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Developing a Virtual Research Environment in the Parkinson's Progression Markers Initiative: myPPMI

  • Craig E. Stanley*
  • , Kimberly Fabrizio
  • , Bridget A. McMahon
  • , Auldyn Matthews-McGee
  • , Cailey Fitzgerald
  • , Zeina Singh
  • , Nichole H. Rigby
  • , John Michael Talarico
  • , Ethan G. Brown
  • , Monica Korell
  • , Maggie McGuire Kuhl
  • , Christina Destro
  • , Nicola Pavese
  • , Alicia Garrido
  • , Brit Mollenhauer
  • , Sohini Chowdhury
  • , Kenneth Marek
  • , Caroline M. Tanner
  • , Thomas F. Tropea*
  • , Kenneth Marek
  • Tanya Simuni, Andrew Siderowf, Caroline Tanner, Thomas F. Tropea*, Tatiana Foroud, Lana Chahine, Brit Mollenhauer, Kalpana Merchant, Douglas Galasko, Christopher Coffey, Kathleen Poston, Roseanne Dobkin, Ethan Brown, Roy Alcalay, Dan Weintraub, Emily Flagg, Kimberly Fabrizio, Susan Bressman, Cornelis Blauwendraat, Paola Casalin, Sonya Dumanis, Raymond James, Karl Kieburtz, Sneha Mantri, Werner Poewe, Michael Schwarzschild, John Seibyl, David Standaert, Sonja Jonsdottir, Claire Pauly, the Parkinson’s Progression Markers Initiative
*Corresponding author for this work

Research output: Contribution to journal › Editorial

Abstract

In the 15 years since Parkinson's Progression Markers Initiative (PPMI) launched, research conduct has advanced with broader connectivity, enabling virtual and hybrid methods for recruitment, engagement, education, and data collection. To meet evolving needs, PPMI created “myPPMI,” which has grown from an informational portal to a multi-country, participant-centered, virtual research environment integrating education, screening, e-consent, longitudinal non-motor and motor assessments, and biospecimen referral. Built on a secure, cloud-native architecture with daily analytics and a multi-tier support model, myPPMI enables precision recruitment, real-time eligibility matching, and standardized low-burden data capture across studies. The platform is designed to enable focused data collection from individuals or groups based on the data they have already provided. This strategy provides the tools to establish precise subsets of high interest that could be targeted for further data acquisition. Usability testing and rapid global scaling demonstrate a generalizable, decentralized framework for biomarker-driven, Parkinson's disease research. ANN NEUROL 2026.

Original languageEnglish
Number of pages8
JournalAnnals of Neurology
Early online date21 Apr 2026
DOIs
Publication statusPublished - 21 Apr 2026

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