Statistical design of Path to Prevention platform trial in early neuronal alpha-synuclein disease
The Path to Prevention (P2P) platform trial is a first-in-class, phase 2A, randomized, double-blind, placebo-controlled learning study. Its design expedites the assessment of investigational therapies for the treatment of early-stage Neuronal a-Synuclein Disease (NSD), a biological disease continuum that encompasses and often precedes clinically manifest Parkinson's Disease. P2P is embedded within the Parkinson's Precision Medicine Initiative (PPMI), a robust observational longitudinal cohort study on Parkinson's disease progression and a trial-facilitating enrollment framework. A regimen, comprised of an active investigational therapy and a matched placebo control, evaluates a therapeutic candidate within the P2P perpetual platform framework. Multiple regimens can be enrolled, enabling efficient testing of multiple therapeutics. A two-stage randomization scheme determines regimen sample size with 125 participants assigned to a regimen's active therapy and a variable number to placebo control. The treated follow up period is a minimum of 96 weeks and a maximum of 144 weeks, with the last randomized participant followed for 96 weeks. As a pioneering interventional trial in early-stage NSD, P2P endpoint selection was critically informed by modeling and analysis of available PPMI data. In P2P, regimens will be evaluated for efficacy using two primary endpoints: 1) a biomarker outcome of Dopamine Transporter Single-Photon Emission Computed Tomography (DAT SPECT) imaging measured by the bilateral putamen Specific Binding Ratio (SBR) and 2) a clinical outcome measured by the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III score. Each endpoint will be assessed separately using a longitudinal Bayesian mixed effects model, which compares the active treatment group to the shared placebo control group. The model uses regimen-specific controls at full weight and dynamically discounts controls from other regimens. Additionally, placebo control estimates are supplemented by non-randomized control data from the PPMI cohort. Clinical trial simulations, informed by longitudinal data from 275 P2P-eligible PPMI study participants (Age 60-81, 35% Female, 65% Male), were conducted to evaluate the design. Each regimen is well-powered to detect a 40% slowing in progression for both the clinical and biomarker primary endpoints when comparing active treatment to randomized control data. Supplementing the control estimation with non-randomized, P2P-eligible registry participant data increases power in the explored scenarios up to 4% for each endpoint. The embedded P2P platform trial is a powerful learning study that leverages statistical efficiencies from the platform trial design and established PPMI infrastructure and is poised to advance treatment development in early-stage NSD.
Authors
- Michael C. Brumm (ORCID: https://orcid.org/0000-0002-3173-9989)
- Catherine Kopil (ORCID: https://orcid.org/0000-0001-8678-7550)
- Nicola Pavese (ORCID: https://orcid.org/0000-0002-6801-6194)
- Barbara A. Wendelberger (ORCID: https://orcid.org/0000-0003-4426-9602)
- Amy M. Crawford (ORCID: https://orcid.org/0000-0002-8411-0084)
- Seung Ho Choi (ORCID: https://orcid.org/0000-0002-5257-5741)
- Thomas Francis Tropea (ORCID: https://orcid.org/0000-0003-0766-1496)
- Karl D. Kieburtz (ORCID: https://orcid.org/0000-0002-1645-6921)
- Ruth B. Schneider (ORCID: https://orcid.org/0000-0001-8094-4041)
- Frederic S. Goldstein (ORCID: https://orcid.org/0009-0006-6083-3444)
- Tatiana Foroud (ORCID: https://orcid.org/0000-0002-5549-2212)
- Danielle Larson (ORCID: https://orcid.org/0000-0002-8505-6614)
- Dixie J. Ecklund (ORCID: https://orcid.org/0000-0001-6086-962X)
- Tanya Simuni (ORCID: https://orcid.org/0000-0002-2347-1644)
- Andrew D. Siderowf (ORCID: https://orcid.org/0000-0002-1750-7698)
- Caroline M. Tanner (ORCID: https://orcid.org/0000-0002-3775-5082)
- Sohini Chowdhury (ORCID: https://orcid.org/0009-0009-8321-0081)
- David-Erick Lafontant (ORCID: https://orcid.org/0000-0003-2157-7151)
- Craig E Stanley
- Maggie McGuire Kuhl (ORCID: https://orcid.org/0009-0009-3187-4572)
- Kimberly Fabrizio
- Cora Allen‐Savietta (ORCID: https://orcid.org/0000-0001-7694-1948)
- Christopher S. Coffey (ORCID: https://orcid.org/0000-0002-8130-5484)
- Nijee Luthra (ORCID: https://orcid.org/0000-0002-6774-0711)
- Cornelia Kamp (ORCID: https://orcid.org/0000-0003-4158-8691)
- Kenneth Marek (ORCID: https://orcid.org/0000-0002-4197-5627)
- Tawny Willson
Institutions
- Northwestern University (US)
- University of Iowa (US)
- University of California, San Francisco (US)
- Michael J. Fox Foundation (US)
- University of Rochester Medical Center (US)
- Institute for Neurodegenerative Disorders (US)
- Indiana University Indianapolis (US)
- Indiana University School of Medicine (US)
- Berry Consultants, LLC (United States) (US)
- University of Rochester (US)
- University of Pennsylvania (US)
- Newcastle University (GB)
Publication Details
- Journal
- medRxiv
- Published
- 2026-11-06
- DOI
- https://doi.org/10.64898/2026.11.04.26367306
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- preprint
Funders
- Michael J. Fox Foundation for Parkinson's Research
- Bristol-Myers Squibb
- Eli Lilly and Company
- Sanofi
- Patient-Centered Outcomes Research Institute
- Regeneron Pharmaceuticals
- Ionis Pharmaceuticals
- ACADIA Pharmaceuticals
- Voyager Therapeutics
- Weston Family Foundation
- H. Lundbeck A/S
- National Institutes of Health
- Genentech