Researchers may be able to use measurable biological signals called aging rate indicators (ARIs) to detect much sooner whether an intervention slows the pace of aging. This is according to a recent Frontiers in Science article.
Join the authors—Prof Richard A. Miller, Prof Steven Austad, and Dr Matt Kaeberlein—at our Frontiers in Science Deep Dive webinar on 24 November 2026, 15:00–16:30 CET, to explore machine-learning approaches to identifying and validating ARIs.
The authors will be joined by Carolyn Baker Ringel (Center for Bioethics, Harvard Medical School, USA), to also discuss the regulatory barriers to testing anti-aging interventions in humans, and the safeguards needed for equitable access to these interventions.
Aging rate indicators and the search for anti-aging drugs | 24 November 2026 | Register
Frontiers in Science Deep Dive sessions bring researchers, policy experts, and innovators together from around the world to discuss a specific area of transformational science published in Frontiers' flagship, multidisciplinary journal, Frontiers in Science, and explore next steps for the field.