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2.
Orphanet J Rare Dis ; 17(1): 389, 2022 10 27.
Artículo en Inglés | MEDLINE | ID: mdl-36303170

RESUMEN

Scientific advances in the understanding of the genetics and mechanisms of many rare diseases with previously unknown etiologies are inspiring optimism in the patient, clinical, and research communities and there is hope that disease-specific treatments are on the way. However, the rare disease community has reached a critical point in which its increasingly fragmented structure and operating models are threatening its ability to harness the full potential of advancing genomic and computational technologies. Changes are therefore needed to overcome these issues plaguing many rare diseases while also supporting economically viable therapy development. In "Data silos are undermining drug development and failing rare disease patients (Orphanet Journal of Rare Disease, Apr 2021)," we outlined many of the broad issues underpinning the increasingly fragmented and siloed nature of the rare disease space, as well as how the issues encountered by this community are representative of biomedical research more generally. Here, we propose several initiatives for key stakeholders - including regulators, private and public foundations, and research institutions - to reorient the rare disease ecosystem and its incentives in a way that we believe would cultivate and accelerate innovation. Specifically, we propose supporting non-proprietary patient registries, greater data standardization, global regulatory harmonization, and new business models that encourage data sharing and research collaboration as the default mode. Leadership needs to be integrated across sectors to drive meaningful change between patients, industry, sponsors, and academic medical centers. To transform the research and development landscape and unlock its vast healthcare, economic, and scientific potential for rare disease patients, a new model is ultimately the goal for all.


Asunto(s)
Investigación Biomédica , Enfermedades Raras , Humanos , Ecosistema , Difusión de la Información , Atención a la Salud
3.
Orphanet J Rare Dis ; 16(1): 161, 2021 04 07.
Artículo en Inglés | MEDLINE | ID: mdl-33827602

RESUMEN

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.


Asunto(s)
Ecosistema , Enfermedades Raras , Bases de Datos Factuales , Desarrollo de Medicamentos , Humanos , Enfermedades Raras/tratamiento farmacológico , Sistema de Registros
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