The role of Artificial Intelligence in extending health span

By Calum Chace | 11 March 2022
Calum Chace

(Credit: Dreamstime.com)

“Not proper science”

The field of longevity medicine is coming alive. Until the last few years, the project of halting and reversing aging was not seen as “proper science”, and not a fit use for public funds. Aging was seen as an inevitable and permanent part of the human condition. It was not a disease, but a vulnerability to disease which grows over time, and cannot be redressed. People who argued the contrary were viewed by the medical establishment as entertaining mavericks at best, disreputable charlatans at worst.

The sneering has not entirely disappeared, but today there is significant investment in tackling aging itself, not just the diseases which emerge with age, like cancer, heart attacks, and Alzheimer’s. The medical profession is engaging too, albeit cautiously: after many years of trying, funding and approval has been obtained for the TAME project, which stands for Targeting Aging with Metformin. Metformin is a drug approved 60 years ago for the treatment of diabetes, and TAME consists of phase III clinical trials of metformin to delay aging. The impact on aging is not expected to be massive, but the drug is known to be safe, and the project is at least partly an exercise in persuading the FDA, and the profession at large, to take aging itself more seriously.

In the last couple of weeks, a potential game-changer has emerged. The crypto currency community includes quite a few billionaires. Some of them are convinced that aging can be arrested and reversed, and they are starting to put serious money behind this belief. Richard Heart is an influential if controversial figure in the crypto community, and he has launched an “air drop”, a co-ordinated programme of major donations to SENS, a longevity research and campaigning organisation. In the first few days after Heart’s announcement, SENS received over £20m of donations, which is four times its annual budget. It is too early to be sure, but Heart’s air drop could be an important moment in the fight against aging.

AI and aging clocks

Part of the reason for the change in attitudes towards aging is the application of modern artificial intelligence techniques to healthcare, and in particular, deep neural nets and reinforcement learning. Neural networks are algorithms which process data in layers, each layer taking data from the previous layer as an input, and passing an output up to the next layer. The outputs are not necessarily binary (just on or off), but can be weighted. Reinforcement learning algorithms adjust their approach according to feedback from their environment.

One of the contributions AI is making to anti-aging science is the development of aging clocks. Aging clocks help us study what causes aging, and how to address it. In 2013, Professor Steve Horvath persuaded a sceptical world that bio-markers at 353 sites on the DNA strand could “predict” (estimate) a person’s age accurately. The causal connections between the indicators and the person’s age is not yet clear, but leading AI healthcare researcher Alex Zhavoronkov says that when you train an AI to predict age on certain types of biological data, it learns biology. The hope is that over time, these AIs will help us better understand how aging works.

AIs will analyse the oceans of data we collect about our health, including time series (longitudinal) data and comparative data across social and national groups. The patterns it reveals in the data will suggest hypotheses to test. The aging clocks will show the effectiveness of treatments – or the lack thereof. As the old saying goes, what you measure is what you get: clinicians must demonstrate that their therapies work.

Alex Zhavoronkov and his colleagues have developed aging clocks that use AI to analyse data from various other sources, including blood tests. His company Deep Longevity, recently acquired by Hong Kong-listed Endurance Longevity, develops and commercialises these clocks.

Zhavoronkov also founded Insilico Medicine, which is another example of how serious money is now targeting the use of AI to understand and combat ageing: it has just raised $225m in a funding round that reads like a Who’s Who of prestigious financial, biotechnology, and AI investors. Their confidence is based in part on Insilico’s ability to identify promising drug candidates for novel or difficult protein targets in a range of pathologies, including chronic and age-related diseases. Recently, the company announced it had reached pre-clinical candidate stage with a novel drug to treat idiopathic pulmonary fibrosis (IPF), a disease which scars the lungs. Insilico’s AI tools enabled the company to squeeze into 18 months and $2.7m a process which normally takes several years and hundreds of millions of dollars.

Zhavoronkov uses an additional type of AI called generative adversarial networks (GANs), in which two AI systems compete. One generates new data, and the other, called the discriminator, evaluates these candidates.

AI monitoring and agents

David Wood, the author of “The Abolition of Aging”, gives an example of how AI can provide early warning systems. NHS Scotland is using a system developed in Seattle to monitor patients with Chronic Obstructive Pulmonary Disease (COPD), one of the top five causes of death worldwide. The system, which alerts doctors to any sign of deterioration in a patient’s condition, was trained on three years of data from breathing assistance machines, patient diaries, and hospital records.

Researchers are increasingly using AI to help identify and develop new drugs. And looking further ahead, we will have personalised AI agents that study the idiosyncrasies of our bodies – our genetic makeup, our microbiomes, and so on. They will coach us and nudge us to modify our behaviour, including our diet, exercise and sleep. They will develop digital twins, virtual models of each of us as individual and unique organisms.

The prize

From the first appearance of our species until around three hundred years ago, a human baby could expect to live for around 35 years. In the last three centuries we tackled the diseases of youth and infection, using hygiene, vaccines, and antibiotics. Life expectancy at birth – globally – is now around 73. But we have made far less progress with the diseases of age. Today, most of us die from cancer, heart failure, and dementia. Solving any one of these would be wonderful, but would still leave us exposed to the others. We need to solve aging itself, and we cannot do this until the medical establishment and its funding bodies take the problem seriously.

The best-known pioneer of anti-aging is the British scientist Aubrey de Grey, who founded SENS, the organisation that is benefiting from the crypto air drop. De Grey started his career in AI before deciding that tackling aging was even more important than harnessing artificial intelligence. He has long championed the idea that it will soon be possible for medical science to give us all a year’s additional life each year that passes, so that most of us would effectively stop getting older. He calls this Longevity Escape Velocity, and with the sea-change in attitudes that is under way, he now thinks there is a 50% chance of achieving it by 2035. Perhaps his most startling claim is that the first human to live to 1,000 years has probably already been born. He forecasts dramatic, and perhaps turbulent, impacts on our culture when a lot of people start taking this idea seriously.

What is aging?

There is no firm consensus about the nature of aging, but it can be described as the cumulative impact of our metabolism on our bodies. Metabolism is the process of converting food into energy, and into the materials we need, like proteins and other molecules. It is also the process of expelling various kinds of waste.

De Grey offers the metaphor of a car. Over time, the combustion of fuels, the process of oxidation, and the jostling contacts with roads, rain, and wind causes damage to a car which must be repaired by mechanics. We minimise the damage to cars by maintaining their fluid levels and tyre pressures, and we repair them by replacing any parts which fail or rust.

The damage to our bodies caused by metabolism must be addressed on a much smaller scale, at the cellular level. De Grey has argued for a couple of decades that aging is caused by seven types of cellular damage. Some cells get stiff, and others wither; some replicate when they shouldn’t, and others stop replicating when they should. Some suffer from mutations in the tiny batteries within their nuclei (their mitochondria); others get cluttered up with junk, both internally and in the spaces between them. De Grey argues that we have long known the broad outlines of how to redress all these seven kinds of damage, but the devil is in the detail, and the detail is formidably complex. Unravelling this complexity is where AI can help.

Lifespan and health span

Some people argue that the important objective is not extending lifespan, but extending health span, the period we live free of illness. They point out that the reduction of mortality in the last half century in particular has dramatically increased the financial burden on developed countries by extending lifespan without a corresponding increase in health span.

In truth these objectives are mutually supportive, not mutually exclusive. Extending health span without extending lifespan means failing to tackle the root cause of the diseases of aging, which is aging itself.

The long and the short of it

As with all discussions about the impact of AI, it is important to remain realistic about the timescales. We are still only at the beginning of our AI journey, and we are a very long way from a full understanding of how to halt and reverse the mechanisms of aging. But AI is advancing at an exponential rate, and that type of improvement produces astonishing results over periods of a decade or two.

Meanwhile, the healthcare advice to all of us remains essentially what our grandmothers told us. Tina Woods researched her book “Live Longer With AI” by interviewing 30 science and technology pioneers, and she reports their advice as consistent and straightforward. Eat well, and not too much. Exercise regularly, and sleep well. Make sure your life is guided by a purpose, and enhanced by solid friendships. If you do this, and you are young enough, you may live to a very ripe old age indeed.

Reprinted with permission from the author.

Calum Chace is an English writer and speaker, focusing on the likely future impact of Artificial Intelligence on people and societies. He became a full-time writer in 2012, after a 30-year career in business. He is the author of Surviving AI, The Economic Singularity, and the philosophical science fiction novel Pandora’s Brain.

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