The Accelerating Medicines Partnership (AMP) program for Parkinson’s disease (PD) has launched a data portal to provide de-identified information collected from 4,298 PD patients and healthy controls to researchers working to develop effective therapies for the disease. The portal enables researchers to study complex data sets and perform genome-wide analyses at a scale previously impossible.
AMP PD is a public-private partnership between the National Institutes of Health, the U.S. Food and Drug Administration, with industry (Celgene, GSK, Pfizer, Sanofi and Verily) and non-profit (The Michael J. Fox Foundation for Parkinson’s Research) organizations and managed through the Foundation of the National Institutes of Health (FNIH). The goal of this partnership is to transform and accelerate drug development in PD by providing the expertise and support needed to determine which biomarkers show the greatest potential for predicting PD and the progression of the disease.
The AMP PD Knowledge Portal contains data from cerebrospinal fluid, RNA, plasma and DNA samples previously collected through programs including The Michael J. Fox Foundation for Parkinson’s Research (MJFF) and National Institute of Neurological Disorders and Stroke (NINDS) BioFIND Study, the Harvard Biomarkers Study of Brigham and Women's Hospital and Massachusetts General Hospital, the NINDS Parkinson's Disease Biomarkers Program, and MJFF’s Parkinson’s Progression Markers Initiative. Additionally, AMP PD provides a platform that can incorporate additional data sources and new types of data, including proteomics, a project already planned.
Over the past 18 months, AMP PD scientific teams have worked to ensure that the data added into the portal was accurate and described in a consistent way. This crucial step, called data harmonization, allows information gathered from different programs to be compared, and it also provides best practices for how to integrate new data provided by the community into the platform. One of the unique features of these data is that they are longitudinal – it will allow researchers to analyze data from across an individual’s lifespan or disease course.
