Year: 2026
Type: article
Abstract: The inaugural Global Conference on Gerophysics convened 160 researchers across physics, biology, computation, and medicine in Singapore on March 5-6, 2025. With 31 speakers, the two-day event explored how physical laws, and quantitative principles unify aging science, linking biological processes to longevity patterns. Sessions covered diverse aging aspects, from developmental stages to species comparisons. The meeting showcased innovative methods to study aging, emphasizing data-driven insights. A central theme was bridging theory and experiment to advance understanding. It concluded with a consensus around (1) shared multi-modal datasets; (2) physics-based definitions for "aging", "rejuvenation", and "healthspan"; (3) models predicting intervention outcomes; and (4) translational links between non-human species and human research. These priorities outline a practical path for a quantitative, predictive Gerophysics, building on the 2025 conference's insights to shape future aging research.
Source: Aging
Authors: Maximilian Unfried, Weihan Huai, Kamil Pabis, Sandra Jose, Zhi Meng Lim, Uri Alon, Marija Cvijovic, Nir Eynon, Peter Fedichev, Yumi Kim, Leong Kim Whye, Csaba Kerepesi, Woon-Puay Koh, Dmitrii Kriukov, Matt Kaeberlein, Feng Ling, Glen Pridham, Michael Rera, Steffen Rulands, Andrew Rutenberg, Kumar Selvarajoo, Ben Shenhar, Morten Scheibye-Knudsen, Andrei E. Tarkhov, Andrew Teschendorff, Weilan Wang, Ee Hou Yong, Yifan Yang, Jan Gruber, Brian K. Kennedy
Institutions: National University of Singapore, Weizmann Institute of Science, Chalmers University of Technology, University of Gothenburg, Australian Regenerative Medicine Institute, Monash University, Ulsan National Institute of Science and Technology, Mechanobiology Institute, HUN-REN Institute for Computer Science and Control, Hungarian Research Network, Agency for Science, Technology and Research, Skolkovo Institute of Science and Technology, AIRI - Artificial Intelligence Research Institute, Institute of High Performance Computing, Centre National de la Recherche Scientifique, Université Paris Cité, Unit of Functional and Adaptive Biology, Ludwig-Maximilians-Universität München, Dalhousie University, Nanyang Technological University, Bioinformatics Institute, University of Copenhagen, Equipe d’Economie Le Havre Normandie, Castle Biosciences, Inc. (United States), Chinese Academy of Sciences, Shanghai Institute of Nutrition and Health, Westlake University
Language: English
Subfield: Aging
Domain: Life Sciences
Open Access status: hybrid
Funder: National University of Singapore
OpenAlex ID: W7161112848