Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Kachuwaire OneHealth2021 13.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Asiimwe JofTransMed21 19.png|240px]]</div>
'''"[[Journal:Quality management system implementation in human and animal laboratories|Quality management system implementation in human and animal laboratories]]"'''
'''"[[Journal:From biobank and data silos into a data commons: Convergence to support translational medicine|From biobank and data silos into a data commons: Convergence to support translational medicine]]"'''


The ability to rapidly detect emerging and re-emerging threats relies on a strong network of [[Laboratory|laboratories]] providing high-quality testing services. Improving laboratory [[Quality management system|quality management systems]] (QMS) to ensure that these laboratories effectively play their critical role using a tailored stepwise approach can assist them to comply with World Health Organization's (WHO) International Health Regulations (IHRs), as well as the World Organization for Animal Health's (OIE) guidelines. Fifteen (15) laboratories in Armenia's human and veterinary laboratory networks were enrolled into a QMS strengthening program from 2017 to 2020. Training was provided for key staff, resulting in an implementation plan developed to address gaps. Routine mentorship visits were conducted. Audits were undertaken at baseline and post-implementation using standardized checklists to assess laboratory improvements ... ('''[[Journal:Quality management system implementation in human and animal laboratories|Full article...]]''')<br />
To drive [[Translational research|translational medicine]], modern day [[biobank]]s need to integrate with other sources of data (e.g., [[Health informatics|clinical]], [[genomics]]) to support novel data-intensive research. Currently, vast amounts of research and clinical data remain in silos, held and managed by individual researchers, operating under different standards and governance structures; such a framework impedes sharing and effective use of data. In this article, we describe the journey of British Columbia’s Gynecological Cancer Research Program (OVCARE) in moving a traditional tumor biobank, outcomes unit, and a collection of data silos into an integrated [[Open data#Policies and strategies|data commons]] to support data standardization and [[Data sharing|resource sharing]] under collaborative governance, as a means of providing the gynecologic cancer research community in British Columbia access to tissue samples and associated clinical and [[Molecular diagnostics|molecular]] data from thousands of patients ... ('''[[Journal:From biobank and data silos into a data commons: Convergence to support translational medicine|Full article...]]''')<br />
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Revision as of 14:07, 22 August 2022

Fig2 Asiimwe JofTransMed21 19.png

"From biobank and data silos into a data commons: Convergence to support translational medicine"

To drive translational medicine, modern day biobanks need to integrate with other sources of data (e.g., clinical, genomics) to support novel data-intensive research. Currently, vast amounts of research and clinical data remain in silos, held and managed by individual researchers, operating under different standards and governance structures; such a framework impedes sharing and effective use of data. In this article, we describe the journey of British Columbia’s Gynecological Cancer Research Program (OVCARE) in moving a traditional tumor biobank, outcomes unit, and a collection of data silos into an integrated data commons to support data standardization and resource sharing under collaborative governance, as a means of providing the gynecologic cancer research community in British Columbia access to tissue samples and associated clinical and molecular data from thousands of patients ... (Full article...)

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