AgeXtend is a multimodal, mechanism-backed, AI-based platform that predicts the anti-aging potential of a compound. AgeXtend helped in screening ~1.1 billion compounds for their geroprotective potential and predicted novel anti-aging compounds, further validated through high throughput yeast-based assays, along with human fibroblasts and C. elegans.
First author: Sakshi Arora, the first author of this study, is a fourth-year PhD candidate with a background in biotechnology and industrial experience. Her passion for interdisciplinary research, integrating AI, biology, and chemistry, led her to pursue innovative scientific endeavors in the Ahuja Lab. She is dedicated to making meaningful contributions to the scientific community and aims to continue driving impactful and passionate projects in the future.
- Linkedin – https://www.linkedin.com/in/sakshi327/
- Twitter (X) – @sakshi_327
- Instagram – sakshi_327
Lab: Dr. Gaurav Ahuja, Department of Computational Biology, Indraprastha Institute of Information Technology – Delhi
- Twitter – @ahuja_77
- Github – https://github.com/the-ahuja-lab
What was the core problem you aimed to solve with this research?
In longevity science, one of the biggest challenges is the absence of systematic tools to identify and understand compounds that can slow or reverse aspects of aging. Most current methods rely heavily on trial-and-error experimentation, which is both time-consuming and resource-intensive. Recognizing this gap, we developed AgeXtend—a cutting-edge platform that harnesses artificial intelligence to not only predict potential geroprotectors but also provide insights into how these compounds interact with aging mechanisms.
How did you go about solving this problem?
To address this challenge, we created AgeXtend, which stands apart from traditional models by offering explainability. It links compounds directly to key hallmarks of aging, providing clarity on their potential mechanisms of action. By integrating advanced AI techniques with biological knowledge, AgeXtend significantly accelerates the discovery of geroprotectors, minimizing the reliance on time-intensive trial-and-error methods.
Currently, we aim to continue our scientific journey in longevity science by researching more about alternate solutions to healthy aging, focusing more on aging-associated disorders. – Â Dr. Gaurav Ahuja
How would you explain your research outcomes (Key findings) to the non-scientific community?Â
AgeXtend is an advanced artificial intelligence platform that identifies chemical compounds with anti-aging potential. It is a highly intelligent tool that helps scan through an enormous library of about 1.1 billion compounds to find those that might slow down or even reverse certain aspects of aging. Using this platform, we discovered several new compounds with promising anti-aging properties. These compounds were then tested in various models, including yeast, human cells, and tiny organisms called Caenorhabditis elegans, to validate their effectiveness.
This research is exciting because AgeXtend could help scientists develop new therapies to promote healthy aging, extend our health span, and even create innovative treatments for age-related conditions. It’s like having a smart assistant that accelerates the discovery process, paving the way for breakthroughs in the science of aging.
What are the potential implications of your findings for the field and society?
AgeXtend has the potential to revolutionize aging research by providing detailed mechanistic insights into how certain compounds interact with the biological processes of aging. These insights can guide the development of targeted therapeutic interventions to slow down aging or address age-related conditions.
Beyond its scientific contributions, AgeXtend is designed for accessibility and collaboration. By making it available as a Python package, it empowers researchers worldwide to use and build upon this tool, fostering a global effort to accelerate discoveries in healthy aging and longevity. This collaborative potential could ultimately lead to breakthroughs that improve the quality of life for aging populations, benefiting society as a whole.
What was the exciting moment during your research?
One of the most thrilling moments in our research was taking on the monumental challenge of screening approximately 1.1 billion compounds. It was both daunting and exhilarating to handle such an enormous dataset, requiring countless hours of meticulous data collection, processing, and analysis. Seeing meaningful patterns and actionable insights emerge from this vast sea of data was incredibly rewarding and underscored the power of combining computational tools with scientific curiosity.
Reference
Arora, S., Mittal, A., Duari, S. et al. Discovering geroprotectors through the explainable artificial intelligence-based platform AgeXtend. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00763-4; https://www.nature.com/articles/s43587-024-00763-4
