Artificial Intelligence Paves Way for New Horizons in Anti-Aging Medicine

The world of artificial intelligence (AI) has broadened the horizons of anti-aging medicine by enabling scientists to unearth novel senolytic compounds that curtail age-related phenomena such as inflammation and cancer. Deep neural networks, honed with experimental information, have played a significant role in identifying three compelling drug contenders from a plethora of over 800,000 molecules. These contenders are likely to display superior medicinal traits compared to the current generation of senolytics.

The emergence of this new platform signals an era of accelerated advancement in the creation of anti-aging compounds known as senolytics and boosts research efforts centered around longevity. A recent article published in Nature Aging from Integrated Biosciences - a company merging synthetic biology with machine learning to combat aging - showcases the effective use of AI in identifying novel senolytic compounds. These tiny molecules are gaining traction due to their ability to obstruct aging-related processes such as inflammation, fibrosis, and cancer.

The research paper is the brainchild of a combined effort involving scientists from Massachusetts Institute of Technology (MIT) and the Broad Institute of MIT and Harvard. It encapsulates an AI-driven analysis of over 800,000 compounds, which successfully pinpoints three potential drugs that have a comparable efficacy and superior medicinal chemistry traits to those of the existing senolytics being studied.

Felix Wong, Ph.D., co-founder of Integrated Biosciences and leading author of the publication, stated that this result is a groundbreaking achievement for both longevity research and AI's application in drug discovery. “The information we gathered proves that we can probe the chemical realm digitally and come up with multiple anti-aging compounds that stand a better chance of success in clinical settings compared to even the best examples of their kind currently under study.”

Senolytics are substances that selectively trigger apoptosis, or the programmed death of cells, in senescent cells that have ceased to divide. Aging brings about the onset of these cells, which are implicated in a variety of age-related conditions and diseases, including Alzheimer’s disease, cardiovascular disease, diabetes, and cancer.

Even though senolytic compounds have shown promising results in clinical trials, the majority have been impeded by their poor bioavailability and adverse side effects. Integrated Biosciences, founded in 2022, aims to surmount these challenges, focus on other overlooked aspects of aging, and propel the development of anti-aging drugs utilizing AI, synthetic biology, and other state-of-the-art tools.

“One of the most promising pathways to treat age-related diseases is to discover treatments that selectively eliminate these cells from the body, in the same way that antibiotics destroy bacteria without harming host cells. The compounds we discovered exhibit high selectivity and the favorable medicinal chemistry traits needed to result in a successful drug,” said Satotaka Omori, Ph.D., Head of Aging Biology at Integrated Biosciences and co-leading author of the publication. “We are confident that the compounds identified using our platform will have better chances in clinical trials and eventually contribute to rejuvenating the health of aging individuals.”

In their latest research, scientists at Integrated Biosciences trained deep neural networks on data generated experimentally to predict the senolytic potential of any molecule. Using this AI model, they unearthed three potent and highly selective senolytic compounds from a chemical pool of over 800,000 molecules.

All three compounds demonstrated chemical properties indicative of high oral bioavailability and passed hemolysis and genotoxicity tests with favorable toxicity profiles. Further structural and biochemical analysis revealed that all three compounds latch onto Bcl-2, a protein that oversees apoptosis and is also a target for chemotherapy. When one of the compounds was tested in 80-week-old mice (analogous to 80-year-old humans), it successfully removed senescent cells and lowered the expression of genes associated with senescence in the kidneys.

James J. Collins, Ph.D., Termeer Professor of Medical Engineering and Science at MIT, and founding chair of the Integrated Biosciences Scientific Advisory Board, praised the research. “This study epitomizes how AI can be harnessed to take medicine one step closer to addressing aging, one of biology's most fundamental challenges. Integrated Biosciences builds on the groundwork that my academic lab has been conducting for over a decade, demonstrating that we can target cellular stress responses using systems and synthetic biology. This experimental triumph and the standout platform that facilitated it are noteworthy in the field of drug discovery and will significantly propel longevity research forward.”

Reference: “Discovering small-molecule senolytics with deep neural networks” by Felix Wong, Satotaka Omori, Nina M. Donghia, Erica J. Zheng, and James J. Collins, 4 May 2023, Nature Aging. DOI: 10.1038/s43587-023-00415-z

Dr. Collins, the senior author on the Nature Aging paper, led the team that discovered the first antibiotic identified by machine learning in 2020.