Humanity and AI will master aging in future: Expert

Aging is something most of us will undergo as the years progress. With aging comes debilitating diseases which can make aging a very expensive and undignified experience for many people. But scientists are trying to come up with mechanisms that will not only slow down the aging process but also allow people to age well and smoothly. Read on to find out more about this exciting process.

Updated Mar 10, 2023 | 02:49 PM IST

Find out how humanity and AI will master aging in future
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Ageing is inevitable and so are the problems and diseases associated with ageing. Nobody wants to grow old and humans have been studying hard to reverse or at least slow down the process. They have also been studying on how to minimise the ailments and other problems that come along with ageing.
Modern medicine recognises ageing as a set of diseases. It also claims that by using the tools of artificial intelligence (AI) we can not only slow down the aging process but will also be able to protect ourselves against aging and age-related diseases. This according to experts is possible because of the revolutionary ability of AI to aid the identification of compounds with anti-aging properties.
Kirsten Fortney a postdoctoral researcher at Stanford University has used bioinformatics to study the genetics of supercentenarians i.e. people who live up to the age of 110 and beyond.
Fortney is now at the forefront of biotech efforts to turn longevity science knowledge into medicine. Fortney is the CEO and co-founder of BioAge , a clinical stage biotech developing a pipeline of treatments to extend healthy lifespan by targeting molecular causes of aging.
About her research Fortney says that aging is a good target to address the greatest number of people through medical innovation. She says that aging biology is a unique lever point to delay the incidence of multiple diseases hitting the human body at once, and longevity science has arrived at the point where it is ready to start translating knowledge into therapies.
Aging is the primary cause of many chronic diseases, including devastating illnesses like cancers and Alzheimer’s. Scientists are now confident that science and technology have advanced to the point that they can do something about it and claim to have discovered multiple interventions that can increase healthy longevity in animal models, showing that human healthspan can be extended. At the same time, technological progress has given us unprecedented understanding of human aging, as well as the ability to translate this knowledge into therapeutics. Targeting aging will enable us to treat disease in entirely new ways.
According to Fortney BioAge takes a “human data first” approach to understanding aging, learning about the underlying mechanisms of healthy longevity from humans who are already aging well. People age at different rates — some die of an age-related disease in their 50s and 60s, whereas others live into their 90s and beyond in good health.
She further adds that they use AI and machine learning to analyze the distinctive molecular features of people who live the healthiest, longest lives, and then use that knowledge to develop therapies that could help everyone age more successfully. Because we’re using modern technologies to get a comprehensive molecular picture of aging, we are able to discover many different aging mechanisms, rather than being limited to a handful of targets chosen in advance.
Incorporating AI into your drug pipeline
Fortney says that AI and ML are the key technologies that enable us to pinpoint the molecular differences that predict healthy versus unhealthy aging. Our discovery process begins with our aging cohorts — precious samples collected from thousands of people over decades — coupled with detailed records of their health and mortality, which we access through exclusive partnerships with unique biobanks around the world.
Each sample is analysed using modern omics technologies, measuring tens of thousands of proteins, RNAs, and metabolites. AI and statistical techniques are used to sift through subtle patterns and identify the biological pathways and molecular factors underlying healthy longevity. The aim is find those who age more gently. The proteins that play key roles in these pathways become our drug targets.
How will BioAge’s approach to developing therapeutics slow down or prevent age-related disorders?
Because diseases inevitably occur alongside therefore a central aspect of our approach is discovering pathways which, when they’re active in certain ways, result in a healthier person. So, drugs aimed at these mechanisms have the potential to be curative for some diseases and also slow or prevent them, Fortney says.
How is machine learning methodology applied into studies?
Fortney says that they believe in learning as much as possible from their clinical trials, not only about the primary indication but also about aging itself. This is achieved by using biomarkers that we build with our machine learning approach. BioAge recently completed a successful Phase 1b trial of the lead drug in their muscle aging program. The drug, BGE-105, mimics the effects of apelin, a small peptide that plays important roles in muscle regeneration. The aging cohorts revealed that people with higher activity in the apelin pathway lived longer and maintained better muscle and cognitive function as they aged. In the trial, BGE-105 prevented muscle atrophy in people over 65, and this has implications for a large number of medical conditions with high unmet need.
The importance of preventing muscle atrophy
Muscle atrophy decreases mobility, robbing older people of their autonomy and dignity, and often forcing them to become dependents. In addition, declining muscle function compounds the risk of falls, which are a major cause of accidental death in older people. Frailty affects a large section of the population over 65, and some degree of muscle atrophy is a nearly universal aspect of aging. But despite its prevalence, we have no effective treatment, so this is an enormous unmet medical need that we are hoping to address with our clinical programs.
What about brain aging, what do your studies show so far
Like muscle loss, cognitive decline is a nearly universal aspect of the aging process, and can range in severity from mild memory impairment to severe illnesses like Alzheimer’s. Fortney says our ML analyses of our aging cohorts revealed multiple pathways that play important roles in brain aging. For example, higher activity of a cellular machine called the NLRP3 inflammasome was correlated with more rapid decline in cognitive function with age. This implied that if we could decrease inflammasome activity, we could slow some aspects of brain aging and treat or even prevent age-related neurological diseases.
Fortney added that “Human data and human samples are central to everything we do at BioAge. However, human aging takes a long time, so we need some way to follow aging in individuals that doesn’t require us to wait 80 years to collect our data. We solved this problem by establishing exclusive partnerships with multiple aging biobanks, which contain samples collected longitudinally from healthy people over decades of follow-up. These resources provide invaluable insight into the molecular bases of healthy longevity.”
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