Translational research is another term for traslative research and translational science, although it fails to disambiguate itself from forms of research that are not scientific (e.g., market research), which are currently considered outside its scope. Translational research is a way of thinking about and conducting scientific research to make the results of research applicable to the population under study and is practised in the natural and biological, behavioural, and social sciences. In the field of medicine, for example, it is used to translate the findings in basic research more quickly and efficiently into medical practice and, thus, meaningful health outcomes, whether those are physical, mental, or social outcomes. In medicine in particular, governmental funders of research and pharmaceutical companies have spent vast amounts internationally on basic research and have seen that the return on investment is significantly less than anticipated. Translational research has come to be seen as the key, missing component.
With its focus on removing barriers to multi-disciplinary collaboration, translational research has the potential to drive the advancement of applied science. An attempt to bridge these barriers has been undertaken particularly in the medical domain where the term translational medicine has been applied to a research approach that seeks to move “from bench to bedside” or from laboratory experiments through clinical trials to actual point-of-care patient applications. However, it should be noted that the term translational medicine is a misnomer, as medicine is not a science: it is the clinical practice of healing the given individual whereas science addresses principles and populations. This distinction is the primary reason that science needs to be translated at all. "Translational medicine" would best be termed "Translational medical science".
Comparison to basic research or applied research
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 medicine 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 measured in decades – to be applied in any practical context. Basic research often leads to breakthroughs or paradigm-shifts in practice. Applied research on the other hand is characterised as being capable of having an impact in practice within a relatively short time, but would often represent 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 [1].
Outside of the medical domain, this mode of research can be applied more generally where researchers seek to shorten the time-frame and conflate the basic-applied continuum to ‘translate’ fundamental research results into practical applications. It is of necessity a much more iterative style of research with low and permeable barriers and a great deal of interaction between academic research and industry practice. Practitioners help shape the research agenda in supplying what may be intractable problems to which applied research approaches will only offer incremental improvements.
Challenges in translational research
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 integral. 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 participants of studies in an organized and structured format to repositories and research-based facilities and laboratories. Furthermore, 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, precipitates an informatics approach that enables the integration of both operational capabilities and clinical and basic data. Most informatics systems in use today are inadequate in terms of handling the tasks of complicated operations and contextually in data management and analysis.
Definitions of translational research
Translational research is a new and rapidly evolving domain. As such, the definition is bound to evolve over time. Generally speaking, the primary goal of “translational” research is to integrate advancements in molecular biology with clinical trials, taking research from the “bench-to-bedside”. [2][3]
Websites that help to define translational research:
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