Abstract
ALS is a rare disorder whose cause and pathogenesis is largely unknown ( 1 ). There is a recognized need to develop biomarkers for ALS to better understand the disease, expedite diagnosis and to facilitate therapy development. Collaboration is essential to obtain a sufficient number of samples to allow statistically meaningful studies. The availability of high quality biological specimens for research purposes requires the development of standardized methods for collection, long-term storage, retrieval and distribution of specimens. The value of biological samples to scientists and clinicians correlates with the completeness and relevance of phenotypical and clinical information associated with the samples ( 2 , 3 ). While developing a secure Web-based system to manage an inventory of multi-site BioRepositories, algorithms were implemented to facilitate ad hoc parametric searches across heterogeneous data sources that contain data from clinical trials and research studies. A flexible schema for a barcode label was introduced to allow association of samples to these data. The ALSBank™ BioRepository platform solution for managing biological samples and associated data is currently deployed by the Northeast ALS Consortium (NEALS). The NEALS Consortium and the Massachusetts General Hospital (MGH) Neurology Clinical Trials Unit (NCTU) support a network of multiple BioBanks, thus allowing researchers to take advantage of a larger specimen collection than they might have at an individual institution. Standard operating procedures are utilized at all collection sites to promote common practices for biological sample integrity, quality control and associated clinical data. Utilizing this platform, we have created one of the largest virtual collections of ALS-related specimens available to investigators studying ALS.
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