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Artificial intelligence identifies new anti-aging compounds

A recent study led by Integrated Biosciences – a biotechnology company founded in 2022 that combines synthetic biology and machine learning to combat aging – has shown the potential of artificial intelligence (AI) to discover new senolytic compounds. These are a class of small molecules with the capacity to suppress age-related processes such as inflammation, fibrosis, or cancer. 

By using AI to screen over 800,000 compounds, the experts discovered three highly efficient drug candidates with superior medicinal chemistry properties than currently known senolytics.

“This research result is a significant milestone for both longevity research and the application of artificial intelligence to drug discovery,” said co-lead author Felix Wong, the co-founder of Integrated Biosciences. 

“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.”

Senescent cells are known to be involved in a wide variety of age-related diseases such as diabetes, cancer, Alzheimer’s disease, and cardiovascular disease.

Senolytics are a type of medicines selectively inducing apoptosis (programmed cell death) in senescent cells that no longer divide. However, most of the previously identified senolytic compounds are hampered by poor bioavailability and undesirable side effects.

“One of the most promising routes to treat age-related diseases is to identify therapeutic interventions that selectively remove these cells from the body similarly to how antibiotics kill bacteria without harming host cells. The compounds we discovered display high selectivity, as well as the favorable medicinal chemistry properties needed to yield a successful drug,” said co-lead author Satotaka Omori, the Head of the Aging Biology department at Integrated Biosciences. 

“We believe that the compounds discovered using our platform will have improved prospects in clinical trials and will eventually help restore health to aging individuals.”

To predict the senolytic activity of a wide range of molecules, the scientists trained deep neural networks on experimentally generated data.

By using this machine learning model to screen more than 800,000 compounds, they discovered three highly selective and potent senolytic compounds, with chemical properties suggestive of high oral bioavailability. 

In addition, these compounds – which all bind Bcl-2, a protein that regulates apoptosis and is also a chemotherapy target – exhibited favorable toxicity profiles in hemolysis and genotoxicity experiments.

Testing these compounds in 80-week-old-mice (an age corresponding to 80-year-old humans), the researchers found that they efficiently removed senescent cells and reduced the expression of genes associated to senescence in the kidneys.

“This work illustrates how AI can be used to bring medicine a step closer to therapies that address aging, one of the fundamental challenges in biology,” said senior author James J. Collins, a professor of Medical Engineering and Science at the Massachusetts Institute of Technology (MIT) and founding chair of the Integrated Biosciences Scientific Advisory Board.

“Integrated Biosciences is building on the basic research that my academic lab has done for the last decade or so, showing that we can target cellular stress responses using systems and synthetic biology. This experimental tour de force and the stellar platform that produced it make this work stand out in the field of drug discovery and will drive substantial progress in longevity research,” he concluded.

The study is published in the journal Nature Aging.

More about anti-aging

Anti-aging refers to the various techniques, therapies, and lifestyle changes aimed at delaying or reversing the aging process in humans. The primary goal of anti-aging interventions is to promote a healthy and longer life by targeting the underlying causes of aging and age-related diseases. Here are some key aspects of anti-aging:

Cellular aging

This involves studying cellular senescence, the process by which cells lose their ability to divide and function normally. Interventions targeting cellular aging include senolytics (compounds that selectively eliminate senescent cells) and telomerase activation (aimed at maintaining or extending telomere length).

Oxidative stress

Accumulation of reactive oxygen species (ROS) can damage cells and contribute to aging. Antioxidants are molecules that help neutralize ROS, and their supplementation has been considered as a potential anti-aging strategy.


Chronic low-grade inflammation is associated with aging and age-related diseases. Anti-inflammatory interventions, such as dietary changes and medications, can help reduce inflammation and potentially slow the aging process.

Hormone replacement therapy

As we age, hormone levels decline, contributing to various age-related symptoms. Hormone replacement therapy seeks to restore hormone levels to those of younger individuals, potentially improving health and well-being.

Caloric restriction and fasting

Reducing caloric intake or fasting for short periods has been shown to extend lifespan in various organisms, possibly by activating stress-response pathways that promote cellular repair and maintenance.

Lifestyle changes

Maintaining a healthy lifestyle, including regular exercise, a balanced diet, stress management, and sufficient sleep, has been shown to promote overall health and longevity.

Genetic and epigenetic interventions

Genetic manipulation and epigenetic modifications have shown potential for altering the aging process. Examples include gene therapy to target specific aging-related genes and interventions that modify epigenetic marks, such as DNA methylation and histone modifications.

Pharmaceutical interventions

Several compounds, such as rapamycin, metformin, and resveratrol, have shown promise in extending lifespan and improving health in animal models. These drugs target various aging-related pathways and are under investigation for their potential human application.

It’s important to note that while many of these interventions show promise, their long-term safety and efficacy in humans are not yet fully understood. Further research is needed to determine the optimal strategies for promoting healthy aging and extending human lifespan.

By Andrei Ionescu, Staff Writer

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