Hacking Aging with AI

GERO.AI uses Whole-Exome Sequencing data for in-human AI Drug Discovery, while GeroSense is the arm of Gero creating Digital Biomarkers. GERO.AI models are taken from the physics of complex dynamic systems. They have presented their unique approach in the journal Frontiers in Genetics. They combine deep neural networks with the physical models to study dynamical processes and undersend what drives a disease.

Currently, biopharma and gene editing is curing single gene diseases called monogenic diseases. Those are a substantial market of about $60 billion. However, our main health problems are from more complex diseases and going beyond and cracking aging will be even more complex.

Monogenic diseases will be extinguished by genetic therapies. Most of us will suffer from much more prevalent and lucrative complex diseases, those that are not caused by a single gene.

Common Gene Variants (FREQUENT MUTATIONS or SNPs) cover only 0.5% of the whole genome length. They are mostly responsible for hair and eye color, height, ancestry. Whole-Exome (and eventually GENOME) Sequencing reveal rare mutations, with Gero technology they can discover ideas for drugs in the remaining 99.5% of the genetic.

GERO.AI has successfully identified and validated a human target for treating senescence-associated disorders and aging. They achieved systemic rejuvenation in experiments with 100-weeks old animals by intervention vs. protein predicted by the AI. Their discovery is even a little better than the antiaging drug Rapamycin.

A Gero co-founder, Peter Fedichev, published a study that counts blood cells and footsteps to predict a hard limit of 120-150 to longevity unless there is intervention. They created the dynamic organism state indicator (DOSI).

GERO did a systematic investigation of aging, organism state fluctuations, and gradual loss of resilience in a dataset involving multiple Complete Blood Counts (CBC) measured over short periods of time (a few months) from the same person along the individual aging trajectory. Neutrophil to Lymphocyte Ratio (NLR) and Red cell distribution width have been already suggested and characterized as biomarkers of aging. Instead of focusing on individual factors, to simplify the matters, they followed and described the organism state by means of a single variable, henceforth referred to as the dynamic organism state indicator (DOSI) in the form of the log-transformed proportional all-cause mortality model predictor.

The average line demonstrates nearly linear growth after age of 40. In younger ages the dependence of age is different and consistent with the universal curve suggested by the general model for ontogenetic growth. Looking at many people they have found that key aging really starts at 40.

In the most healthy subjects, i.e., those with no diagnosed diseases at the time of assessment, the DOSI predicted the future incidence of chronic age-related diseases observed during 10-year follow-up in the UB study.

They have an app gerosense analyzes acceleration patterns and provides insight into health changes. They use the app to provide data, development and tracking for the DOSI aging indicator.

SOURCEs- Gero, Nature
Written By Brian Wang, Nextbigfuture.com

6 thoughts on “Hacking Aging with AI”

  1. Listen, there are now a huge number of developers and reliable development companies that provides quality services for startups. In general, I suggest you start a new project with kindgeek.com, as this is a really trusted company that I have already worked with. And in general, the reviews for these developers are very positive.

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  2. It all hinges on the idea of how much of your original parts/processes do you want as you move past typical maximum-life expectancies of at least 20%, so 85 to 95 YO?
    – 75%+ original parts but super-accelerated healing/recovery (based on 5% of your income and 5% of your time per year for the ongoing procedures) – maybe 120 years max in the next 150 years of anti-aging development
    – 50%+ original parts but latest replacement organs/ nano-fixers (based on 10%
    of your income and 2% of your time per year for the ongoing procedures)
    – maybe 150+ years max in the next 150 years of anti-aging development
    – your mind/ memory and at least all of your sensory input (huge chunk of money one-time and just the maintenance on your hub, various sensor arrays, and if desired, your exo-body-form when wanting to get out there.

    All this tech will do is confirm humanity's basic frailty and diminishing physical
    existence with time – repair plan or upgrade??

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  3. Maybe. But recall how IBM's Watson was supposed to replace human doctors for diagnosis and deliver individually targetted cancer treatments? Basically that was hype.

    OTOH, Watson has probably (almost certainly) fallen behind other AI work by this point, so maybe this time will be different.

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  4. What does HR mean in the ordinate of the graph in the thumbnail? It does not seem to be explained in the article, so it must be a standard indicator?

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  5. Medicine, longevity science super fast becoming information tech and from now it will progress at least exponentially (thanks to narrow AI most likely much faster- at double exponential rate). If we figure out AGI or ASI(automate intelligence and be able to "mass produce" or copy ASI's with 10 000IQ nonillions of times) we will grow at at last triple exponential rate

    This is most relevant for us mortals, more than Mars cities, rocketry, fast EV cars, crypto, blockchains and other stuff. If we die there's no point in all of that, these are just brief entertainment for masses.

    On the other hand, if we solve aging we could have indefinite time to enjoy all these developments + much more futuristic/advanced tech in the future.

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