Precompetitive data sharing as a catalyst to address unmet needs in Parkinson's disease


Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease.

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Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Aston University (General)
Additional Information: © 2015 – IOS Press and the authors. All rights reserved. This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License.
Uncontrolled Keywords: collaboration,data integration,data standards,privacy,quantitative disease progression,regulatory science,Clinical Neurology,Cellular and Molecular Neuroscience
Publication ISSN: 1877-718X
Last Modified: 10 Jun 2024 07:15
Date Deposited: 01 Oct 2015 10:25
Full Text Link: http://content. ... sease/jpd150570
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2015-09-14
Authors: Stephenson, Diane
Hu, Michele T.
Romero, Klaus
Breen, Kieran
Burn, David
Ben-Shlomo, Yoav
Bhattaram, Atul
Isaac, Maria
Venuto, Charles
Kubota, Ken
Little, Max A. (ORCID Profile 0000-0002-1507-3822)
Friend, Stephen
Lovestone, Simon
Morris, Huw R.
Grosset, Donald
Sutherland, Margaret
Gallacher, John
Williams-Gray, Caroline
Bain, Lisa J.
Avilés, Enrique
Marek, Ken
Toga, Arthur W.
Stark, Yafit
Gordon, Mark Forrest
Ford, Steve


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