By cutting through the time it takes to analyze a vast amount of data, artificial intelligence can help researchers develop products much more quickly, Smith says.
Life Extension, for instance, used AI to create the aforementioned cellular senescence supplement, whittling down the list of 70 potential nutrients to four final ingredients in the product. “If I were doing that research myself in a lab, [the product’s creation] would be decades away,” he adds. “We sped up time using AI technology by at least a couple of decades.”
Life Extension worked with medical technology firm Insilico Medicine Inc. (Rockville, MD) and Insilico’s artificial intelligence technology, which the company uses for drug, biomarker, and aging research.
AI is also helping Life Extension better determine which ingredients to study moving forward. Without the guidance of AI, Smith says, “It would take decades to actually study whether a group of nutrients actually had longevity effects at the cell level—and then ultimately at the organism level. You’d have to follow people for a very long time.”
He continues, “Let’s say I wanted to test whether resveratrol has an antiaging effect on a certain population of patients with diabetes. Well, that would require a huge study, millions of dollars, and many years. And we might not even know if we’d get a positive result. We’d have a hypothesis, but we would have to invest a lot really not knowing what the outcome would be. But what AI allows me to do is, I can put a lot of this information into an AI engine that then can almost run simulations of these trials, and I can get an idea of whether it would be worth it to invest money in an actual trial” because AI can indicate which research might yield positive results.
For instance, he says, “Maybe the engine comes back and says, ‘Well, resveratrol in that population might not have that effect; however, if you studied it in people with heart failure, it would tell us the pathway to go down where we could be the most effective. That’s really exciting.”
The ability to better determine where to invest research dollars is especially important to the nutraceutical industry. While drug makers have millions of dollars to invest in clinical research, nutraceutical researchers have much smaller budgets; therefore, being able to better utilize those research dollars is extremely beneficial, Smith says. AI, he says, is “actually helping us be very effective with our research money.”
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