Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1st to 4th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8th ARDD meeting that is scheduled for the 31st of August to 3rd of September, 2021, at Columbia University, USA.
Bibliographical noteFunding Information:
S.B. is supported by the Novo Nordisk Foundation (grants NNF17OC0027594 and NNF14CC0001). F.C. acknowledges funding from the Wellcome Trust/Royal Society (102532/Z/12/Z and 102531/Z/13/A). A.M.C is supported in part by grants from JPB and Rainwaters Foundation. C.G.S.G. is funded by the NIH/NIA (K99AG065508). E.F.F. is supported by HELSE SØR-ØST (#2017056), the Research Council of Norway (#262175 and #277813), the National Natural Science Foundation of China (#81971327), an Akershus University Hospital Strategic grant (#269901), and a Rosa Sløyfe grant (#207819) from the Norwegian Cancer Society. V.N.G. is supported by grants from the National Institute on Aging. D.W.L. is supported in part by research grants and funds from the National Institutes of Health (AG041765, AG050135, AG051974, AG056771 and AG062328), the Wisconsin Partnership Program, the Progeria Research Foundation, the American Federation for Aging Research, and the University of Wisconsin-Madison School of Medicine and Public Health and Department of Medicine. The Lamming laboratory is supported in part by the U.S. Department of Veterans Affairs (I01-BX004031), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. H.H.P. is supported by a NIA F31 predoctoral fellowship (NIA F31 AG066311). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government. JTT is supported by the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR). CBMR is an independent Research Center at the University of Copenhagen and partially funded by an unrestricted donation from the Novo Nordisk Foundation (NNF18CC0034900). L.N. is funded by NIH/NIA (R01 AG063543-02S1). L.Z. work is funded by NIH/NIA (U19 AG056278 and P01 AG062412). L.J.R is supported by research grants from Nordea-fonden, Olav Thon Foundation, Novo Nordisk Foundation (NNF17OC0027812). L.J.R. is a member of the Clinical Academic Group: Recovery Capacity After Acute Illness in And Aging Population (RECAP). C.G.R. is supported by the Swedish Research Council (VR) grants (2015-03740, 2017-06088, and 2019-04868), the COST grant BM1408 (GENiE), and an ICMC project grant. D.T. work is funded by The David and Inez Myers foundation and ISF 188/17. D.A.S is supported by the Harvard Medical School Epigenetics Seed Grant and Development Grant, The Paul F. Glenn Foundation for Medical Research, and NIH awards (R01AG019719 and R37AG028730). B.S. acknowledges funding from the Deutsche Forschungsgemeinschaft (SCHU 2494/3-1, SCHU 2494/7-1, SCHU 2494/10-1, SCHU 2494/11-1, CECAD, SFB 829, KFO 286, KFO 329, and GRK2407), the Deutsche Krebshilfe (70112899), and the H2020-MSCA-ITN-2018 (Healthage and ADDRESS ITNs). D.B. is supported by the Lundbeck foundation (# R303-2018-3159). M.S.K. is funded through the Nordea Foundation (#02-2017-1749), the Novo Nordisk Foundation (#NNF17OC0027812), the Neye Foundation, the Lundbeck Foundation (#R324-2019-1492), the Ministry of Higher Education and Science (#0238-00003B) and Insilico Medicine.
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- artificial intelligence
- drug discovery
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural
- Research Support, Non-U.S. Gov't
- Research Support, U.S. Gov't, Non-P.H.S.