Translational research informatics

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."

...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."

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.

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

• Cantor, Michael N. (January 2012). "Translational informatics: an industry perspective". Journal of the American Medical Informatics Association (19): 153–155. doi:10.1136/amiajnl-2011-000588. http://jamia.bmj.com/content/19/2/153.full. 

• Payne, Philip R. O.; Embi, Peter J.; Sen, Chandan K. (November 2009). "Translational informatics: enabling high-throughput research paradigms". Physiological Genomics 39 (3): 131–140. doi:10.​1152/​physiolgenomics.​00050.​2009. http://physiolgenomics.physiology.org/content/39/3/131.full. 

External sites

• Clinical and Translational Science Awards
  
• American Medical Informatics Association (AMIA)