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Funded Studies

The Foundation supports research across basic, translational and clinical science to speed breakthroughs that can lead to the creation of new treatments and a better quality of life for people with Parkinson's disease.

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Previously funded studies appear chronologically, with the most recent appearing first.

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  • Therapeutic Pipeline Program, 2019
    Miro1-targeting Drug Discovery for Parkinson's Disease

    Study Rationale:
    There is mounting evidence for involvement of mitochondrial biology in the pathogenesis of Parkinson’s disease (PD). Alterations in mitochondrial dynamics and distribution have been...

  • Therapeutic Pipeline Program, 2019
    Screening for Precision Parkin Activators

    Study Rationale:
    Defects in the protein parkin cause the loss of nerve cells in the brain and are responsible for many cases of young-onset Parkinson's disease that develops before 50 years of age. We...

  • Research Grant, 2019
    Patient Reports on Cannabis Use in Parkinson's Disease

    Study Rationale:
    Medical marijuana (cannabis) is now legal in 47 states, and recreational use is legal in nine. Interest in cannabis for treating Parkinson’s disease (PD) is rapidly increasing. Despite...

  • Aligning Science Across Parkinson's, 2019
    Global Parkinson’s Genetics Program (GP2)
    GP2 Logo

    GP2 is a resource of the Aligning Science Across Parkinson's (ASAP) Initiative.

    Study Rationale
    A substantial proportion of risk for Parkinson’s disease (PD) is driven by genetics, and genetic links...

  • Improved Biomarkers and Clinical Outcome Measures, 2019
    Applying Artificial Intelligence for Early Identification of Parkinson’s Disease

    Study Rationale:
    The nervous system regulates heart rate in response to situations such as stress and emergencies. Dysfunction of part of the nervous system controlling the heart can cause changes in...

  • Research Grant, 2019
    Enhancing the Clinical Utility of Data-Driven Parkinson’s Subtypes with Knowledge Distillation and Visualization

    Study Rationale:
    Data-driven analytics, such as machine learning methods, have been applied to discover comprehensive Parkinson’s disease (PD) subtypes from observational patient data. However, many of...

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