NIH Funds Translational Research Centers to Accelerate AD Drug Discovery

Modules. Clusters. Networks. eQTLs. Big data has exposed a plethora of biological pathways and potential drug targets for AD in recent years, but how to use all this information? A new initiative aims to leverage growing reams of data into drugs. On October 1, the National Institute on Aging (NIA) announced that it will infuse $73 million into the Alzheimer's Centers for the Discovery of New Medicines over the next five years (see press release). Essentially a newly formed network of collaborations, the centers plan to deepen their understanding of biological mechanisms that underlie AD, and develop drug targets beyond the realm of Aβ and tau. All data, tools, assays, and models that come out of the centers will be made openly available to researchers in academia and industry.

  • Alzheimer's Centers for the Discovery of New Medicines founded.
  • NIA to disburse $73 million over five years.
  • Centers to accelerate and diversify drug discovery.

Larry Refolo, program director for Alzheimer’s Translational Research at NIA, said the centers will help drive a “course correction” in AD research, which has narrowly focused on targeting Aβ and tau over the past 25 years.

“We have been trying to treat AD as a monolith, but in reality it is not one disease. You can have 10 people with Aβ plaques and tau tangles, but processes driving their disease may all be different,” he said.

The NIA grants will fund infrastructure to facilitate collaborations between two multi-institutional research teams. One is the Indiana University School of Medicine Alzheimer’s Disease Drug Discovery Center, to be led by IU’s Alan Palkowitz and Bruce Lamb, along with researchers from Purdue University in West Lafayette, Indiana. This center will build a portfolio of AD drug targets based on results from the NIH-funded Accelerated Medicines Project-AD (AMP-AD).

Since its launch in 2014, AMP-AD has integrated large-scale “omics” approaches to uncover biological pathways that underlie AD pathology. It reportedly has identified hundreds of potential drug targets (Feb 2014 news; Jun 2018 news; and May 2019 news on Mathys et al., 2019). Potential targets, and drug compounds, will be tested in animal models generated though the Model Organism Development and Evaluation for Late-Onset AD consortium. In collaboration with Jackson Laboratory, MODEL-AD has been using human genetic data to develop mouse strains with better predictive validity than prior strains used in the field.

The second center—the Open Drug Discovery Center for Alzheimer’s Disease (Open-AD)—will generate Target Enabling Packages (TEPs), a collection of tools such as antibodies, chemical probes, bioinformatics, and assays that will facilitate testing of targets by researchers in academia or industry. This center will also generate new hypotheses about the underlying causes of AD. It will be led by Allan Levey of Emory University, Atlanta; Lara Mangravite of Sage Bionetworks, Seattle; and Aled Edwards of the Structural Genomics Consortium, Toronto. Open-AD aims to move the most promising targets closer to the point where they can be picked up for clinical development.

Levey told Alzforum that the goal of the newly funded centers will be to find multiple treatments for AD. “The field needs to move beyond Aβ and tau,” Levey said.—Jessica Shugart

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References

News Citations

  1. New Initiative AMPs Up Alzheimer’s Research
  2. Culling Connection From Chaos, Alzheimer’s Genetic Network Study Pins PLXNB1 and INPPL1
  3. When It Comes to Alzheimer’s Disease, Do Human Microglia Even Give a DAM?

Paper Citations

  1. Mathys H, Davila-Velderrain J, Peng Z, Gao F, Mohammadi S, Young JZ, Menon M, He L, Abdurrob F, Jiang X, Martorell AJ, Ransohoff RM, Hafler BP, Bennett DA, Kellis M, Tsai LH. Single-cell transcriptomic analysis of Alzheimer's disease. Nature. 2019 Jun;570(7761):332-337. Epub 2019 May 1 PubMed.

External Citations

  1. press release
  2. Accelerated Medicines Project-AD
  3. Model Organism Development and Evaluation for Late-Onset AD

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