AIs helped discover an affordable anti-aging cocktail that reverses your age by up to seven years

A team of researchers claims to have had a major breakthrough in anti-aging developments, thanks to AIs capacity to see patterns at scale. Their paper was posted on Aging-US. The team includes researchers from Harvard, with contributions from MIT, Moscow State University, Cambridge and University of Maine.

David Sinclair made the announcement over Twitter.

Grateful to share our latest publication: We’ve previously shown age reversal is possible using gene therapy to turn on embryonic genes. Now we show it’s possible with chemical cocktails, a step towards affordable whole-body rejuvenation.

The team is looking at a cocktail of chemicals that would rejuvenate kidneys, muscles, the optic nerve and brain tissue.

Sinclair said the tests on mice showed improved vision and extended lifespan in mice, and improved vision in monkeys. The chemicals are supposed to visibly reverse signs of aging in less than a week. If true, feeling younger wouldn’t involve procedures under the knife or invasive surgeries. It would just be a matter of swallowing a pill.

The research itself isn’t yet peer-reviewed and is a long way away from human trials. Still, Sinclair is confident in the reprogramming of various tissues without them becoming cancerous. This has previously been a thick wall to break through. The rejuvenation itself has been possible for quite some time now but got a notable side effect. Cells grow uncontrollably and cause various types of cancers. Sinclair says this is no longer the case. According to him, his mice had a longer lifespan under the effects of his cocktail.

The Hallmarks of Aging

Numerous processes, known as "hallmarks of aging," contribute to the deterioration and failure of cells as they age. Evidence from a variety of species supports the idea of a reduction in epigenetic information. This leads to changes in gene expression and culminates in the loss of a cell's identity.

Young cells divide to repair wounds, remodel tissue and avoid cancer. When the cells gets old, a process called cellular senescence happens, by which cells stop that cycle completely. This state of senescence is linked with transformations in the cell's shape, the organization of DNA, and the release of inflammatory factors. The shift to cellular senescence can be sparked by a loss of epigenetic information, the shortening of telomeres (the protective ends of chromosomes), irreversible damage to DNA, and the presence of DNA within the cell's cytoplasm.

As people age, the buildup of senescent cells leads to inflammation and the creation of reactive oxygen species (ROS) throughout the body. According to The Information Theory of Aging, the decrease in information triggers a chain of events: mitochondrial failure, inflammation, cellular senescence. They contribute to a steady deterioration in cell and tissue function. It manifests as aging and the illnesses that accompany it.

The chemical cocktail has senolytic compounds - drugs that target aging cells. They are supposed to selectively kill cells that are no longer dividing, without affecting the young cells that function normally.

It consist of a combination of five to seven agents, some of which are already prescribed for the treatment of various physical and mental disorders (seizures, depression, and Parkinson's disease).

AI Sees Patterns at Scale

The research shows how artificial intelligence (AI) may be used to find novel senolytic chemicals. The AI analyzed over 800,000 compounds. It found three candidate medicines that outperformed the senolytics now under research by laboratories

“This research result is a significant milestone for both longevity research and the application of artificial intelligence to drug discovery,” said Felix Wong, Ph.D., co-founder of Integrated Biosciences and first author of the publication. “These data demonstrate that we can explore chemical space in silico and emerge with multiple candidate anti-aging compounds that are more likely to succeed in the clinic, compared to even the most promising examples of their kind being studied today.”

While many senolytic compounds have shown encouraging results in clinical trials, their effectiveness has been limited due to poor absorption in the body and unwanted side effects. To address these challenges, the researchers aim to focus on overlooked aspects of aging. In their research, they leveraged artificial intelligence and synthetic biology to push development.

Artificial Intelligence has a remarkable capacity to see patterns at scale.

AI systems can process vast amounts of data much faster and analyze large datasets in a fraction of the time. With the new developments, systems learn from the data they process, so their results are a lot more refined as they work longer. They identify patterns and correlations in the data, and use these insights to make predictions or decisions without being explicitly programmed to perform the task.  AI can simultaneously analyze data across multiple dimensions, identifying patterns that might be missed when data is analyzed from a single perspective. This makes AI a powerful tool in medical research.

These are by no means definitive results or even in a reliably-optimistic stage of discovery.