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https://pdbp.ninds.nih.gov

Common data management resource and web portal to promote discovery of Parkinson's Disease diagnostic and progression biomarker candidates for early detection and measurement of disease progression. PDBP will serve as multi-faceted platform for integrating existing biomarker efforts, standardizing data collection and management across these efforts, accelerating discovery of new biomarkers, and fostering and expanding collaborative opportunities for all stakeholders.

Proper citation: Parkinson’s Disease Biomarkers Program Data Management Resource (PDBP DMR) (RRID:SCR_002517) Copy   

•   Source: SciCrunch Registry

http://www.commondataelements.ninds.nih.gov

The purpose of the NINDS Common Data Elements (CDEs) Project is to standardize the collection of investigational data in order to facilitate comparison of results across studies and more effectively aggregate information into significant metadata results. The goal of the National Institute of Neurological Disorders and Stroke (NINDS) CDE Project specifically is to develop data standards for clinical research within the neurological community. Central to this Project is the creation of common definitions and data sets so that information (data) is consistently captured and recorded across studies. To harmonize data collected from clinical studies, the NINDS Office of Clinical Research is spearheading the effort to develop CDEs in neuroscience. This Web site outlines these data standards and provides accompanying tools to help investigators and research teams collect and record standardized clinical data. The Institute still encourages creativity and uniqueness by allowing investigators to independently identify and add their own critical variables. The CDEs have been identified through review of the documentation of numerous studies funded by NINDS, review of the literature and regulatory requirements, and review of other Institute''s common data efforts. Other data standards such as those of the Clinical Data Interchange Standards Consortium (CDISC), the Clinical Data Acquisition Standards Harmonization (CDASH) Initiative, ClinicalTrials.gov, the NINDS Genetics Repository, and the NIH Roadmap efforts have also been followed to ensure that the NINDS CDEs are comprehensive and as compatible as possible with those standards. CDEs now available: * General (CDEs that cross diseases) Updated Feb. 2011! * Congenital Muscular Dystrophy * Epilepsy (Updated Sept 2011) * Friedreich''s Ataxia * Parkinson''s Disease * Spinal Cord Injury * Stroke * Traumatic Brain Injury CDEs in development: * Amyotrophic Lateral Sclerosis (Public review Sept 15 through Nov 15) * Frontotemporal Dementia * Headache * Huntington''s Disease * Multiple Sclerosis * Neuromuscular Diseases ** Adult and pediatric working groups are being finalized and these groups will focus on: Duchenne Muscular Dystrophy, Facioscapulohumeral Muscular Dystrophy, Myasthenia Gravis, Myotonic Dystrophy, and Spinal Muscular Atrophy The following tools are available through this portal: * CDE Catalog - includes the universe of all CDEs. Users are able to search the full universe to isolate a subset of the CDEs (e.g., all stroke-specific CDEs, all pediatric epilepsy CDEs, etc.) and download details about those CDEs. * CRF Library - (a.k.a., Library of Case Report Form Modules and Guidelines) contains all the CRF Modules that have been created through the NINDS CDE Project as well as various guideline documents. Users are able to search the library to find CRF Modules and Guidelines of interest. * Form Builder - enables users to start the process of assembling a CRF or form by allowing them to choose the CDEs they would like to include on the form. This tool is intended to assist data managers and database developers to create data dictionaries for their study forms.

Proper citation: NINDS Common Data Elements (RRID:SCR_006577) Copy   

•   Source: SciCrunch Registry

http://www.ninds.nih.gov/news_and_events/proceedings/20101217-NEXT.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 26,2022. A unique clinical trial network open to studies of more than 400 neurological diseases, allowing investigators to more efficiently pursue new therapies based on scientific opportunity. The network has a centralized IRB serving 25 sites, which will allow trials to move faster, without the need to coordinate IRBs at each individual site. It is not necessary to be part of the NeuroNEXT infrastructure to propose and conduct a study within the network. The Network for Excellence in Neuroscience Clinical Trials, or NeuroNEXT, was created to conduct studies of treatments for neurological diseases through partnerships with academia, private foundations, and industry. The network is designed to expand the National Institute of Neurological Disorders and Stroke''s (NINDS) capability to test promising new therapies, increase the efficiency of clinical trials before embarking on larger studies, and respond quickly as new opportunities arise to test promising treatments for people with neurological disorders. The NeuroNEXT program aims to: * Provide a robust, standardized, and accessible infrastructure to facilitate rapid development and implementation of protocols in neurological disorders affecting adult and/or pediatric populations. The network includes multiple Clinical Sites, one Clinical Coordinating Center (CCC) and one Data Coordinating Center (DCC). * Support scientifically sound, possibly biomarker-informed, Phase II clinical trials that provide data for clear go/no-go decisions. * Energize and mobilize federal, industry, foundations and patient advocacy partners by leveraging existing relationships between NINDS and NeuroNEXT to organize high impact Phase II clinical trials for neurological disorders. * Expand the pool of experienced clinical investigators and research staff who are prepared to be leaders of multicenter clinical research trials. * Working with NeuroNEXT is a cooperative venture between NINDS, the NeuroNEXT network and the applicant.

Proper citation: NeuroNEXT (RRID:SCR_006760) Copy   

•   Source: SciCrunch Registry