This research introduces ClockBase, a comprehensive platform that utilizes specialized AI agents to analyze millions of biological samples for aging research. By applying transcriptomic and epigenetic clocks to vast datasets from the Gene Expression Omnibus, the system systematically identifies how various drugs, genetic modifications, and environmental factors influence biological age. The study highlights the discovery of ouabain as a potent anti-aging candidate, which was shown to improve cardiac output and reduce frailty in elderly mice. Beyond specific findings, the authors demonstrate that autonomous AI workflows can achieve expert-level accuracy in bioinformatic tasks, such as statistical modeling and data integration. Ultimately, this framework establishes a scalable, data-driven approach to discovering longevity interventions and understanding the complex mechanisms of biological decay.

References:

• Autonomous AI Agents Discover Aging Interventions from Millions of Molecular Profiles
• doi: doi.org