AMP Projects

Alzheimer鈥檚 Disease (AD)

uses a precision medicine approach to validate existing targets and discover novel targets and biomarkers. launched in 2014 and applied cutting-edge systems and network biology approaches to integrate multidimensional human 鈥渙mic鈥 data for more than 2,000 human brains at all stages of AD. Using clinical and pathological data, researchers aimed to discover novel therapeutic targets for AD; gain a systems-level understanding of the gene, protein, and metabolic networks within which these novel targets operate; and conduct experimental validation of candidate targets in multiple model systems. To validate existing targets, the AD 1.0 program embedded PET TAU imaging in two anti-amyloid clinical trials.

launched in 2021 and builds on the work of AD 1.0 with a goal of enabling a precision medicine approach to the discovery of novel targets and biomarkers. This program supports research on the molecular profiling in brain, cerebral spinal fluid, and blood samples from diverse cohorts; generates longitudinal immunologic profiling data to enable dynamic modeling of AD trajectory; and expands the existing single-cell/single nucleus molecular profiling efforts to build predictive models of the disease at single cell resolution.

Data, Analyses & Tools:

  • 鈥 An informatics platform for rapid sharing of well-annotated, high-quality human multi-omic data from brain, spinal fluid, and blood samples as well as cell-based and animal models.
  • 鈥 An interactive tool designed to allow researchers to explore curated genomic analyses AD.
  • 鈥 Explore the AD Biomarkers in Clinical Trials A4 Project data.

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Amyotrophic Lateral Sclerosis (ALS)

AMP ALS launched in May 2024 with the aim to accelerate the development of validated biomarkers for early diagnosis and effective treatments, discover new therapeutic targets and improve clinical outcome assessments. The program will introduce a new centralized knowledge portal to enable collection, management and analysis of current and future ALS data, and expand accessibility to that data. Researchers will also explore standardizing clinical tools and including patient reported outcomes when assessing the efficiency and effectiveness of ALS treatments and clinical trials. People with lived experience of ALS, including individuals and families affected by the disease, caregivers, and those at high genetic risk for developing ALS in the future, participated in the development of the partnership, and will continue to be involved in this program.

AMP ALS is part of the public-private partnership called for in H.R. 3537-Accelerating Access to Critical Therapies (ACT) for ALS Act, signed into law by President Biden in December 2021.

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Autoimmune and Immune-Mediated (AIM) Diseases

launched in December 2021 to deepen the understanding of the cellular and molecular interactions that lead to inflammation and autoimmune diseases and drive the development of new research tools, data storage platforms, and data sharing technologies. This program leverages the research infrastructure, datasets and novel technologies created by by broadening the scope to include psoriasis, psoriatic arthritis, and Sj枚gren鈥檚 disease.

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Bespoke Gene Therapy Consortium (BGTC)

launched in October 2021 and aims to develop platforms and standards that speed the development and delivery of customized or 鈥榖espoke鈥 gene therapies that could treat the millions of people affected by rare diseases. The effort鈥檚 goal is to overcome major obstacles related to developing gene therapies and create a gene therapy protocol book that the research community can use to make the process of developing gene therapies for rare conditions much more efficient.

Additional goals include improving the understanding of the basic biology of the harmless adeno鈥慳ssociated virus (AAV), a common gene-delivery vehicle or vector; improving the efficiency of both vector manufacturing and production quality control testing; and streamlining the path from animal studies to human testing.

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Common Metabolic Diseases (CMD) and Type 2 Diabetes (T2D)

aims at identifying promising new targets for six common metabolic diseases: liver diseases such as nonalcoholic steatohepatitis, kidney diseases, obesity, cardiovascular diseases, type 2 diabetes/prediabetes, and type 1 diabetes.

AMP CMD is using existing genomic data, including from the (T2D) program, and generate new largescale molecular data to achieve a deep understanding of genes and pathways that underlie common metabolic diseases. The consortium will integrate datasets to identify potential biotargets and new therapeutic targets.

was launched in 2014 to use and supplement the substantial amount of human genetic data available from people with T2D to identify and validate novel molecules and pathways as targets for therapeutic development. Researchers built a public database of DNA sequence, functional genomic and epigenomic information, and clinical data from studies on type 2 diabetes and its cardiac and renal complications.

Data, Analyses & Tools:

  • 鈥 Aggregates, analyzes, and displays human genetic and functional genomic information linked to common metabolic diseases and traits, while protecting the integrity and confidentiality of the underlying data.
  • 鈥 Includes DNA sequence, functional genomic and epigenomic information, and clinical data from studies on type 2 diabetes and its cardiac and renal complications.

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Heart Failure (HF)

AMP HF launched in September 2022 and investigates the multiple factors that lead to heart failure with preserved ejection fraction (HFpEF), a major unmet need in cardiovascular health. The program seeks to determine the phenotypes that constitute this complex, heterogenous syndrome and uses two complementary and integrated research components that run simultaneously.

In Component I, researchers are combining and analyzing existing HFpEF datasets sourced from studies funded by the public and private sectors. In Component II, researchers are creating a new deep phenotyping study based on best practices and existing research to develop a framework for new precision treatments.

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Parkinson鈥檚 Disease (PD)

The Accelerating Medicines Partnership庐 Parkinson鈥檚 Disease (AMP庐 PD) launched in 2018 with the goals of identifying and validating the most promising biological targets for therapeutics, and accelerating the development of novel therapies. The program is providing the resources and tools needed to determine which biomarkers show the greatest potential for predicting Parkinson鈥檚 Disease diagnosis, progression, and potential therapeutic targets.

To address these goals, the AMP PD program performed large-scale harmonization of previously collected clinical data and analyzed biospecimens from over 10,000 subjects. Whole genome sequencing, transcriptomics, proteomics, and post-mortem tissue sequencing are now publicly available for use by the scientific community. This resource enables researchers to pursue large-scale biomarker discovery, dissect new targets and disease subtypes, track and predict disease progression, and identify biomarkers of Parkinson鈥檚 progression and assess their potential as targets for therapies. The AMP PD program also collaborated with the Global Parkinson鈥檚 Genetic Program (GP2) to bring their genotyping data from 150,000+ international patients onto the AMP PD platform to provide a one-stop shop for Parkinson鈥檚 Disease omics data.

Data, Analyses & Tools:

  • 鈥 Contains data from cerebrospinal fluid, RNA, plasma, DNA, and postmortem brain samples from more than 10,000 Parkinson鈥檚 disease patients and healthy controls accessible to academic and industry researchers for the identification and validation of biomarkers for Parkinson鈥檚 disease.

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Autoimmune Diseases of Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE)

is analyzing, at the single cell level, tissue and blood samples from people with RA and lupus to pinpoint genes, proteins, biological pathways, and signaling networks. This type of analysis will allow insights into key aspects of diseases processes and allow comparisons between diseases. The project will provide a better systems level understanding of disease mechanisms in both RA and lupus.

AMP RA/SLE research phases aim to examine the cell types, gene expression patterns, and signaling molecules that play a role in rheumatoid arthritis and systemic lupus erythematosus. During Research Phase 0 of the project, researchers developed standardized methods and technology selection. Research Phase I used the standardized technologies established in Phase 0 to analyze samples from patients with RA and SLE and identify pathways that distinguish disease and non-disease tissue. Research Phase II studies are being conducted with a larger number of patients from subgroups within RA and SLE to improve understanding of disease variability.

Data, Analyses & Tools:

  • Knowledge Portals: dbGAP (; ) and

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Schizophrenia (SCZ)

launched in 2020 and addresses the critical need for more effective treatments for people with schizophrenia and related mental health conditions. The program aims to generate tools that will fast-track the development of effective, early-stage treatments for people who are at risk for schizophrenia, improve our understanding of disease pathways, and identify new and better targets for treatment.

The program鈥檚 goals include developing tools for predicting individual outcomes, establishing a global research network, disseminating research data to the broader scientific community through the NIMH Data Archive platform, and enabling clinical trials to test new pharmacologic interventions that may prevent or delay the onset of psychosis in individuals who are at risk for schizophrenia.

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Governance

Steering committees for each of the projects, with representation from the partners participating in those projects, meet regularly to review ongoing progress and milestones. The steering committees are managed by FNIH under the direction of an AMP Executive Committee comprised of representatives from NIH, participating industry leaders, FDA, European Medicines Agency, and non-profit and other organizations.

This page last reviewed on May 23, 2024