Difference between revisions of "Translational research informatics"

From LIMSWiki
Jump to navigationJump to search
m (→‎External sites: Bulletss)
m (Added attribution.)
 
(3 intermediate revisions by the same user not shown)
Line 1: Line 1:
__NOTOC__
'''Translational research informatics''' (TRI) (or '''translational informatics''' or TI) is a sister domain to or a sub-domain of biomedical or [[health informatics|clinical informatics]] concerned with the application of [[Informatics (academic field)|informatics]] theory and methods to [[translational research]]. While translational informatics has elements in common with clinical informatics, it's primarily concerned with enabling multi-disciplinary research to accelerate clinical outcomes, with clinical trials often being the natural step beyond translational research.
'''Translational research informatics''' (TRI) (or '''translational informatics''' or TI) is a sister domain to or a sub-domain of biomedical or [[health informatics|clinical informatics]] concerned with the application of [[Informatics (academic field)|informatics]] theory and methods to [[translational research]]. While translational informatics has elements in common with clinical informatics, it's primarily concerned with enabling multi-disciplinary research to accelerate clinical outcomes, with clinical trials often being the natural step beyond translational research.


Line 4: Line 5:


1. "integrated solutions to manage the: (i) logistics, (ii) data integration, and (iii) collaboration, and (iv] knowledge generation required by translational investigators and their supporting institutions."
1. "integrated solutions to manage the: (i) logistics, (ii) data integration, and (iii) collaboration, and (iv] knowledge generation required by translational investigators and their supporting institutions."
<ref name="NDNAnderson">{{cite web |url=http://www.neurodevnet.ca/sites/default/files/neurodevnet/download/Anderson_NeuroDevNet_0103.ppt |archiveurl=https://web.archive.org/web/20140323010951/http://www.neurodevnet.ca/sites/default/files/neurodevnet/download/Anderson_NeuroDevNet_0103.ppt |format=PPT |title=Pragmatic translational informatics: Supporting collaborative science |author=Anderson, Nicholas |publisher=NeuroDevNet |date=2013 |archivedate=23 March 2013 |accessdate=23 March 2013}}</ref>
<ref name="NDNAnderson">{{cite web |url=http://www.neurodevnet.ca/sites/default/files/neurodevnet/download/Anderson_NeuroDevNet_0103.ppt |archiveurl=https://web.archive.org/web/20140323010951/http://www.neurodevnet.ca/sites/default/files/neurodevnet/download/Anderson_NeuroDevNet_0103.ppt |format=PPT |title=Pragmatic translational informatics: Supporting collaborative science |author=Anderson, Nicholas |publisher=NeuroDevNet |date=2013 |archivedate=23 March 2014 |accessdate=23 March 2014}}</ref>


...or in more lengthy terms:
...or in more lengthy terms:
Line 10: Line 11:
2. "the informatics subdiscipline that is primarily concerned with the development and application of biomedical informatics theories, methods, and best practices intended to support: 1) the acquisition of knowledge and information from the preceding sources; 2) the representation of such knowledge and information in an actionable format (e.g., readily consumed and analyzed, usually through the use of computational tools and applications), and the subsequent dissemination of that knowledge or information to targeted end-users or analytical platforms; and 3) the semantic integration of disparate data sources to support the discovery and verification/validation of complex bio-marker-to-phenotype relationships that may collectively define a translational biomedical knowledge model."<ref name="PayneTI">{{cite journal |url=http://physiolgenomics.physiology.org/content/39/3/131.full |journal=Physiological Genomics |year=November 2009 |volume=39 |issue=3 |page=131–140 |title=Translational informatics: enabling high-throughput research paradigms |author=Payne, Philip R. O.; Embi, Peter J.; Sen, Chandan K. |doi=10.​1152/​physiolgenomics.​00050.​2009 |accessdate=22 March 2014}}</ref>
2. "the informatics subdiscipline that is primarily concerned with the development and application of biomedical informatics theories, methods, and best practices intended to support: 1) the acquisition of knowledge and information from the preceding sources; 2) the representation of such knowledge and information in an actionable format (e.g., readily consumed and analyzed, usually through the use of computational tools and applications), and the subsequent dissemination of that knowledge or information to targeted end-users or analytical platforms; and 3) the semantic integration of disparate data sources to support the discovery and verification/validation of complex bio-marker-to-phenotype relationships that may collectively define a translational biomedical knowledge model."<ref name="PayneTI">{{cite journal |url=http://physiolgenomics.physiology.org/content/39/3/131.full |journal=Physiological Genomics |year=November 2009 |volume=39 |issue=3 |page=131–140 |title=Translational informatics: enabling high-throughput research paradigms |author=Payne, Philip R. O.; Embi, Peter J.; Sen, Chandan K. |doi=10.​1152/​physiolgenomics.​00050.​2009 |accessdate=22 March 2014}}</ref>


The field is relatively new, with most Clinical and Translational Science Awards (CTSAs) funding and research going into informatics tools and systems enabling the end-to-end TRI requirements.<ref name="CTSATools">{{cite web |url=https://www.ctsacentral.org/reports/sharing/tools/public |title=Tool Awareness Project |publisher=CTSA |accessdate=22 March 2014}}</ref>
The field is relatively new, with most Clinical and Translational Science Awards (CTSAs) funding and research going into informatics tools and systems enabling the end-to-end TI requirements.<ref name="CTSATools">{{cite web |url=https://www.ctsacentral.org/reports/sharing/tools/public |title=Tool Awareness Project |publisher=CTSA |accessdate=22 March 2014}}</ref>


==Systems in translational informatics==
==Systems in translational informatics==
Line 54: Line 55:
* [https://www.ctsacentral.org/ Clinical and Translational Science Awards]<br />
* [https://www.ctsacentral.org/ Clinical and Translational Science Awards]<br />
* [http://www.amia.org American Medical Informatics Association (AMIA)]<br />
* [http://www.amia.org American Medical Informatics Association (AMIA)]<br />
==Notes==
An element or two of this article is reused from [http://en.wikipedia.org/wiki/Translational_research_informatics the Wikipedia article].


==References==
==References==

Latest revision as of 19:38, 24 April 2014

Translational research informatics (TRI) (or translational informatics or TI) is a sister domain to or a sub-domain of biomedical or clinical informatics concerned with the application of informatics theory and methods to translational research. While translational informatics has elements in common with clinical informatics, it's primarily concerned with enabling multi-disciplinary research to accelerate clinical outcomes, with clinical trials often being the natural step beyond translational research.

Translational research informatics can be described in several different ways.

1. "integrated solutions to manage the: (i) logistics, (ii) data integration, and (iii) collaboration, and (iv] knowledge generation required by translational investigators and their supporting institutions." [1]

...or in more lengthy terms:

2. "the informatics subdiscipline that is primarily concerned with the development and application of biomedical informatics theories, methods, and best practices intended to support: 1) the acquisition of knowledge and information from the preceding sources; 2) the representation of such knowledge and information in an actionable format (e.g., readily consumed and analyzed, usually through the use of computational tools and applications), and the subsequent dissemination of that knowledge or information to targeted end-users or analytical platforms; and 3) the semantic integration of disparate data sources to support the discovery and verification/validation of complex bio-marker-to-phenotype relationships that may collectively define a translational biomedical knowledge model."[2]

The field is relatively new, with most Clinical and Translational Science Awards (CTSAs) funding and research going into informatics tools and systems enabling the end-to-end TI requirements.[3]

Systems in translational informatics

The informatics systems involved in translational informatics tend to fall between and often inter-operate with health informatics and electronic medical record systems, clinical trial management systems, and statistical analysis and data mining tools.

System type Description of system
Translational study management Systems to manage investigator-lead biomarker validation studies and observational studies
Electronic patient questionnaires Web-based forms for capturing participant demographic, condition, treatment, and outcome information
Clinical information management Systems to integrate clinical annotations extracted from various source systems, like HL7 electronic medical records, cancer registries, clinical laboratory information systems, and data warehouses
Biorepository management systems Manage biospecimens derived from study participants, operating rooms, etc.
Laboratory information management systems and laboratory information systems Systems to manage clinical, analytical, and life sciences core technology laboratories which often conduct genomics, proteomics, metabolomics, molecular imaging, peptide synthesis, and flow cytometry activities
Systems biology / science data management A database and content management system to archive raw instrument files and database test results and other data
Research collaboration system A software solution to enable investigators and their research teams to share project information, results data, and insights

See also

Bioinformatics

Further reading


External sites

Notes

An element or two of this article is reused from the Wikipedia article.

References