The Rodent Aging Interventions Database
You might compare the LEV Foundation's Rodent Aging Interventions Database with the DrugAge database, both emerging from the efforts of researchers who found themselves frequently reviewing the existing literature on age-slowing interventions in animal models. One of the things to bear in mind about the existing literature is that rodent studies that show an apparent modest slowing of aging frequently fail to replicate when later investors take a more rigorous approach, with larger numbers of mice. The history of the NIA Interventions Testing Program is largely a repeated demonstration of this point.
The Rodent Aging Interventions Database (RAID) project arose as a result of work conducted during late 2022 in preparation for the first study in LEV Foundation's Robust Mouse Rejuvenation (RMR) program: specifically, a comprehensive survey conducted by LEVF of publications documenting successful lifespan extension in strains of rodents (mice and rats) with normal baseline lifespans. That survey played an important role in informing the selection of interventions for the RMR program.
Recognising that this compilation of data may be of interest to other researchers in the field of longevity/aging research, we decided to make it publicly available. To enable convenient exploration of the results, we have also developed a visualization tool which depicts the increases in lifespan achieved in different studies as a single bar chart.
The dataset queried by this tool is intended to cover all published studies that meet the inclusion criteria: (a) in mice (Mus musculus) or rats (Rattus norvegicus), (b) a genetic background consistent with normal aging rates (e.g. no progeria, PolG mitochondrial DNA mutator, Alzheimer's models such as APP/PS1, etc.), and (c) the study reports an intervention with some statistically significant effect on average or maximum lifespan. It is our intention to update the dataset periodically, but some newer (or recently identified) publications may not yet be indexed.