Finding a Path To Prevention in Parkinson’s Disease: A Nested Platform Trial to Efficiently Identify Effective Treatments

Conference: Women in Statistics and Data Science 2023
10/25/2023: 3:05 PM - 3:30 PM PDT


Recent reviews of the platform trial literature include hundreds of papers, yet case studies of real platform trials remain limited. Case studies are vital because they illustrate the concrete, unique challenges and opportunities presented to real-world platform trials. To this end, we propose a presentation on the Path to Prevention (P2P) phase 2 platform trial in Parkinson's disease. The P2P trial will investigate multiple therapies hypothesized to slow or prevent progression in Parkinson's disease gaining efficiency by using a common, perpetual trial infrastructure and sharing control participants, reinvesting saved resources into the investigation of new therapies. In addition to its platform efficiencies, the randomized P2P trial is nested within the Parkinson's Progression Marker Initiative (PPMI), an existing observational cohort of high-risk participants. This nesting allows P2P to leverage cohort data at both the population and individual level, as many people enroll in the PPMI cohort before enrolling in P2P.
The P2P platform uses two primary outcomes to explore treatment efficacy: a biomarker to measure change in dopamine transporter binding (mean striatal SBR) and a symptom scale to measure change in Parkinson's-related motor symptoms (MDS-UPDRS part III). Disease progression in each of these endpoints will inform treatment effect estimates within a disease progression modeling framework previously used successfully in Alzheimer's disease, ALS, and frontotemporal dementia. The trial's hierarchical primary analysis model combines information directly from its multiple therapeutic arms and indirectly from the broader PPMI study, incorporating the latest methods to handle possible time trends and augment platform trial control arms.
The P2P platform employs state of the art experimental design and modeling to efficiently advance the understanding and treatment of Parkinson's disease. Both P2P and PPMI are sponsored by the Michael J Fox Foundation.


Bayesian hierarchical models

disease progression modeling

natural history study

preventative treatments

platform trial

Bayesian borrowing 

Presenting Author

Cora Allen-Savietta, Berry Consultants

First Author

Cora Allen-Savietta, Berry Consultants

Target Audience



Women in Statistics and Data Science 2023