Our mission is to find common drivers for metabolic diseases to accelerate therapeutic interventions.

The Accelerating Medicines Partnership® (AMP®) Program in Common Metabolic Diseases (AMP CMD) is a collaborative partnership among government and private-sector partners that harnesses their collective capabilities, scale, and resources to therapeutically address multiple metabolic diseases that share common pathogenic drivers and overlapping molecular pathways and make them available in a precompetitive space.

Building on the successful output of AMP Program in Type 2 Diabetes, which collected predominantly genetic datasets on over 1.5 million participants, AMP CMD generates and acquires genetic, functional genomic and multi omics data to accelerate target discovery across the metabolic disease indications. The AMP CMD Knowledge Portal (CMDKP) and the AMP CMD Genome Atlas (CMDGA), the project’s open access knowledge portals, aggregate, analyze, and display summary statistics data from subjects with type 1 and type 2 diabetes, obesity, cardiovascular, kidney, and liver diseases, and related complications.

  • Expand the CMDKP by generating new and leveraging existing genetic, genomic, and biomarker data.

  • Address data gaps in metabolic diseases, including obesity, atherosclerotic cardiovascular disease and heart failure, pre-diabetes, type 2 diabetes, autoimmune diabetes, and diabetic complications, nonalcoholic steatohepatitis, chronic kidney disease ,and inflammatory drivers.

  • Evolve the AMP CMD Knowledge Portal by developing analytic and visualization tools to support integrative analysis.

  • Deliver prioritized targets for the common metabolic diseases with supporting mechanistic data.

The Foundation for the National Institutes of Health is releasing two funding opportunities for the Accelerating Medicines Partnership® in Common Metabolic Diseases. Investigators working with genetic, genomic, and other tissues/omics data, and analytic tools and methods relating to common metabolic diseases including obesity, cardiovascular and kidney diseases, NAFLD/NASH, and diabetes are encouraged to apply. The program is especially interested in datasets from non-European ancestry cohorts. Proposals are due by April 3, 2024.


Need for New Approaches

Traditionally, common metabolic diseases have been targeted and treated as individual diseases. Their potential shared molecular basis represents an opportunity to treat multiple diseases simultaneously and to provide more effective treatment outcomes.

Accelerating Target Discovery

AMP CMD will apply large scale genetic, genomic, transcriptomic, proteomic, metabolomic approaches to characterize human physiology and pathophysiology at the cellular, tissue, organ and whole organism levels. The initiative will prioritize targets for metabolic diseases and develop tools to analyze links between them.


Private Sector Partners
Public Sector Partners

We are proud to participate in the Accelerating Medicines Partnership to help further research progress in this field through collaboration with leading industry and non-profit partners. The ability to leverage each partners’ insights and experience, along with integrating the power of human data, will help to identify and validate novel pathways and potential therapeutic targets to address unmet clinical needs.

-Narimon Honarpour, M.D., Ph.D., Vice President of Translational
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We are excited to work on this important collaboration designed to decode the complexities of common metabolic disorders that will lead to an increased understanding of the disease drivers. This public-private partnership calls for a critical mass of researchers determined to research diabetes, obesity, non-alcoholic steatohepatitis, chronic kidney and cardiovascular diseases, with the aim to expand research strengths to address the significant unmet need for patients living with these diseases.

-Karin Conde-Knape, Ph.D., Senior Vice President for Global Drug Discovery, Novo Nordisk
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Data Portals

AMP CMD Knowledge Portal and AMP CMD Genome Atlas

AMP CMD Knowledge Portal currently houses 368 datasets consisting of 388 traits, representing cohorts from 66 countries.



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