Figure: resTORbio Public Share Price 2019
Figure: resTORbio Public Share Price 2020-2021
While the above examples are the most stark, we can see that this is a general trend by viewing the 1-year average drop in the capitalization of a wider variety of publicly-traded Longevity companies:
As we can see, unfortunately most of the publicly traded companies which can be considered Longevity-focused companies have seen declining capitalization in the last years and in 2019 in particular.
By now, it should be clear that the Longevity Industry faces a fundamental and widespread problem: the majority of leading Longevity investors are still operating under the paradigm of therapeutic validation (and, by extension, company valuation) that worked in the broader BioTech and BioPharma industries.
This fundamentally flawed and risky industry-standard paradigm has led to unjustified company valuations following successful preclinical trials in model organisms such as mice. And even in the case of BioTech and BioPharma (which deal with domains of science and medicine far less complex than Longevity, focusing on single disease targets rather than highly complex and integrated networks of deep biological processes), it only just about worked, given the enormously high clinical failure rate in these industries.
Due to the complexities of the biology of aging and the underlying science and technology, as well as the high levels of scientific and technological intersectionality in the Longevity sphere, many companies are likely to fail, leading to much higher clinical trial failure rates, and ultimately a failure of many players to provide ROIs proportional to their valuations
This issue is especially prevalent in California, which has a very strong geroscience focus, and which can be considered the global epicenter of Longevity BioTech. Compared to other regions (e.g. the U.K. and Switzerland), the perception of the Longevity Industry, in both its scope and main trends, in California in general and Silicon Valley in particular varies significantly. Here in the U.K., it is most often conflated with biomedical moonshots – very advanced biomedicine not yet at the stage of human clinical trials. This is an angle that severely underestimates technologies which we consider to be within the scope of the Longevity Industry, and which are actionable and closer to market readiness.
About the Next Article
In this article I have outlined what Deep Knowledge Group has believed for several years (since our first investment in the Longevity Industry in 2014) to constitute the largest fundamental and systemic risk and source of potential market destabilization for the Longevity Industry: namely, the overwhelming reliance on results in model organism studies (e.g. in mice) rather than humans, and the assumption that positive preclinical results will translate into correspondingly positive results in humans.
In the next article of this series, I will outline an integrated set of modern technological and scientific approaches and the framework of a proposed solution to this widespread foundational and dangerous assumption – a solution that can allow for safe and effective human-centered validation of Longevity therapies and technologies at the pre-clinical trial phase, and can be used by investors to de-risk their investment decision-making; by Longevity companies to more reliably validate the safety and efficacy of their therapeutic pipelines; and by Longevity startups preparing to launch IPOs to prevent dramatic declines in their market capitalization following failures for their model organism results to translate to humans.
The Longevity Industry’s Fundamental & Systemic Risk: Reliance on Animal Model (Mouse) Results for
Investment Due Diligence and Valuations
By Dmitry Kaminskiy, Founder and General Partner of Deep Knowledge Group
In ‘Longevity Industry 1.0: Defining the Biggest and Most Complex Industry in Human History’, we distilled the complex assembly of deep market intelligence and industry knowledge that Deep Knowledge Group and its Longevity-focused subsidiaries (including Longevity.Capital and Aging Analytics Agency) have developed over the past 5 years into a full-scope understanding of the global Longevity Industry, showing the public exactly how the international consortium of commercial and non-profit entities managed to define the overwhelmingly complex and multidimensional Longevity Industry for the first time, and how they created a tangible framework for its systematization and forecasting.
Whereas Longevity Industry 1.0 charted the inception and rise of the industry up to 2020, and provided the methodology and framework for defining and analyzing the industry, its sequel, ‘Longevity Industry 2.0: DeepTech Engineering the Accelerated Trajectory of Human Longevity - The Blueprint and Pathway from Longevity Industry 1.0 to 2.0’, outlines Deep Knowledge Group’s recent work towards formulating the pathway to Longevity Industry 2.0, and presents the framework for safeguarding the sector’s current upward trajectory and ensuring its optimized, sustainable growth towards its next stage and the realization of its practical benefits for humanity by the year 2030.
The previous article in this series introduced actionable, market-ready panels of Biomarkers of Human Longevity as the scientific and technological domain having perhaps stronger prospects of accelerating the translation of Longevity theory into practice than any other, and in accelerating the short-term trajectory of real-world applications in Practical Healthy Human Longevity.
In the present article, we will extend this discussion by discussing the Longevity Industry’s foremost fundamental and systemic risk and potential source of future destabilization, which lays the necessary background and context for the third article in this series, which will provide an overview of how Biomarkers of Human Longevity, in integral combination with other modern tools, techniques and technologies, can be used to neutralize this source of risk, and pave the way for more stable and balanced developmental prospects for the future of the Global Longevity Industry.
The Longevity Industry’s Most Flawed Assumption Is Also Its Biggest Fundamental & Systemic Source of Risk
The Longevity Industry faces a fundamental, widespread and systemic problem that threatens to destabilize its current upward trajectory of growth, diversification and increasing investment volumes: namely, the well-established but highly outdated practice of experimentation on model organisms with the expectation that their outcomes will translate to humans.
This has been the consensus paradigm followed in the traditional biomedicine and biotech industry for the past 50 years, and has consistently shown that, in the majority of cases, drugs do indeed fail to translate to humans with sufficiently high effectiveness or acceptably low adverse effects to make it to market.
Given the 90% failure rate of clinical translation into humans in the comparatively simple biomedicine, biopharma and biotech industries, which deal with interventions with far fewer complex components (e.g. single molecules) targeting far simpler biological systems (e.g. individual disease targets), it is reasonable to expect higher failure rates for multidimensional therapies with many “moving parts” that target significantly more complex biological processes.
The source of this high anticipated failure rate is twofold. The first fundamental factor is the vast biological (physiological, genomic, epigenomic, etc.) differences between humans and model organisms, both general and in terms of the actual nature of aging in particular, which is scientific. The second is not so much a scientific (and, therefore, fundamental) problem, but one rooted in honest but flawed human nature and error – the fact that by current estimates as many as 70% of scientific experiments, studies and articles are not repeatable, due to either well-intentioned mistakes or intentional fraud. This phenomenon is often referred to as science’s modern “replication crisis” and will pose even more challenges for the expected success rate of human-focused Longevity therapeutics.
If this trend continues, it could lead to general pessimism about the Longevity Industry among investors and harm the prospects of the entire field, including non-biomedical sectors, by association, weakening investor sentiment, driving down the market cap of the increasing number of Longevity companies that are holding IPOs before demonstrating human safety and efficacy, and risking the rise of a Longevity boom and bust cycle.
There is, however, still time to neutralize these risks by embracing new, modern and more sophisticated approaches to investment analytics, due diligence company valuation and – most importantly – technological and scientific validation of Longevity therapies and technologies, that are equal to the complexity, intersectionality and multidimensionality of the Longevity Industry itself.
Mice vs. Men: The Rise and Risk of Longevity Hype
Back in 2013, Silicon Valley tech giant Google promised the world that it will solve the problem of death. We have entered a new decade now; however, in our opinion, the progress in actual, practical life extension of humans is not far away from where it was back in 2013.
There is a lot of positive hype on the subject: many people, ranging from the general public to scientists, entrepreneurs and investors, are confident that we are at the brink of creating actual human life extension techniques which will soon translate into real-world, accessible applications.
Here, we will systematically examine the evidence for whether or not this is actually the case and offer a set of guidelines to help separate hype from reality around this proposition in a concrete, logical and tangible way.
Indeed, a number of Longevity-focused scientists have achieved rather significant progress over the last decade with respect to stalling the aging process and in some cases even achieving rejuvenation (restoration of a young phenotype) in certain model organisms such as yeast, worms, flies and mice.
For instance, in January 2020 researchers at MDI Biological Laboratory, in collaboration with scientists from the Buck Institute for Research on Aging and Nanjing University in China, identified synergistic cellular pathways for Longevity that amplify lifespan fivefold in C. elegans, a nematode worm used as a model in aging research.
In another example (October 2019), Maria Blasco and colleagues managed to extend the lifespan of mice by 24% by breeding a set of chimeric mice using embryonic stem cells with telomeres twice as long as usual.
The number of headlines highlighting substantial increases in both the lifespan and healthspan of model organisms has grown dramatically in the past decade.
However, while we see significant progress in model organisms, this is not the case with respect to humans. The overwhelming focus and confidence of Silicon Valley-based Longevity companies that positive results in model organisms will translate into comparable outcomes in humans is a major destabilizing factor in the industry and the most dangerous underlying assumption in the entire industry ecosystem.
Such an assumption is something that Deep Knowledge Group’s Longevity-focused investment fund Longevity.Capital takes specific measures to avoid and de-risk by mandating preliminary positive results in humans as a core factor of its scientific due diligence for biomedical companies, as well as by strategically prioritizing other sectors with high degrees of market-readiness that are not exclusively focused on biomedicine, such as AI for Longevity, AgeTech and Longevity FinTech.
While the issue of transferability of positive outcomes in model organisms to humans has long been a concern for some of the more forward-thinking specialists in the field, it is only recently that hard data on the matter has come to light. For instance, on February 14 Science published a study under the title “Translating preclinical studies to humans.”
The article summarizes many of the issues at the heart of the difficulties in translating drug successes in model organisms into humans and provides some suggestions on how AI could be used to shift toward more human-centered approaches: “Systems biology and machine learning (ML) can be used to translate relationships across species. Instead of attempting to “humanize” animal experimental models, which is possible only to a limited extent, greater success may be obtained by humanizing computational models derived from animal experiments.” Suffice to say that we have always been skeptical regarding over-valued results in model organisms and overconfidence in their ability to translate to humans, and we welcome the latest science which is validating those concerns more and more with each passing day.
In short, in contrast to the growing volume of positive results in model organisms, advances (or lack thereof) in practical human life extension and understanding of human Longevity are at a comparative standstill. Deep Knowledge Group’s position is that with the right set of approaches and methodologies, science could have progressed twice as much in terms of human healthspan extension compared to actual results achieved during the past 10 years.
In our opinion, one of the factors behind this comparatively slow rate of progress is that aging research overvalues certain specific technologies and domains compared to others. With the enormous volume of resources behind tech giants such as Google and Amazon, as well as many biotech, biomedicine and healthcare companies, we should have seen much higher success rates of practical, tangible developments aimed at extending human life and healthspan, enabling us to determine which research sectors are overfinanced and which are underfinanced – however, this has not be the case.
Furthermore, the fact of the matter is that retail investors are already beginning to feel the tangible results of these risks and dangers on their own bank accounts, as a result of the public share price of public Longevity companies (who help IPOs based solely on the results of model organism studies) plummeting due to post-IPO failures in clinical (human) translation and validation.
Figure: Unity Biotechnology Public Share Price 2019
Figure: Unity Biotechnology Public Share Price 2020 - 2021