Skip to main content

Proceedings from Longevity Science Conferences 2021

Ending Age-Related Diseases 2021

This post is in-progress!  The conference just ended on Aug. 22;  as I clean up my notes, I'll post them here.  Please come back for future updates...

Link to conference


 (Notes and screenshots taken - and sometimes annotated - by me.  I will later contact the presenters to offer them the option to review them for accuracy...)

Science at SENS Research Foundation 2021

Talk by Alexandra Stolzing, Professor for Biogerontological Engineering, VP of Research at SENS Research Foundation ("Strategies for Engineered Negligible Senescence".)

This overview talk immediately emphasizes that the aging process involves multiple broad fundamental categories of physiological change.  Those are related to what are often referred as "the Hallmarks of Aging", as I detail in my intro post on Longevity Science.  In this talk, 7 of those categories are identified, and given convenient icons (rightmost column) that make it easier to refer to them:

The SENS foundation has both intramural and extramural projects happening, and tries to have at least one project in each of the above broad categories.  (But currently no project in the "OncoSENS" category; submissions are encouraged!)

External projects at SENS include the following:

More info on SENS's external projects; in particular, the above ones:

  1. Target Prioritization of Tissue Crosslinking
  2. Functional Neuron Replacement to Rejuvenate the Neocortex
  3. Therapy to Destroy Cells with Reactivated “Jumping Genes” 
  4. Lipofuscin Degradation by Bacterial Hydrolases

Moving on to intramural projects... if the mitochondrion slackens off, can the nucleus take over its genes?  In-vivo work with a mouse model:

The immune system's decline with age has been tragically underscored during the Covid pandemic...  One strategy being explored is trying to eliminate senescent cells in hope of improving immune function.  

[Side note from me: the elimination of senescent cell, in a different context, has been a goal, though without positive outcome so far, of Google's venture into longevity science, Calico Life SciencesHal Barron, the Chief Scientific Officer and President of R&D at the company where I work, pharma giant GSK, was President of R&D at Calico for 3 years, till 2017]

But how to kill off those pesky senescent cells?  How about recruiting "Natural Killers", aka NK cells, and stimulating their natural proclivity to dispatch senescent cells?  Enhancing Innate Immune Surveillance of Senescent Cells.

Troublesome senescent cells, sadly, tend to "corrupt" other cells and instigate them to enter a senescent state, too.  These "second-generation" senescent cells are different - and another project is to figure out how to get rid of those as well:

The SENS Research Foundation likes to incubate projects, typically foundational and remote from direct practical application; the spinoff companies focus on the latter.  Some of them:

 SENS also has educational programs, in collaboration with various institutes:

Grants proposals are accepted by SENS at any time of the year.  Typical grants are US $50 - 350k , for 1-3 years.

SENS is especially interested in combining potential targets (possibly developed by separate companies) and exploring if they have synergy together.

 

(More talks to be added!  Please come back for future updates...)

 ____________________________________________

One talk from last year, but still relevant:

Ending Age-Related Diseases 2020

Acceleration of human rejuvenation trials: The path from research to application

4 key points:

1. We need to monitor people in trials AND out in the wild more frequently and on a wider amount of biomarkers 2. We need to give access to interventions to people and collect data on more interventions and combos 3. We need to start collaborating and finding ways to allow all data to be leveraged to slow aging 4. We need to learn from any failures and iterate more quickly The 6 presenters:

* Aubrey de Grey, PhD, Chief Science Officer and Co-founder, SENS Research Foundation

* Kevin Perrott, PhD, Adjunct Processor at U. of Alberta / CEO at OpenCures [Note: I used to work there, as CTO and science liaison, prior to my current position at GlaxoSmithKline pharmaceuticals]

* Gregory Fahy, PhD, Chief Scientific Officer, Researcher, Intervene Immune

* Sajad Zalzala, MD , Co-Founder, Chief Medical Officer, AgelessRx

* Steve Horvath, PhD, Professor, University of California, Los Angeles

* Michael Geer, Co-Founder, Humanity.

Detailed bullet points from the talk (taken by me and reviewed by all panelists for accuracy): ___________________________________________________________________________ 1. We need to monitor people in trials AND out in the wild more frequently and on a wider amount of biomarkers
• [Kevin] We don't have enough data from healthy humans to describe normal human biology. Why haven't mass spectrometers, generally regarded as a "research" instrument, not been used to help people monitor their health? With a mass spectrometer, we measure a large number of biomarkers. He founded OpenCures to help ordinary people have access to research tools normally reserved for biotech and academia. • [Michael] His own company, Humanity, is following a similar direct-to-consumer path • We need to measure more biological clocks, including from plasma metabolites
• We need to expand methylation measurements • We should do more un-targeted assays - above and beyond the "standard clinical biomarkers"
• [Steve] It's important to have a variety of biomarkers, across various "omics" data. For example, methylation can be robustly measured, but it is not suitable for all interventions - and has multiple varieties, such as blood methylation , or skin, or fat, etc.
• [Steve] Some "omics" data can be very noisy. Their costs ought to be covered by NIH or other organizations funding basic research. • [Aubrey, Steve, Greg] To do good statistics on intervention treatments, it's critical to do a baseline measurement (or better yet 2+) prior to the treatment • [Greg] Baseline measurements - including the familiar "boring" biomarkers - also have helped some people discover health problems they didn't know about, such as poor renal function, early prostate cancer and pre-diabetes • [Kevin] OpenCures does assays for 85 proteins, including the "boring" standard ones normally prescribed by doctors (such as cholesterol.) • [Kevin] "You don't look at the blueprint of your car, to know how well it works! You take it to the smog check, and they measure it". In particular, not enough focus has been placed on the aging of the peroxisomes and cellular membranes. We haven't been able to measure metabolites easily in the past, but that has changed. • [Michael] We need to add more attention to direct-to-consumer methods to allow users to monitor their rate of aging. This includes digital biomarkers from wearable devices.
• We need more "omics" data - and ways to pool it
• [Kevin] The whole purpose of OpenCures is the creation of a collaborative database of multi-omics data. Anybody who has the ability to generate data that is human-relevant for aging : we should "throw it all into the pot" as much as legally possible. The data can be obscured to protect the subjects' privacy.
2. We need to give access to interventions to people and collect data on more interventions and combos
• [Steve] Cocktails of interventions may succeed where individual treatments don't. He works on biomarkers of aging. What the field really needs is one success story! We need to diversify the field - not just do the interventions that everyone has heard about (such as rapamycin.) Also, we need to experiment with interventions that have initially failed, but perhaps could succeed by combining them: "cocktails" could make all the difference. His perception of clinical trials is that people give up too early: by contrast, in basic research, if one fails, one just tries something else.
• [Greg] Aging requires a multi-prong approach. We did a trial recently that involved a cocktail, and the results may not have happened if we had just used one of those agents by itself. That are many pathways involved in aging, and you must target more than one, if you want a more comprehensive solution. We use growth hormone, DHEA and metformin. Our aim was to restore immune function. We need to regenerate the thymus; our research showed some promising signs in that direction. Steve's epigenetic clock, and other clocks - such as computing age from blood plasma metabolites - are all valuable. With InterveneImmune, he's collaborating with Steve. • [Sajad] Using telemedicine and other approaches so that people won't have to jump through too many hoops to try interventions, such as getting prescriptions for rapamycin. Now making the process easier, and also launching a clinical trial for rapamycin at various doses, and compared to placebo.
• [Michael] RWE (Real world evidence) and actually giving people the superpower of monitoring themselves and the effects of interventions will be a major new way of finding ways to slow aging.
• [Greg] Involved in the Health Span Initiative: an open observational clinical trial in the aging space. Help researchers run clinical trials.
3. We need to start collaborating and finding ways to allow all data to be leveraged to slow aging • Expand GenBank to pinpoint new biomarkers
• [Kevin] We need a multi-dimensional version of GenBank that can describe human health. Can we identify more biomarkers, not just the "standard" ones? How about all the rest - the undiscovered biomarkers, the "dark matter" of the field? We need to develop high-volume un-targeted assays to create a data resource, which we could then open to the world. Data data-sharing standards are especially important to that end. We need a way to submit data and have it validated. • Deal with issues sharing data : strategy & methods for new repositories • [Steve] NIH ought to lean on recipients of grants to urge them to make their data public. Open-access to data is NOT a new idea... and is required by many journals... but more could be done; sometime, it takes months to get the data, especially from government-funded agencies. NIH ought to deny grants to any groups that aren't forthcoming about sharing their data; there are some professors who don't want to share their data.
• [Kevin] Working with FASEB (the Federation of American Societies for Biology), working on developing common data standards for data sharing • [Michael] The use of federated learning and differential privacy can allow for privacy preservation of all data and still leverage it to save lives.
4. We need to learn from any failures and iterate more quickly • Investors need a long-term outlook : initial failure are to be expected. Every clinical trial is just an experiment. • For example, a strength of Silicon Valley is to embrace failures • Investors need risk diversification
• [Steve] The data from negative trial results ought to be made widely available as well.
• Clinical trials tend to "give up too quickly" whenever they encounter negative result #longevity #aging #healthspan #LifeExtension #conferences #medicine

Comments

Popular posts from this blog

Online Courses: (Often) Free and Just Awesome!

“Education is the kindling of a flame, not the filling of a vessel.” -Socrates.  [UPDATED Mar. 2021] Acquiring knowledge has been a hobby of mine since 4th grade, so it's no surprise that I'm the proverbial "kid in the candy store" when it comes to online courses!   As of writing, I have followed over 20 so far, and trying to decide what the next one will be... Utopia or Dystopia? You ever find yourself imagining the future, and wondering whether it'll turn out to be “utopian” or “dystopian”? Well, the state of higher education in the United States is decisively dystopian , with its absurdly ballooned costs and runaway student loans (a “bubble” that may burst sooner or later, mark my words!),  BUT there’s a counterpoint that is decisively utopian , namely the explosive rise of free online courses 😊 Here’s a brief 2012 Ted talk about the rise of free online courses , dated but still of interest. The gist of that TED talk is that online learning has com

Graph Databases (Neo4j) - a revolution in modeling the real world!

(UPDATED 9/2022) - I was "married" to Relational Databases for many years... and it was a good "relationship" full of love and productivity - but SOMETHING WAS MISSING! Let me backtrack.   In college, I got a hint of the "pre-relational database" days...  Mercifully, that was largely before my time, but  - primarily through a class - I got a taste of what the world was like before relational databases.  It's an understatement to say: YUCK! Gratitude for the power and convenience of Relational Databases and SQL - and relief at having narrowly averted life before it! - made me an instant mega-fan of that technology.  And for many years I held various jobs that, directly or indirectly, made use of MySQL and other relational databases - whether as a Database Administrator, Full-Stack Developer, Data Scientist, CTO or various other roles. But there were thorns in the otherwise happy relationship The root cause: THE REAL WORLD DOES NOT REALLY RESEMBLE THE

D3 Visualization with Vue.js : a powerful alliance (when done right!)

[UPDATED MAY 2022]  D3.js is a very powerful visualization tool, especially for specialized/custom needs...  On the flip side, it's rather hard to use - with a steep learning curve. Even worse if one also wants interactivity ! But why is D3 so hard/clunky to use?  And what can be done about it? Spoiler alert: Vue.js (or other modern front-end framework) to the rescue - if done right... All code in the examples is available in this GitHub repository . The Root of the Problem In a nutshell, what makes D3 awkward to use is that, for historical reasons, it tries to do too much : most painfully, it uses an old way to do direct DOM manipulation (i.e. restructuring the page layout) - an operation that nowadays is superbly handled in a far more friendly way by modern front-end frameworks, such as Vue.js Document Object Model ( DOM ) is a programming interface for web documents.  In simple terms, it's the structure of the elements on a web page (text, images, etc.) Let the front-e

A "Seismic Shift" in Longevity Science : Mainstream Acceptance + Large Funding

"You are incredibly prescient!"   I woke up to those words from a former colleague on Jan. 19, 2022: the bombshell announcement that the Chief Science Officer of pharma giant GSK, where I worked until recently, will become the CEO at the new, $3 BILLION longevity science company Altos (presumably also funded by Amazon's Jeff Bezos.) Big Pharma is at long last embracing Longevity Science. The corollary: longevity science is entering Mainstream (with capital "M") But let me backtrack... The Decade of Longevity Science When Harvard professor David Sinclair declared the 2020's to be the " decade of the paradigm shift about age reversal ", one could perhaps be dismissive of it as just an outburst of enthusiasm... But in the past couple of years, we're seeing strong evidence that his forecast is right on the mark! While I worked at GlaxoSmithKline - a giant, top-10, pharma company - I vigorously advocated forming a Longevity Science dept., and sp

Life123 : Quantitative Modeling of Biological Systems

(UPDATED 8/2022) - Are we ready to embark on a next-generation detailed quantitative modeling of complex biological systems , including whole-cell simulations?  An anticipated up-jump in computing power may be imminent from Photonics computers (which I discuss here ), and GPU's are rapidly gaining power as well...  Are we in ready state to put existing - and upcoming - power to good use? This is a manifest, and a call to action What's Life123? It's about detailed quantitative modeling of biological systems in 1-D, 2-D and full 3-D, as well as a multi-faceted software platform for doing so. What's (pseudo-)1D?  For now, let's say it's like the inside of a long, thin tube - with no interactions with the tube.  Likewise, (pseudo-)2D can be thought of as a Petri dish, with no interactions with the lid or the bottom. Website : https://life123.science A purposeful decision to also utilize 1D and 2D But why?  Yes, it's in part about "walk before you run&quo

Multimedia Knowledge Representation and Management : "Brain Annex"

 (Updated Feb. 2022) Wouldn't it be fantastic to have a "butler" to help us as we constantly face drowning in information? That need was crushingly pressing for me , as a polymath with a thirst for knowledge in several fields, not to mention numerous very technical jobs over the years, several complex research projects, old notes from college and grad school, an endless stream of online courses I take , a tech startup I founded and used to run, the many conferences I attend, life in general, and even hobbies that tend to generate abundant information (such as flying airplanes and studying multiple foreign languages!)   I was immensely eager for some sort of powerful assistance, something so helpful that I could poetically describe as an " annex " to my brain.. In this blog entry, I'll describe how deep frustration with existing software tools led to the start of the open-source BrainAnnex.org project, a web-based knowledge representation and manageme

Anti-Aging Research: Science, not Hype

Last updated November 2021 Q: "How is aging a disease?" A: "It's a dynamic system that veers away from its homeostasis (normal equilibrium point): hence a form of slow-progressing illness. Labeling it as 'natural' is a surrender to our traditional state of ignorance and powerlessness, which fortunately is beginning to be changed!" The above is my standard answer to an oft-asked question. The science of aging is by all evidence very misunderstood by the general public.  Hype, misinformation and unquestioned assumptions often prevail, unfortunately. Aging as a systemic breakdown of the body, rather than a series of isolated events and conditions. This 2013 diagram from NIH is a good way to jump-start contemplating the big picture: The diagram originates from the Cell journal: The Hallmarks of Aging   Telomere shortening is perhaps the one most talked about - but just one of several processes.  As stated in the above paper: Each

Interactomics + Super (or Quantum) Computers + Machine Learning : the Future of Medicine?

[Updated Mar. 2021] Interactomics today bears a certain resemblance to genomics in the  1990s...  Big gaps in knowledge, but an explosively-growing field of great promise. If you're unfamiliar with the terms, genomics is about deciphering the gene sequence of an organism, while interactomics is about describing all the relevant bio-molecules and their web of interactions. A Detective Story Think of a good police-detective story; typically there is a multitude of characters, and an impossible-to-remember number of relationships: A hates B, who loves C, who had a crush on D, who always steers clear of E, who was best friends with A until D arrived... Yes, just like those detective stories, things get very complex with our biological story!  Examples of webs of interactions, familiar to many who took intro biology, are the Krebs cycle for metabolism or the Calvin cycle to fix carbon into sugars in plant photosynthesis. Now, imagine vastly expanding those cycles of rea

Brain Microarchitecture : Feedback from Higher-order areas to Lower-order areas

Some questions that arise in Machine Learning involve the prospect of using feedback from Higher-order areas (downstream) to Lower-order areas (upstream), and using Global Knowledge for Local Processing.  A desire to gain insight into those issues from Neuroscience ("how does the brain do it?") led me to some fascinating investigations into the Microcircuits of the Cerebral Cortex.  This blog entry is a broad review of the field, in the context of the original motivating questions from Machine Learning.   Starting out with a quote from the “bible of Neuroscience”: From Principles of Neural Science, 5th edn  (Online book location 1435.3 / 5867).  Emphasis and note added by me: Sensory pathways are not exclusively serial; in each functional pathway higher-order areas project back to the lower-order areas from which they receive input. In this way neurons in higher-order areas, sensitive to the global pattern of sensory input, can modulate the activity of neurons in lowe

Photonic Computer - a "supercharged GPU" with very low energy consumption

Yes, we all wish for Quantum Computers... but in the meantime we need something here and now!  Could Photonic Computers fit that role? Just about everyone has heard of fiber optics – using light for data transmission – but did you know that light can also be used for computing? There's a new commercial product expected for early next year (2022) . I contacted the CEO, Nicholas Harris, of a 4-y.o. startup, Lightmatter , interviewed in April 2021 here . Photonic computers, at least in their first commercial appearance, are essentially accelerator cards for Linear Algebra - and so of special interest for Machine Learning and some types of simulations.    Their claims are remarkable: 10X faster than some of the best GPUs using 90% less energy can be used with existing software stacks, such as TensorFlow commercially available early next year (2022) a lot of future growth, as additional wavelengths of light get used in parallel My own interest is pr