AI and anti-aging research: According to a study, AI algorithms have led to the discovery of three drugs that have the potential to delay the effects of aging
Cutting-edge research in artificial intelligence has identified 3 compounds targeting age-related ailments. The successful identification of these three chemical compounds possess the remarkable ability to target malfunctioning cells linked to aging.
This groundbreaking approach is combining AI tech with drug development efforts. This means it is significantly more cost-effective than conventional screening methods, and has enabled the discovery of these compounds.
AI algorithms unlock promising anti-aging drugs
The study findings indicate that these drugs have the potential to effectively and safely eliminate senescent cells, which are faulty cells associated with a range of conditions such as cancer, Alzheimer’s disease, and age-related declines in eyesight and mobility.
Although previous research has demonstrated some initial potential, the identification of chemicals capable of safely targeting and eliminating senescent cells has remained limited. According to researchers, the challenge lies in the fact that many senolytic drugs tend to exhibit high toxicity towards normal, healthy cells within the body.
Targeting malfunctioning cells: A breakthrough approach
The University of Edinburgh researchers, leading a team of scientists, have developed an innovative method that employs artificial intelligence (AI) to identify senolytic drugs.
By leveraging data from over 2,500 chemical structures extracted from past studies, the team successfully trained a machine-learning model to recognize the essential characteristics associated with chemicals possessing senolytic activity.
Subsequently, employing their models, the team performed a comprehensive screening of over 4,000 chemicals, resulting in the identification of 21 prospective drug candidates for further experimental evaluation.
Eliminating senescent cells: Overcoming challenges
Experiments conducted in human cells within the laboratory setting unveiled the remarkable capability of three chemicals, namely ginkgetin, periplocin, and oleandrin, to eliminate senescent cells while preserving the integrity of healthy cells.
Remarkably, all three compounds are derived from natural sources found in traditional herbal medicines, as highlighted by the research team. Additionally, oleandrin demonstrated superior effectiveness compared to the current leading senolytic drug within its category.
Dr. Vanessa Smer-Barreto, the lead author from the University of Edinburgh’s Institute of Genetics and Cancer and School of Informatics, expressed her thoughts on the matter by stating,
“This work was borne out of intensive collaboration between data scientists, chemists, and biologists. Harnessing the strengths of this interdisciplinary mix, we were able to build robust models and save screening costs by using only published data for model training. I hope this work will open new opportunities to accelerate the application of this exciting technology.”
I hope this work will open new opportunities to accelerate the application of this exciting technology
AI-powered drug discovery: The University of Edinburgh’s innovations
Published in the esteemed journal Nature Communications, this study received support from various institutions, including the Medical Research Council, Cancer Research UK, United Kingdom
Research and Innovation (UKRI), and the Spanish National Research Council. Collaboration was also fostered with researchers from the University of Cantabria, Spain, and the Alan Turing Institute.
This study represents a significant milestone in the field of computer science and artificial intelligence (AI), building upon the University’s rich history in these disciplines that spans six decades.
To celebrate these achievements and explore the future of computer science and AI at Edinburgh, a year-long series of events has been planned.
Co-author Dr. Diego Oyarzún, of the University of Edinburgh’s School of Informatics and School of Biological Sciences, said: “This study demonstrates that AI can be incredibly effective in helping us identify new drug candidates, particularly at early stages of drug discovery and for diseases with complex biology or few known molecular targets.”
AI can be incredibly effective in helping us identify new drug candidates
