Advancements in AI: Expert points to opportunities in anti-aging and gene treatment

05 Sep 2023 --- Companies are increasingly recognizing the potential of AI in product development, and New Zealand-based biotechnology company Science Research Wellness (SRW) links the technology to cellular health, while highlighting the potential of AI in gene treatment and anti-aging products.

In this second of our two-part series, Nutrition Insight speaks to Greg Macpherson, SRW’s founder, on the latest developments in the field, how he expects it to develop and what role AI can play in product development.

Last week, Macpherson explained how AI can accelerate the search for anti-aging pathways and molecules to modulate these processes. SRW also works with DNA methylation tests to determine a person’s biological age, an approach supported by AI’s capacity to process large and complex data sets.

“We know diet, exercise, lifestyle, sleep and meditation etc., moves biological age backward through the DNA methylation test,” he explains. “The next layer is the drugs coming to market that affect aging. Lifestyle might give us ten years. The new drugs that are coming may give us another ten years.”

AI in genetics
Macpherson explains that AI could rapidly accelerate gene treatment by identifying which genes need to be addressed to resolve an issue.

He expects that with AI, researchers can make models to determine the downstream consequences of changing a gene to ensure “we don’t inadvertently mess things up through secondary genes, for example.”

AI could rapidly accelerate gene treatment, by identifying which genes to address.“Then we get into understanding and learning from nature,” Macpherson continues. “From long-lived animals with exceptional longevity, we’ll be able to pick up the key differences causing that longevity; that will be the next gateway for us to change our aging. Their biological clock ticks slower than ours.”

“Once we understand what’s driving that, we can then adopt that into our genome. This is what AI will deliver for us in this area.”

Recently, scientists posited an anti-aging solution based on immortal regenerating sea creatures.

“Pace of aging clocks”
Macpherson notes that models for AI and machine learning are advancing rapidly. He adds that biological age clocks – DNA methylation patterns – have also progressed substantially, as first-generation clocks were limited. “They might have told you your biological age but not what it means regarding outcomes.”

The third generation clocks are “pace of aging clocks.” These determine a person’s biological age and estimate the progress of aging up to a certain point in time.

“A new clock that will be available to the public soon takes it one level further by looking at all the biomarkers associated with aging and certain diseases and then maps those to the DNA methylation patterns,” Macpherson underscores.

“Then we’ve got this incredible, one blood drop test, which gives us a ballpark indication of how we’re [aging in time]. That’s where it’s starting to get interesting because we can intervene before it becomes a problem.”

Molecule discovery
Macpherson highlights that machine learning found that several molecules with known health benefits, such as vitamin D, impact biological age.

In the last five years, research has pointed to several molecules that weren’t particularly common, such as NAD+ precursors or alpha-ketoglutarate. “These molecules are examples of what’s coming in quickly.”

Greg Macpherson, founder of SRW (Image credit: SRW).AI has also identified metabolites, where the body takes a particular precursor and adds elements to it to make it a metabolite. “Sometimes those metabolites are more potent or more effective than a precursor. AI is helping us identify what those molecules are.”

“This means that we’ll have access to molecules which our body already has, if for some reason we are deficient in a particular metabolite or a pathway is not working optimally, we can take these compounds.”

From nutraceuticals to drugs
Although nutraceuticals are not authorized to make medicinal claims, Macpherson underscores that companies can develop new products based on a deep level of science and proof through AI. “The level of understanding of what’s working and what’s not will mean that consumers will have products they’ve never had access to.”

“I like to think of nutraceuticals as a good place to start, where we’ll learn much about what these molecules can do to slow the aging process. We know we can do it; it’s just how much we can slow it down.”

He estimates that pharmaceuticals will be the next generation, making a better version of a nutraceutical. It might be that nutraceuticals hold 70% of the effectiveness of a pharmaceutical on the same pathway, highlights Macpherson.

“But we can deliver it now rather than wait ten years to validate that that molecule is safe as a pharmaceutical.”

He shares an example of rapamycin, a drug that slows aging in various tests, though it has not been confirmed yet in humans. When researchers used AI to screen compounds to find a natural component similar to this drug, withaferin A – a molecule found in the adaptogen ashwagandha – was one of the leading candidates.

“This will open up so many opportunities to learn which of these natural molecules will interact with the various pathways associated with aging.”

Macpherson highlights there still is much to learn about genes and anti-aging pathways.Learning to live longer
Macpherson highlights that there still is much to learn about genes and anti-aging pathways. “We’re about to go through 20 years of incredible learning and insight, meaning we live considerably longer.”

“The modern lifestyle doesn’t suit our biology,” he argues. “We’re modern humans with aging bodies. We are built to move, and we’re not built to consume much sugar and carbohydrates.”

“By 2050, we’ll have two billion people over 60. We can’t afford to do what we’re doing right now regarding the health system. We’ve got to work out how to do preventive medicine, and it loops back to AI, which will get us there.”

SRW also looks into how cellular health interplays with the microbiome, though Macpherson expects it will take longer to unpack.

“AI will give us insight into where we are, looking at the challenges we’ve got and potentially map that back to the microbiome,” he concludes.

By Jolanda van Hal

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