Norn Group Thesis
Norn Group’s mission is to maximize the probability that by 2060 we have interventions that will let a 60 year old live for another 60 years without a decline in health and function.
We’re on the way, but not there yet.
We believe that three decades of molecular aging research have revealed gene targets and possibly treatments that can add healthy years of life. Targeting biology that drives multiple diseases is a tremendous opportunity compared to tackling hundreds of diseases one at a time. Such multimorbidity therapeutics will represent the biggest impact on health since antibiotics, and should be pursued.
Refinement and application of currently known targets is promising, but will not by itself achieve our mission. First, effect sizes are not large enough1. Second, we cannot expect that combining treatments without some understanding of how they affect different organs and biological processes will yield compounding benefits. It’s possible that we will find very effective levers to reduce phenotypes of aging across all cells in the body, but also highly plausible that great benefits depend on combining ways to tune different cells in ways addressing their specific manifestations of aging.
We therefore believe that pushing the most promising ‘aging drugs’ into human testing should be combined with research efforts to develop layered solutions that could work in concert to overcome age-related decline.
* The most effective late-life intervention in mice, rapamycin, has a 10-15% effect size.
In the near term, increase our rate of learning.
With the aging field still engaged in unbounded exploration, we may be far from reducing development of additional treatments to a predictable playbook. This means that improvements in the rate of learning can have a large impact on what we can accomplish by 2060.
Given that the world is rapidly advancing in ability to computationally analyze and interpret data, we think that focusing on generating highly relevant data addresses the key bottleneck for unlocking new approaches for improving health. The greatest impact will come from validated ways to measure/predict the impact of interventions on age-related decline (i.e. biomarkers), which will give researchers the ability to test hypotheses 10-100+ times faster than they would waiting for aging to play out in humans**. Second will be to address the tension between aging being an interconnected set of processes while most assays measure one or a few at a single point in time - better tools to measure sets of causal relationships, especially non-linear ones, will greatly increase the insight per experiment.
Another way to increase our rate of learning is to increase the pool of talented individuals working on longevity. The aging/longevity field remains small, probably fewer than ten thousand researchers globally, and the space of ideas to explore is far from saturated. Given the challenges mentioned above, it is particularly useful to recruit experts in areas like biotechnology, drug development, and data science to work on problems in longevity.
Particularly in the 2020s and -30s, investing in improving the field’s capacity to generate insights will have great impact. Our goal should be to maximize our touchpoints with reality, rather than push a specific agenda for therapeutic development.
** Note that a number of biomarkers have been proposed, including DNA methylation arrays, composite blood scores, and more. But so far none have been rigorously tested for predictive validity.
In the medium term, clear the path for human data and application.
It is common wisdom in therapeutic development that preclinical models provide useful but imperfect predictions about human outcomes. For developing new multimorbidity therapies early and frequent human outcome data will be invaluable. And the duration of human studies targeting chronic diseases suggests planning ahead to avoid future bottlenecks for the field.
The lack of clinical strategy and trial designs with demonstrated success inhibits the field both by adding risk for startups and academic trials, and because this uncertainty is a major factor for investment into translational efforts. Different approaches are already being taken towards approval of multimorbidity drugs based on aging biology***, including some proposing to replace or circumvent FDA approval. We do not believe that a new paradigm is required for translating aging medicines; though not common, the current regulatory system has produced therapies targeting metabolic syndromes and/or cardiovascular health that appear to impact multiple diseases.
The main challenge for aging-based multimorbidity drugs is rather the circular dependency between effective treatments and trial design (endpoints, duration, etc) suited to measure those effects. Rigorous clinical trials for age-related conditions may well take a decade per therapeutic. Assuming that it may take two or even three attempts to provide a clear trial design, we should aim to have multiple plausible therapies in trials by the end of the 2020s****. Even without reaching primary endpoints, secondary endpoints suggesting target engagement and potential efficacy would let derisked trial designs be adopted by a suite of second and third wave therapeutic candidates.
Though not required, a superior system for identifying and approving treatments that broadly improve health becomes possible by validating predictive biomarkers that can predict future health and disease. Sound biomarkers would let us measure therapeutic effects without waiting for aging and disease to manifest, allowing far more opportunities to learn from patient outcomes. This could increase testing of therapies by perhaps an order of magnitude.
But the value of biomarkers depends on validating their sensitivity and specificity in predicting meaningful outcomes, which depends on validation data generated without shortcuts. The process of getting FDA and payer recognition of cardiovascular surrogate endpoints, allowing drug approvals based on lowering cholesterol rather than waiting for cardiovascular hospitalization and death, took two decades. We should therefore not delay rigorous testing of putative biomarkers, and we suggest that biomarker efforts ought to be included in all longevity-based clinical trials. In addition, work should be done to develop biomarkers that could be applied to existing biobanked samples.
What should biomarkers measure? Many current biomarker approaches attempt to capture ‘biological age’ as a single compressed metric, which would be efficient and powerful if successful. Because ‘aging’ is not well defined we think this approach holds risk, and advocate for a parallel effort to develop biomarkers of defined biological mechanisms that plausibly play a driving role in age-related disease. Such a modular approach is more robust to new discoveries, and linking interpretable biology to disease outcomes broadly incentivizes therapeutic development targeting this biology.
Regardless of approach, surrogate endpoints based on biology that drives multiple diseases turns every clinical trial into a chance to discover treatments that broadly improve health instead of testing only a single disease hypothesis. A serious effort started soon could achieve this around 2050, without relying on acceleration of technology or regulation.
*** The most common are to target a single age-related disease with hopes of expanding to other indications, targeting indications that may be surrogates for broader aging (e.g. sarcopenia), targeting pets before humans, or selling directly to consumers.
**** How many depends on our estimates of success rate. We think success rates will be lower than clinical trials in general and would suggest more than ten trials.
The field should be open-minded and extroverted.
We support continuing and expanding basic research and encourage exploring new topics. Many basic questions remain unanswered, and we believe the field can readily support several fold more high-quality research.
The range of research topics should also be expanded, to provide a diverse and layered set of opportunities for future therapies. Without an explanation of aging biology with strong predictive power we should not assume that most answers will be found within current areas of research nor the existence of a single ‘silver bullet’ approach to addressing age-related decline.
Aging researchers should invite collaboration with other fields. We think it just as likely that breakthroughs in understanding aging will come from new tools and methods as from directly exploring biology we’re currently aware of. For example, if aging involves interplay between a dozen or more mechanisms, then predicting causal relationships and intervention outcomes will rely on multidimensional assays and new analysis frameworks.
There should also be more communication between aging researchers and those working on individual diseases, e.g. in the form of joint conferences. This will disseminate insights about clinical research and trials into the aging field, and bring awareness about how to study the primary risk factor for most chronic diseases.
What is Norn Group doing?
We take action in all the areas described above. We emphasize areas where we see opportunity for leveraged impact and areas not addressed by other initiatives. Whenever possible we look for impact in multiple areas. For example, our program to provide funding for high-impact ideas has funded several early clinical trials, and many projects by researchers from other fields bringing new tools to bear on aging biology. We’ve also supported these researchers by directing motivated scientists to their labs.
Our activity is directed at solving concrete problems, with publicly available outputs that can benefit the field as a whole. In general we will attempt to empower motivated talent rather than retain staff in our organization, but are pragmatic and focused on outcomes.
In addition to our own efforts, we hope to provide useful guidance to other actors. To this end we will publish open questions, analyses of bottlenecks, and informational resources on this site.