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http://www.nih.gov/science/amp/alzheimers.htm

The Alzheimer's disease arm of the Accelerating Medicines Partnership (AMP) that will identify biomarkers that can predict clinical outcomes, conduct a large scale analysis of human AD patient brain tissue samples to validate biological targets, and to increase the understanding of molecular pathways involved in the disease to identify new potential therapeutic targets. The initiative will deposit all data in a repository that will be accessible for use by the biomedical community. The five year endeavor, beginning in 2014, will result in several sets of project outcomes. For the biomarkers project, tau imaging and EEG data will be released in year two, as baseline data becomes available. Completed data from the randomized, blinded trials will be added after the end of the five year studies. This will include both imaging data and data from blood and spinal fluid biomarker studies. For the network analysis project, each project will general several network models of late onset AD (LOAD) and identify key drivers of disease pathogensis by the end of year three. Years four and five will be dedicated to validating the novel targets and refining the network models of LOAD, including screening novel compounds or drugs already in use for other conditions that may have the ability to modulate the likely targets.

Proper citation: Accelerating Medicines Partnership - Alzheimers (RRID:SCR_003742) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/amp/autoimmune.htm

The autoimmune disease arm of the Accelerating Medicine Partnership (AMP), which aims to identify and validate the most promising biological targets of disease for new diagnostic and drug development, that is focused on rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). They seek to identify shared common flaws in inflammation, particularly those that are shared with a larger number of autoimmune disorders which can cause severe disability, greatly affect quality of life, and are associated with an increased risk of death. This project aims to reveal biomarkers and biological targets for drug development, matching existing drugs to patients with specific molecular profiles who are most likely to benefit. The research plan proposes a 5 year process. Year one will include startup activities such as validation of tissue acquisition processes and analytic technologies, and the development of operating procedures. The second year will focus on identification of disease specific pathways by comparing data from patients and healthy individuals. Years 3-5 will expand the scale to include comparisons of different subsets of patients with RA or lupus to allow molecularly based patient stratification for precise treatment. The final 12 months (2019) will also include preliminary target validation. The data will be made publicly available through an internet-based information portal.

Proper citation: Accelerating Medicines Partnership Autoimmune Diseases of Rheumatoid Arthritis and Lupus (RRID:SCR_003731) Copy   

•   Source: SciCrunch Registry

http://omop.org/

Initiative to improve the safety of drugs on the market that utilized information drawn from patient medical record databases and health insurance claims to develop and test methods to detect and evaluate drug safety issues over time. The OMOP pilot project focused on the following objectives: * Defining and evaluating analytical methods that can be used to identify associations between drugs and health-related conditions. * Developing tools for organizing access to and evaluating the usefulness of multiple observational datasets. * Study how information from analyses of observational data can be used to inform ongoing pharmacovigilence efforts. The software tools - packaged as the OMOP Web RL Platform was developed and made available to the public, https://github.com/OMOP . In addition to these data tools, this collaborative research effort discovered methods for using data to reliably identify correlations between individual medical interventions and specific health outcomes. These insights are being used to help inform the FDA Sentinel Initiative as part of the Innovation in Medical Evidence Development and Surveillance (IMEDS) program. The achievements of the program include: * Establishment of a common data model and creation of data characterization tools, and vocabulary mappings * Implementation of Health Outcome of Interest definitions, including a program to implement these definitions as part of the Regularized Identification of Cohorts (RICO) * Release of 14 analysis methods to evaluate the performance of methods and data in identifying drug safety issues

Proper citation: Observational Medical Outcomes Partnership (RRID:SCR_003724) Copy   

•   Source: SciCrunch Registry