The Personalized Parkinson Project (PPP) — PPP  

Parkinson Disease Clinical Trial

Official title: The Personalized Parkinson Project (De Parkinson Op Maat Studie)

Status Active, not recruiting

Clinical Trial Summary

Background Our understanding of PD has stagnated, partly due to the limited patient diversity and brief followup captured in most study cohorts. Additionally, potentially valuable biomarkers derived from different types of measurements are rarely analyzed in an integrated fashion. Objective This study aims to create a longitudinal dataset of clinical, molecular, imaging, and continuous wearable sensor-based data from a representative Parkinson's disease (PD) cohort. Data will be made available to researchers worldwide to accelerate the discovery of novel etiological insights, development of new therapeutic approaches, and personalized disease management. For this purpose, an extensible norm for sharing research data will be developed, meeting the latest data privacy and security standards. Methods Supported by a multinational, public-private partnership, a prospective cohort study was designed to include 650 representative PD patients (disease duration <5 years). Comprehensive follow-up for at least 2 years includes: (1) annual assessment at the study center for acquisition of detailed clinimetric data, magnetic resonance imaging, and biospecimens (plasma, serum, cerebrospinal fluid (CSF), stool) and (2) collection of data from the home environment, using self-assessments and an advanced wrist-worn wearable device to continuously measure biological and environmental signals. Collection, storage, and sharing of these research data will be facilitated by a new method to protect privacy and enhance security using polymorphic encryption and pseudonymization (PEP), a methodology that combines advanced encryption with distributed pseudonymization and data access management. Conclusion This study is unique, as it includes a cohort of unbiased subjects with recently diagnosed PD, creating an unprecedented dataset that combines longitudinally collected clinical, molecular, imaging, and data from wearable sensors using state of the art technology. The single-center study design minimizes measurement variability. Finally, the innovative methodology for data privacy and protection might serve as a new international standard for sharing research data.

Clinical Trial Description

The Personalized Parkinson Project proposes an unbiased approach to biomarker development with multiple clinical, genomic and other molecular, and imaging biomarkers measured in a large population, measured at 3 time points (baseline visit, one year follow-up, and two years' follow-up). In addition, the study protocol includes day-to-day patient monitoring with a multisensor wearable device, the Verily Study Watch, that continuously collects data (movement, pulse, skin temperature, ambient information) and allows for real-time data collection between study visits. The goal of the device is to collect high-resolution, continuous biological signals from the body. These measurements of physiology, activity, and environmental conditions over the course of a 2-year study will be used to create a quantified functional assessment of patients with PD. Mapping these signals with clinical outcomes such as disease progression will allow the investigators to evaluate the relationship between biosensor data and the clinical variables, genotypic, and imaging biomarkers collected in the study. This study is intended to create a unique resource of genotypic, functional, and phenotypic data collected longitudinally on a cohort of Dutch subjects with PD (n=650), allowing the Research Collaborators to address a series of hypothesis-driven research questions. The aim is to develop novel etiological insights, to identify biomarkers that can assist in predicting differences in prognosis and treatment response between patients, to improve existing treatments, to develop new therapeutic approaches, and to develop a more precise and personalized disease management approach. Additionally, the cohort will serve as a source of data that can be accessed by qualified researchers worldwide, allowing them to add their research capacity to further address the main aims of this study. For this reason, data governance will be managed by dedicated advisory boards and data review committees, as specified in the study protocol. Participation in this study and results from this study will not be used for patient treatment decisions. The aim of this study is threefold: 1. The primary objective of the study is to perform a set of hypothesis-driven analyses on the study data set, aiming to correlate established biomarkers (obtained clinically, from brain magnetic resonance imaging (MRI), from cerebrospinal fluid (CSF), from known genetic factors, and from monitoring of biosensors signals) to the rate of disease progression, and to responses to treatment (both pharmacological and behavioral, such as participation in exercise). Also, the investigators aim to identify biomarkers that can assist in predicting differences in prognosis and treatment response between patients. Finally, by developing novel etiological and pathophysiological insights, the study aims to improve existing treatments and to develop new therapeutic approaches, as a basis for development of a more precise and personalized disease management approach. 2. The secondary objective of the study is to evaluate the Verily Study Watch, to assess how these devices could provide information about the function of patients with PD. 3. The tertiary objective of this study is to create an extensive longitudinal dataset describing the genetic, clinical, functional, and phenotypic characteristics of a representative Parkinson's disease (PD) subject cohort (n = 650) to allow researchers to investigate important unanswered questions in PD. ;

Related Conditions & MeSH terms

• Parkinson Disease

• NCT number: NCT03364894
• Study type: Observational
• Source: Radboud University Medical Center
• Status: Active, not recruiting
• Start date: October 1, 2017
• Completion date: December 31, 2023