inflammation begins.  EBS3899 is a molecule they are testing for its ability to sensitize macrophages to senescent cells, and it seems to work better in vitro than in vivo.

Unity Biotechnology works on one molecule at a time, exploring their potential to relieve arthritis or degeneration of the eye or age-related disease in lungs, liver, kidneys and the CNS.  UBX0101 is their arthritis drug, in trials.  Other drugs at earlier stages of development target senescent cells and cognitive decline.

Oisin Biotechnologies is searching senolytic drugs, joining a crowded race to minimize toxicity to normal cells while efficiently eliminating senescent cells.

Biomarkers and Age Clocks

Spring Discovery and InSilico Medicine. In order to study anti-aging interventions, we need to evaluate them, and the traditional measure — waiting for experimental subjects to die — is too slow. This is the reason the Horvath clocks are so important.  His algorithms based solely on methylation profiles are the best measures of human biological age we have so far. Spring and InSilico are both trying to improve on that, combining other measures along with methylation, and using neural network analysis — the black box of AI — to look for patterns that evade human brains. These two companies are unrelated and working on opposite coasts, but if there’s a difference between their goals or methods, I have yet to understand what it might be.  [ScienceBlog article on InSilico]

Signal Molecules in Blood Plasma

[Background in my blog from 2 years ago.]

Jesse Karmazin’s Ambrosia  was an ambitious start-up, turned to object lesson in hazards of the fast track.  The basic premise is sound — that blood factors from the young are able to set back the clock of the older animal (or person) in whom they are introduced.  But which blood factors? And how much is needed? And how many treatments would be needed before the body would set its own clock back, and start producing the youthful factors by itself?  Karmazin’s plan was to ask these questions with clinical trials funded by his subjects, people willing to pay thousands of dollars for two transfused pints of blood from a young person. This past winter, the FDA stopped him in his tracks.

Tony Wyss-Coray’s Alkahest has taken the same promising premise and followed with more care toward a promising future.  In the early 2000s, Wyss-Coray was one of the Stanford pioneers of parabiosis. Originally, Alkahest seemed to be headed in the same direction as Ambrosia, offering small quantities of young blood to wealthy clients afflicted with Alzheimer’s.  But now they’ve made some important discoveries about the active ingredients that give young blood its rejuvenating power. They are well aware that it’s all about dosage–that some plasma components need to be downregulated and some upregulated to turn old blood to young (and perhaps turn old bodies to young…).  They’ve coined the term “chronokines”, key proteins that increase or decrease with age, and they’ve identified a few of these and launched clinical trials for macular degeneration and, Parkinson’s, and dementia. I’m impressed. My only suggestion is that they should be alert to the possibility that the interaction among these chronokines might be non-linear and, perhaps, surprisingly complex.

Other approaches

Google CALICO is well funded, but their relevance to progress in the field is hard to assess.  We might guess that their research direction follows the intersts of Cynthia Kenyon and David Botstein, i.e., understanding the genetic contributors to aging in worms and yeast cells.  They are partnering with Harvard’s Broad Institute and California’s Buck Institute in basic research.  They are in it for the long haul, building biochemical knowledge from the ground up. If someone doesn’t get there first, we may be very glad for their industry in another 10 years.

Google has also invested in shorter-term drug development through Verily Life Sciences, with partnerships that include GlaxoSmithKline. Personal note: I see a danger here, in which the company that we trust to direct us to the best information sources is allied with an industry that has done so much to promote its products with disinformation about health.

Lyceum is Michael Rose’s effort to commercialize research he’s done on the genetics of aging in fruitflies.  The web site claims a systems approach, which sounds right to me, but no details are offered at this early stage.

resTORbio is developing variants of rapamycin, which is perhaps the most credible anti-aging drug commercially available.  Rapamycin is not patentable, the main reason we see more research on variants and less on rapamycin itself.

CHAI = California Healthy Aging Initiative
Game-changer on the horizon

Activists in California are gathering support for a ballot initiative to provide $12B in state funding for anti-aging research over the next 12 years.  CA is one of the states in which the people can create legislation directly with their votes; and in 2004, this process was used to appropriate $4B for stem cell research.  Promoters of CHAI are trying to build on this precedent. But they face a dilemma. Gathering signatures and educating the public is an expensive proposition. They will need a broad coalition of research interests in the field to get their measure off the ground.  But of course, these organizations will want to write the text in such a way as to direct future funding to themselves. The grass-roots activists who are energizing this initiative believe that adding incrementally to institutions that are already well-funded is less likely to generate disruptive technologies than many small grants to individuals and start-ups with idiosyncratic theories of aging.  I like the idea of supporting small people with big ideas, perhaps because I are one.  This is a science still in its exploratory phase, where we do not have a definite idea what will work, and there are competing theoretical frameworks to guide us.  Once the proof-of-concept is complete, it’s appropriate to pursue the “D” part of “R&D”, and for that, industrial-scale research is the most efficient course.

My perspective on the state of research

I believe that aging is regulated under epigenetic control, but that the biochemical language of epigenetics is complicated, and it will be a slow road indeed if we persist in studying one intervention at a time.  The time is right for open science, open communications, interdiciplinary collaboration, and the testing of treatments in sets of 2 and 3 and 4. (If we study only treatments in isolation, we miss the boat; but if we try to study 5-way and 12-way interactions, the number of combinations will overwhelm our neural networks–both silicon and wetware.)

I continue to promote DataBETA because I think that it is a methodology for exploring the landscape from a perspective of radical empiricism, and point us in new directions.  DataBETA is looking for a university partner with experience in large-scale trials and otherwise is funded and ready to launch.

Our knowledge of biochemistry comes mostly from a reductionist framework.  We understand cellular systems better than we understand organs and tissues. We understand least of all the global signaling and interactions by which the body coordinates its growth, its homeostasis and (I believe) its aging.  The primitive state of systems biology counsels an empirical approach.

Im glad to see money and talent pouring into aging research, and it’s refreshing to see how much of it goes to people without theoretical preconceptions.  But many of the engineers and computer geeks coming into aging science are experienced in a world where problems can be split into manageable parts—divide and conquer.  My guess is that aging will be refractory to this approach, and will yield in the end to a multi-pronged but holistic therapy.

I gave up on the stock market years ago, the pride of the mathematician laid low by the surprises of the real world; but if I were a gambling man, I’d bet on Bredesen/Apollo.  There’s a solid core of biochemistry under a mountain of clinical data, and sparked to life with a bit of inspired guesswork.  They are modest (or prudent) enough to claim ‘only’ to have cured Alzheimer’s, but I would be eager to see methylation tests that relate their protocol to the best aging clock we’ve got.

Money in Aging Research, Part I

Part I : The Business Culture of Science

Since 2000, there has been a 20-fold increase* in research funding for anti-aging medicine.  Wow! That’s a good thing. But let’s keep our eyes on the ball. There is danger that this welcome infusion of capital may be biasing research priorities toward those that are most likely to be profitable, and maybe even diverting the best researchers from the radical thinking that will change our understanding of biology.


Whoever discovers an effective age-reversal treatment is destined to become a multi-billionaire!

At first blush, this statement seems obvious, but that doesn’t mean it’s true.  There are many historical examples of people who gave enormous gifts to the world, but struggled in their lifetimes for recognition and even for a livelihood.  Schubert, Poe, and van Gogh are artists who died poor, while people after them reaped billions from their work. Inventors who never profited from their inventions include Johannes Gutenberg and Nikola Tesla, Jagadish Chandra Bose, and Antonio Meucci (who?).  Reginald Fessenden invented radio a generation before Marconi.  Rosalind Franklin got no credit for being the person whose diffraction data and analysis was stolen by Watson and Crick for their Nobel research on the double helix.  

More to the point, there have been great discoveries that had no commercial value, or even negative commercial value.  Linus Pauling spent the last years of his life documenting the anti-cancer action of intravenous vitamin C. To this day, vitamin C is under-utilized and under-studied precisely because it is so cheap that no one can get rich from it.  I believe that aspirin and metformin may be two of the most potent life extention drugs that we currently know about, but we can’t be sure, because they are both long out of patent, and no private company can justify the investment to study them.

Rumors abound about cancer cures and energy technologies that are being suppressed because they would derail two of the most profitable businesses in the history of capitalism.  I don’t dismiss such claims out of hand.

If there were a drug that could increase average human lifespan by 15 years (with side-effects that were wholly salutary), there would be a dozen companies tinkering with it, adding a methyl group here or a double bond there, looking for a variant that might boost lifespan by 18 or 23 years.  In fact, there is about a 15-year advantage for people who are in a loving relationship, have deep community ties, assume responsibility for leadership, make lots of money, enjoy frequent sex, and remain close to young family members; in comparison, the typical middle-aged American is lonely, alienated, struggling financially, and sub-clinically depressed, with a life expectancy 15 years shorter than it could be.  The most effective things you can do to increase your statistical life expectancy are psycho-social, but who is conducting research into optimizing the life-extending benefits of community and relationship?

Diet, exercise, saunas, and fasting are life extension strategies that are promising and under-researched because there is no clear path to mega-profits.

 

What I believe

I am convinced that the primary basis of aging is an epigenetic program.  Systems that repair and protect our cells and tissues are gradually shut down, and destructive systems including inflammation and apoptosis are ramped up at late ages. Gene expression changes, modified systemically by transcription factors that circulate in the blood.  I believe that these blood factors are the holy grail of aging research. Control over aging will come when we learn enough about the basic language of epigenetics to reprogram gene expression with our interventions.

The difficulty is that there are dozens of known epigenetic mechanisms, of which only a few have been studied in detail.  A few years ago, it was understood that modifying non-coding regions of DNA could affect the transcription of nearby genes (cis epigenetic signals), but now we know that transcription of genes far away from the modification can also be affected (trans signals).

There is yet more complexity: most hormones and regulatory molecules have secondary roles that affect transcription.  Imagine an ecosystem of signal molecules that maintains itself homeostatically, but also changes with age. Sixty years ago, we learned that the genetic code is as simple as it can logically be; every codon three base pairs on a DNA strand is uniquely transcribed to one amino acid, and a protein is built by chaining these together in order.  Today we are learning that epigenetics is about as complex as it can be. So in my paradigm, basic research in epigenetics is an essential foundation for anti-aging medicine. If we are lucky, a dozen synergizing interventions will do enough reprogramming to re-set the aging clock. Perhaps there is even a region of the brain that is a common source for the molecules that induce age-related change.  If we are unlucky, it may require re-balancing blood levels of hundreds of different substances.

I am optimistic that this can be done, but it will require collaboration on a broad scale.  The process is unlikely to end with a single patent-holder who can rake in $ billions. The secrecy and the balkanization of corporate research is slowing progress.

 

Biases in Corporate Aging Research

For the last five years, Google CALICO has been the 800-pound gorilla in the room.  Of course, we welcome their funding, the legitimacy they lend, and their collective brainpower to our field.  But they don’t play by academic rules. They are not following the open-source / free-to-the-public model that has been so successful for Google in software.  They trend secretive and are not collaborating with university experts outside their walls.

CALICO isn’t announcing its philosophy or paradigm, but we might guess from its lineage that their methodology is rooted in data mining and artificial intelligence.  Other companies that have announced publicly that they are taking this approach include Unity Biotech, InSilico Medicine and Spring Discovery.  They have in common a data-intensive approach founded in theoretical agnosticism.

Machine learning has been used successfully to create algorithms that translate languages, that drive cars, and that recognize faces.  The best thing you can say about this approach to anti-aging medicine is that it is free of the theoretical biases that have plagued aging research through the decades.  The worst thing you can say about it is that it misses a fundamental difference between organisms and machines.

Machines are designed by human logical minds, and each part is engineered to perform a single function and do it optimally.  Organisms are evolved by a process that depends on results only and involves no logical thought. We have found empirically that in biology, parts tend to serve multiple purposes.  Causes and effects are entwined in tangled feedback loops. Hormones and other proteins are likely to serve multiple, overlapping functions, some of which are metabolic and some of which are regulatory.

With a homeostatic physical system, you can tweak it to the right and it will bounce back to the left some fraction of the distance, so that the net effect is to move to the right but with less than your original amplitude.  With a homeostatic biological system, you can tweak it to the right and it may bounce back and end up further to the left. The canonical example of this is hormesis, which is so counter-intuitive that it took experimental scientists two decades to establish its legitimacy among biological theorists.

The Challenge of Using AI to Modify Aging

Machine learning algorithms work by finding optimal paths toward a well-defined goal.  The machine learning paradigm needs a clearly-defined goal as a prerequisite. In the previous triumphs of machine learning listed above, the goal was well-defined before the process was begun.

Application of machine learning to anti-aging will require a quantified measure of biological age.  This is what has held up the field in the past. We can measure lifespans in worms in a few weeks, but to measure lifespans in humans takes decades.  Aging research needs feedback that is faster than this.

Just in the last year, there are epigenetic clocks based on methylation that predict future mortality and morbidity far better than any other metabolic test.  The bottleneck now is the availability of methylation data that is correlated to anti-aging interventions. That is why I have promoted the DataBETA project to collect methylation data from a diverse set of early-adopters of anti-aging interventions.

Using theory-free computer algorithms to search for anti-aging interventions is better than going about it with the wrong theory, but it’s not as effective as starting with the right theory.

 

This is larger than aging medicine

The culture of business has had a profound impact on science in general, not just aging science.  A hundred years ago, people who pursued science were motivated by pure curiosity and intellectual ambition, because there was little reward to be had.  Today, science is a career for something approching 10 million people worldwide.  Then, science was pursued by dogged individuals.  Now, science is managed by bureaucracies.

More patents have been issued since 2000 than all of history before. It’s often said that the number of working scientists is 10 times greater than all the scientists who have ever performed research in the past, but the actual figure is more than 100 times.

Credit: Future of Life https://futureoflife.org/2015/11/05/90-of-all-the-scientists-that-ever-lived-are-alive-today/

The advance in scientific data reflects this increase, and more.  To the extent that scientific productivity can be quantified, the productivity per scientist has increased as the number of scientists has advanced exponentially.

What we don’t have is exponentially more understanding.  It’s enlightening to compare the first half of the Twentieth Century with the second.  The first half** brought us revolutions in understanding:

  • Milliken made the electron real as Rutherford pointed to the structure of the atom
  • Planck told us the world is quantized
  • Einstein taught us to think in terms of a fabric of space-time, molded by matter-energy
  • Heisenberg and Schrodinger taught us that the quantum world is fundamentally interconnected and indeterminate
  • Godel surprised us with a demonstration that there are limits to mathematical certainty
  • Hubble discovered that there are hundreds of billions of galaxies beyond our own, and that they’re flying away from us, the further the faster
  • Lewis, Born, and Pauling gave us a science of chemical bonds based in quantum physics
  • Alpher and Gamow proposed the hot Big Bang universe
  • Franklin, Crick and Watson discovered the biochemical basis of genetics

What do we have in the second half of the century to compare? I’d put three things in the same league as the above list, and they are all observations for which a theoretical framework remains elusive:

  • Penzias and Wilson stumbled on the 3 degree microwave background, promoting Big Bang cosmology to the status of a quantitative science (1965)
  • Observations of distant galaxies proved that the expansion of the universe is accelerating; dark matter and dark energy were introduced as the least radical modification to established cosmology (1997)
  • Epigenetics came into its own in the 21st century, as it was discovered that big variations in gene expression are more important for the direction of life than small variations in gene sequence.

With so many more scientists, why aen’t we seeing new and powerfully synthetic theories?  It’s just not plausible that no one as smart as Newton or Euler or Darwin or Planck is alive today.  Then, are the “easy” problems all solved, and the remaining problems in science so much harder? Certainly that’s true to some extent.  But there is a larger part of the story, and it is the canalization of scientific thought. Scientists today are paid to be efficient. There is a model of productivity borrowed from industry that is completely inappropriate to science.

We are all agreed that your theory is crazy. The question that divides us is whether it is crazy enough to have a chance of being correct.                       — Niels Bohr (to Wolfgang Pauli)

Through the culture of business, science has become conservative, which is to say dogmatic.  It is more difficult than it used to be to throw out a theory that doesn’t work. Almost everyone is working to push outward in the directions that science has already advanced, but almost no one is digging at the roots, or exploring fundamentally new directions.  Almost everyone is engaged in the safe science of incremental advance and almost no one is taking the big risks.  Tenure is granted to fewer science faculty members, and they are getting tenure at later ages.  Career uncertainty makes scientists risk-averse.

With so much at stake, science is being managed by committees and bureaucracies.  They judge on the basis of conventional wisdom and measurable results.  Business by nature is risk-averse.  But in the long run, science can only advance when we scrap the idea of predictable returns on investment and accept a very high failure rate.


Part II next week: survey of biotech companies doing research in anti-aging medicine.

———————
* 20-fold increase is my estimate, a soft number.  I’ve been unable to identify hard statistics, and of course the very definition of “anti-aging” is changing as the idea that all diseases of old age can be delayed has come into general acceptance.

** I’ve taken the license to include two discoveries from 1952 in the first half of the century.