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Title: | FAIR data for next generation management of multiple sclerosis | Authors: | PEETERS, Liesbet | Issue Date: | 2018 | Source: | Multiple Sclerosis Journal, 24(9), p. 1151-1156 | Abstract: | Multiple sclerosis (MS) is a progressive demyelinating and degenerative disease of the central nervous system with symptoms depending on the disease type and the site of lesions and is featured by heterogeneity of clinical expressions and responses to treatment strategies. An individualized clinical follow-up and multidisciplinary treatment is required. Transforming the population-based management of today into an individualized, personalized and precision-level management is a major goal in research. Indeed, a complex and unique interplay between genetic background and environmental exposure in each case likely determines clinical heterogeneity. To reach insights at the individual level, extensive amount of data are required. Many databases have been developed over the last few decades, but access to them is limited, and data are acquired in different ways and differences in definitions and indexing and software platforms preclude direct integration. Most existing (inter)national registers and IT platforms are strictly observational or focus on disease epidemiology or access to new disease modifying drugs. Here, a method to revolutionize management of MS to a personalized, individualized and precision level is outlined. The key to achieve this next level is FAIR data. | Keywords: | individualized medicine; data management; multidisciplinary treatment; FAIR data; next-generation management; multiple sclerosis | Document URI: | http://hdl.handle.net/1942/28247 | ISSN: | 1352-4585 | e-ISSN: | 1477-0970 | DOI: | 10.1177/1352458517748475 | ISI #: | 000439604700002 | Rights: | This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2019 |
Appears in Collections: | Research publications |
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