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Translational research is scientific research that helps to make findings from basic science useful for practical applications that enhance human health and well-being. It is practiced in fields such as environmental and agricultural science, as well as the health, behavioral, and social sciences. For example, in medicine and nursing it is used to "translate" findings in basic research quickly into medical and nursing practice and meaningful health outcomes. Applying knowledge from basic science is a major stumbling block in science, partially due to the compartmentalization within science. Hence, translational research is seen as a key component to finding practical applications, especially within healthcare. Translational research is another term for translative research and translational science, although it fails to disambiguate itself from research that is not scientific (e.g., market research), which are considered outside its scope.
With its focus on multi-disciplinary collaboration, translational research has the potential to advance applied science. This has been attempted particularly in medicine with translational medicine, research that aims to move “from bench to bedside” or from laboratory experiments through clinical trials to point-of-care patient applications.
Translational research is a paradigm for research alternative to the dichotomy of basic research and applied research. It is often applied in the domain of healthcare but has more general applicability as a distinct research approach. It is also allied in practice with the approaches of participative science and participatory action research.
The traditional categorization of research identifies just two categories: basic research (also labelled fundamental or pure research) and applied research. Basic research is more speculative and takes a long time – often decades – to be applied in any practical context. Basic research often leads to breakthroughs or paradigm-shifts in practice. On the other hand, applied research is research that can have an impact in practice in a relatively short time, but often represents an incremental improvement to current processes rather than delivering radical breakthroughs.
The cultural separation between different scientific fields makes it difficult to establish the multidisciplinary and multi-skilled teams that are necessary to be successful in translational research. Other challenges arise in the traditional incentives which reward individual principal investigators over the types of multi-disciplinary teams that are necessary for translational research. Also, journal publication norms often require tight control of experimental conditions, and these are difficult to achieve in real-world contexts.
In medicine, translational research is increasingly a separate research field. A citation pattern between the applied and basic sides in cancer research appeared around 2000. Since 2009, the field has also a specialized journal, the American Journal of Translational Research.
In nursing, the need for translational research was a primary driver for the development of the Doctor of Nursing Practice degree.
Outside medicine, translational research can be applied more generally, as in science-to-business marketing or other initiatives where researchers try to shorten the time-frame and conflate the basic-applied continuum, to ‘translate’ fundamental research results into practical applications. It is necessarily a much more iterative style of research, with low and permeable barriers and much interaction between academic research and industry practice. Practitioners help shape the research agenda by supplying difficult problems to which applied research would only offer incremental improvements.
"The first problem is that history is not really on the side of translational research. Most inventions and practical applications of science and technology which we take for granted have come not from people sitting in a room trying to invent new things but as fortuitous offshoots of curiosity-driven research." Is the outcome of funding translational research better than funding research itself?
To flourish, translational research requires a knowledge-driven ecosystem, in which constituents generate, contribute, manage and analyze data available from all parts of the landscape. The goal is a continuous feedback loop to accelerate the translation of data into knowledge. Collaboration, data sharing, data integration and standards are very important. Only by seamlessly structuring and integrating these data types will the complex and underlying causes and outcomes of illness be revealed, and effective prevention, early detection and personalized treatments be realized.
Translational research requires that information and data flow from hospitals, clinics and study participants in an organized and structured format, to repositories and laboratories. Also, the scale, scope and multi-disciplinary approach that translational research requires means a new level of operations management capabilities within and across studies, repositories and laboratories. Meeting the increased operational requirements of larger studies, with ever increasing specimen counts, larger and more complex systems biology data sets, and government regulations, requires informatics that enables the integration of both operational capabilities and clinical and basic data. Most informatics systems today are inadequate to handle the tasks of complicated operations and contextually in data management and analysis.
Translational research refers to two distinct domains: T1 research, the “bench-to-bedside” enterprise of translating knowledge from the basic sciences into the development of new treatments; and T2 research, translating the findings from clinical trials into everyday practice.
Websites that help to define translational research: