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      Precompetitive Data Sharing as a Catalyst to Address Unmet Needs in Parkinson’s Disease 1

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          Abstract

          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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          Most cited references21

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          Characterizing mild cognitive impairment in incident Parkinson disease: the ICICLE-PD study.

          To describe the frequency of mild cognitive impairment (MCI) in Parkinson disease (PD) in a cohort of newly diagnosed incident PD cases and the associations with a panel of biomarkers. Between June 2009 and December 2011, 219 subjects with PD and 99 age-matched controls participated in clinical and neuropsychological assessments as part of a longitudinal observational study. Consenting individuals underwent structural MRI, lumbar puncture, and genotyping for common variants of COMT, MAPT, SNCA, BuChE, EGF, and APOE. PD-MCI was defined with reference to the new Movement Disorder Society criteria. The frequency of PD-MCI was 42.5% using level 2 criteria at 1.5 SDs below normative values. Memory impairment was the most common domain affected, with 15.1% impaired at 1.5 SDs. Depression scores were significantly higher in those with PD-MCI than the cognitively normal PD group. A significant correlation was found between visual Pattern Recognition Memory and cerebrospinal β-amyloid 1-42 levels (β standardized coefficient = 0.350; p = 0.008) after controlling for age and education in a linear regression model, with lower β-amyloid 1-42 and 1-40 levels observed in those with PD-MCI. Voxel-based morphometry did not reveal any areas of significant gray matter loss in participants with PD-MCI compared with controls, and no specific genotype was associated with PD-MCI at the 1.5-SD threshold. In a large cohort of newly diagnosed PD participants, PD-MCI is common and significantly correlates with lower cerebrospinal β-amyloid 1-42 and 1-40 levels. Future longitudinal studies should enable us to determine those measures predictive of cognitive decline.
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            The cognitive ability of an incident cohort of Parkinson's patients in the UK. The CamPaIGN study.

            We have used multiple sources to identify a population-representative cohort of newly diagnosed patients with parkinsonism and Parkinson's disease in the UK over a 2-year period. All patients have been invited to participate in a detailed clinical assessment either at home or in an outpatient clinic. These assessments have been used to refine clinical diagnoses of parkinsonism using established criteria, and describe some of the phenotypic variability of Parkinson's disease at the time of diagnosis. The crude incidence of Parkinson's disease was 13.6/10(5yr-1) [confidence interval (CI) 11.8-15.6 and of parkinsonism was 20.9/10(5yr-1) (CI 18.7-23.3). Age-standardized to the 1991 European population, the incidence figures become 10.8/10(5yr-1) (CI 9.4-12.4) for Parkinson's disease and 16.6/10(5yr-1) (CI 14.8-18.6) for parkinsonism. Thirty-six per cent of the Parkinson's disease patients had evidence of cognitive impairment based on their performance in the Mini-Mental State Examination, a pattern recognition task, and the Tower of London task. The pattern of cognitive deficits seen among these patients using these and further cognitive tasks suggests that sub-groups of patients based on cognitive ability might be identifiable even in the early stages of disease, which may reflect regional differences in the underlying neuropathological processes.
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              Motor fluctuations and dyskinesias in Parkinson's disease: clinical manifestations.

              Fluctuations in the symptoms of Parkinson's disease (PD), such as wearing-off and on-off effects, and dyskinesias are related to a variety of factors, including duration and dosage of levodopa, age at onset, stress, sleep, food intake, and other pharmacokinetic and pharmacodynamic mechanisms. The majority of patients, particularly those with young onset of PD, experience these levodopa-related adverse effects after a few years of treatment. Assessment of these motor complications is difficult because of the marked clinical variability between and within patients. Daily diaries have been used in clinical trials designed to assess the effects of various pharmacological and surgical interventions on motor fluctuations and dyskinesias. The most common type of dyskinesia, called "peak-dose dyskinesia", usually consists of stereotypical choreic or ballistic movements involving the head, trunk, and limbs, and occasionally, the respiratory muscles, whereas tremor and punding are less-common complications. Dystonia is also typically seen in patients with diphasic dyskinesia and wearing-off effect. Recognition of the full spectrum of clinical phenomenology of levodopa-related motor complications is essential for their treatment and prevention. (c) 2005 Movement Disorder Society.
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                Author and article information

                Journal
                J Parkinsons Dis
                J Parkinsons Dis
                JPD
                Journal of Parkinson's Disease
                IOS Press (Nieuwe Hemweg 6B, 1013 BG Amsterdam, The Netherlands )
                1877-7171
                1877-718X
                14 September 2015
                2015
                : 5
                : 3
                : 581-594
                Affiliations
                [a ]Critical Path Institute, CAMD, Tucson, AZ, USA
                [b ]Nuffield Department of Clinical Neurosciences, University of Oxford, Neurology Department, Level 3, West Wing, John Radcliffe Hospital, Headley Way, Headington, Oxford, UK
                [c ]Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
                [d ]Scientific consultant, London, UK
                [e ]Henry Wellcome Building, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
                [f ]University of Bristol, Canynge Hall, Bristol, UK
                [g ]US Food and Drug Administration (FDA), New Hampshire Avenue, Silver Spring, MD, USA
                [h ]EMA, 30 Churchill Place, Canary Wharf, London, UK
                [i ]U of Rochester Medical Center, Crittenden Blvd, Rochester, NY, USA
                [j ]Michael J Fox Foundation for Parkinson’s Research, Seventh Avenue, New York, NY, USA
                [k ]Aston University and MIT, Aston University, Aston Triangle, Birmingham, Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
                [l ]Sage Bionetworks, Seattle, WA, USA
                [m ]Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK Department of Neurology, Royal Free Hospital, London, UK Neurology, National Hospital for Neurology, London, UK
                [n ]Institute of Neuroscience and Psychology, University of Glasgow, Scotland, UK
                [o ]National Institute of Neurological Disorders and Stroke (NINDS), Neuroscience Center, Bethesda, MD, USA
                [p ]Department of Psychiatry, University of Oxford Hospital, Warneford, Oxford, UK
                [q ]Department of Clinical Neurosciences, John Van Geest Centre for Brain Repair, University of Cambridge, E.D. Adrian Building, Forvie Site, Robinson Way, Cambridge, UK
                [r ]Independent Scientific & Medical Writer, Savits Drive, Elverson, PA, USA
                [s ]Institute of Neurodegenerative Diseases, Parkinson’s Progression Markers Initiative, Suite 8B, New Haven, CT, USA
                [t ]Laboratory of Neuro Imaging, Keck School of Medicine of USC, University of Southern California, CA, USA
                [u ]Teva Pharmaceutical Industries Ltd., Petach Tikva, Israel
                [v ]Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA
                [w ]Parkinson’s UK, London, UK
                Author notes
                [* ]Correspondence to: Diane T. Stephenson, Critical Path Institute, 1730 E. River Rd, Tucson, AZ 85718, USA. Tel.: +1 520 382 1405; Fax: +1 520 547 3456; dstephenson@ 123456c-path.org
                [1]

                Summary of Parkinson’s UK, London Workshop, co-organized by the Coalition Against Major Diseases (CAMD)

                Article
                JPD150570
                10.3233/JPD-150570
                4887129
                26406139
                82bf6dd8-50c5-49b6-8e29-f33b5069b3ce
                IOS Press and the authors. All rights reserved

                This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Categories
                Research Article

                data standards,privacy,data integration,collaboration,quantitative disease progression,regulatory science

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