Cargando…
Data silos are undermining drug development and failing rare disease patients
Data silos are proliferating while research and development activity explode following genetic and immunological advances for many clinically described disorders with previously unknown etiologies. The latter event has inspired optimism in the patient, clinical, and research communities that disease...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8025897/ https://www.ncbi.nlm.nih.gov/pubmed/33827602 http://dx.doi.org/10.1186/s13023-021-01806-4 |
_version_ | 1783675577281019904 |
---|---|
author | Denton, Nathan Molloy, Monique Charleston, Samantha Lipset, Craig Hirsch, Jonathan Mulberg, Andrew E. Howard, Paul Marsh, Eric D. |
author_facet | Denton, Nathan Molloy, Monique Charleston, Samantha Lipset, Craig Hirsch, Jonathan Mulberg, Andrew E. Howard, Paul Marsh, Eric D. |
author_sort | Denton, Nathan |
collection | PubMed |
description | Data silos are proliferating while research and development activity explode following genetic and immunological advances for many clinically described disorders with previously unknown etiologies. The latter event has inspired optimism in the patient, clinical, and research communities that disease-specific treatments are on the way. However, we fear the tendency of various stakeholders to balkanize databases in proprietary formats, driven by current economic and academic incentives, will inevitably fragment the expanding knowledge base and undermine current and future research efforts to develop much-needed treatments. The proliferation of proprietary databases, compounded by a paucity of meaningful outcome measures and/or good natural history data, slows our ability to generate scalable solutions to benefit chronically underserved patient populations in ways that would translate to more common diseases. The current research and development landscape sets too many projects up for unnecessary failure, particularly in the rare disease sphere, and does a grave disservice to highly vulnerable patients. This system also encourages the collection of redundant data in uncoordinated parallel studies and registries to ultimately delay or deny potential treatments for ostensibly tractable diseases; it also promotes the waste of precious time, energy, and resources. Groups at the National Institutes of Health and Food and Drug Administration have started programs to address these issues. However, we and many others feel there should be significantly more discussion of how to coordinate and scale registry efforts. Such discourse aims to reduce needless complexity and duplication of efforts, as well as promote a pre-competitive knowledge ecosystem for rare disease drug development that cultivates and accelerates innovation. |
format | Online Article Text |
id | pubmed-8025897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80258972021-04-08 Data silos are undermining drug development and failing rare disease patients Denton, Nathan Molloy, Monique Charleston, Samantha Lipset, Craig Hirsch, Jonathan Mulberg, Andrew E. Howard, Paul Marsh, Eric D. Orphanet J Rare Dis Position Statement Data silos are proliferating while research and development activity explode following genetic and immunological advances for many clinically described disorders with previously unknown etiologies. The latter event has inspired optimism in the patient, clinical, and research communities that disease-specific treatments are on the way. However, we fear the tendency of various stakeholders to balkanize databases in proprietary formats, driven by current economic and academic incentives, will inevitably fragment the expanding knowledge base and undermine current and future research efforts to develop much-needed treatments. The proliferation of proprietary databases, compounded by a paucity of meaningful outcome measures and/or good natural history data, slows our ability to generate scalable solutions to benefit chronically underserved patient populations in ways that would translate to more common diseases. The current research and development landscape sets too many projects up for unnecessary failure, particularly in the rare disease sphere, and does a grave disservice to highly vulnerable patients. This system also encourages the collection of redundant data in uncoordinated parallel studies and registries to ultimately delay or deny potential treatments for ostensibly tractable diseases; it also promotes the waste of precious time, energy, and resources. Groups at the National Institutes of Health and Food and Drug Administration have started programs to address these issues. However, we and many others feel there should be significantly more discussion of how to coordinate and scale registry efforts. Such discourse aims to reduce needless complexity and duplication of efforts, as well as promote a pre-competitive knowledge ecosystem for rare disease drug development that cultivates and accelerates innovation. BioMed Central 2021-04-07 /pmc/articles/PMC8025897/ /pubmed/33827602 http://dx.doi.org/10.1186/s13023-021-01806-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Position Statement Denton, Nathan Molloy, Monique Charleston, Samantha Lipset, Craig Hirsch, Jonathan Mulberg, Andrew E. Howard, Paul Marsh, Eric D. Data silos are undermining drug development and failing rare disease patients |
title | Data silos are undermining drug development and failing rare disease patients |
title_full | Data silos are undermining drug development and failing rare disease patients |
title_fullStr | Data silos are undermining drug development and failing rare disease patients |
title_full_unstemmed | Data silos are undermining drug development and failing rare disease patients |
title_short | Data silos are undermining drug development and failing rare disease patients |
title_sort | data silos are undermining drug development and failing rare disease patients |
topic | Position Statement |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8025897/ https://www.ncbi.nlm.nih.gov/pubmed/33827602 http://dx.doi.org/10.1186/s13023-021-01806-4 |
work_keys_str_mv | AT dentonnathan datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients AT molloymonique datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients AT charlestonsamantha datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients AT lipsetcraig datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients AT hirschjonathan datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients AT mulbergandrewe datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients AT howardpaul datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients AT marshericd datasilosareunderminingdrugdevelopmentandfailingrarediseasepatients |