The Foundation supports research that can lead to the creation of better Parkinson's treatments. Here you can search previously awarded grants by keyword, program name, researcher name, institution or organization name and/or year.
FUNDED GRANTS ( 115)
Improved Biomarkers & Clinical Outcome Measures, 2017
Dopamine Buffering Capacity Measured by phMRI as a Novel Biomarker of Disease Progression in Parkinson's Disease
This project will test a new idea for measuring the severity of Parkinson's disease (PD). The brain acts as if it can store each dose of levodopa (L DOPA) for a short period of time and lets it "leak" into the brain when needed. This levodopa reservoir appears to get "leakier" as PD progresses, contributing to a gradually briefer benefit from each dose of the drug. The new idea we...
Researchers: Kevin J. Black, MD
Research Grant, 2017
Assessing the accumulation of tau (protein associated with dementia) and alpha-synuclein (sticky protein associated with Parkinson's) in the living human brain is crucial to better understanding Progressive Supranuclear Palsy (movement disorder that causes impaired balance and vision; PSP), Parkinson's disease (PD) and related neurodegenerative disorders, in addition to aiding in ...
Researchers: Neil Vasdev, PhD
Research Grant, 2017
Promising Outcomes of Original Grant:
Our project aims to develop a brain imaging agent for alpha-synuclein, a key protein involved in Parkinson's disease (PD) pathology. Such an agent will help (i) diagnose PD earlier, (ii) track pathology over time and (iii) monitor the efficacy of therapeutics reducing alpha-synuclein aggregates. The AC Immune team identified promising compounds they are refinin...
Improved Biomarkers & Clinical Outcome Measures, 2016
Amyloid fibrils play a key role in Parkinson's disease (PD). Studying their formation from self‐assembled aggregates (protein clumps) would help aid the development of a valuable diagnostic tool. Despite progress in understanding these processes in a test tube, visualization through an imaging approach has not yet been fully achieved. We will develop a contrast agent with protectiv...
Researchers: Leif Schröder, Dr. rer. nat.
PPMI Data Challenge, 2016
Multivariate Prediction of Parkinson's Disease Clinical Progression (2016 PPMI Data Challenge Winner)
Parkinson's disease (PD) is heterogeneous in both clinical representation and prognosis, as indicated by a large diversity of rates of progression in motor as well as non-motor symptoms. It could therefore be helpful to have well-characterized and distinct subtypes of Parkinson's disease slow and fast clinical progression and have early indicators of the clinical progression rate f...
Researchers: Duygu Tosun-Turgut, PhD