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Translational Capabilities: Characterization of animal models (Milestone 4.B)


Timeline Start - End

2016 - 2020

Research Implementation Area

Translational Tools, Infrastructure, and Capabilities

Create infrastructure/resources for extensive characterization of existing and new animal models and development of standardized and rigorous methods for preclinical efficacy testing including web-based resources for transparent reporting of both positive and negative findings.

Success Criteria

  • Create at least one translational center for animal model resources.
  • Support the generation of large longitudinal, multi-omic data on existing and newly developed transgenic mouse models necessary to build “molecular network maps” that connect molecular attributes of AD across mouse models and humans.
  • Enable comprehensive analyses of ‘clinical’ and deep omics profiles in panels of genetically diverse mice, to better model human genomes.
  • Create a publicly available database that houses experimental designs and analysis relating to the preclinical testing of candidate therapeutics in AD animal models. The data base should function as a knowledge platform for data sharing, mining and analysis and should help identify critical experimental design elements and methodology that impact the rigor and reproducibility of published studies.

Summary of Key Accomplishments

Established through a targeted funding initiative, the NIA-supported MODEL-AD Centers are developing the next generation mouse models based on the genetic factors associated with late-onset AD (LOAD) and providing key infrastructure for rigorous testing of promising candidate therapeutics. To enable transparent reporting of both positive and negative findings from animal model studies testing candidate therapeutics, NIA established the publicly available database AlzPED. The MODEL-AD Centers have created a subset of mouse models of LOAD in genetically diverse strains. The most promising LOAD mouse models are being characterized across the lifespan using multi-omic data which has allowed comparison with the molecular attributes of the human disease.

The key accomplishments summary is current as of March 2022. 

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