Translational research
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The concept of translational research [1] has received very strong focus in the biomedical community over the last few years, as a new way of thinking about and conducting life sciences research to accelerate healthcare outcomes. Global Pharmaceutical companies and the NIH [2] have been pouring billions of dollars into life sciences basic research and are realizing the return on investment is not living up to expectations, and Translational Research is often seen as the key missing component. The NIH, through its Clinical and Translational Science Awards [3], is funding major infrastructure and support for Translational Research in the United States.
With its focus on removing barriers to multi-disciplinary collaboration, translational research has the potential to drive the advancement of molecular-based medicine. By enabling physicians and pharmacologists to leverage systems biology technologies, translational research can enable early detection of cancer and other diseases, increase efficiency in drug development, improve drug efficacy and enable personalized medicine.
The possibilities of using biomarkers to predict, detect, and monitor disease make personalized medicine tangible. Only when clinicians, researchers and the various operational staff can work together effectively, will the movement of scientific discoveries accelerate into the clinic and clinical findings more rapidly fuel research directions.
To fully realize this vision, translational research requires researchers and clinicians to have ready access to two critical types of information - (1) clinical information, including data contained in hospital systems and medical records, pathology reports and diagnostic labs, clinical trials systems and study participant questionnaires; and (2) biomolecular information, including genomics, proteomics, medical imaging and other high-throughput molecular and cellular research data.
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[edit] 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 translational medicine but has more general applicability as a distinct research approach.
The traditional categorization of research identifes 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-frame, but would often represent an incremental improvement to current processes rather than delivering radical breakthroughs.
Universities are traditionally associated with basic research while polytechnics and technology institutes are typically associated with applied research. This separation is more than just cultural, as the physical separation across these different institutions makes it difficult to establish the multidisciplinary and multi-skilled teams that are necessary to be successful in translational research. This represents just one of the particular challenges in conducting translational research successfully. 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].
An attempt to bridge these research activities 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.
This mode of research can be applied more generally outside the medical domain 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.
[edit] 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 disease be revealed, and effective prevention, early detection and personalized treatments be realized.
Furthermore, the scale, scope and multi-disciplinary approach that translational research dictates means a new level of operations management capabilities within and across studies, biorepositories 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 biomolecular data. Most informatics systems in use today are inadequate in terms of handling the tasks of complicated operations and contextually indata management and analysis.
Translational research requires that information and data flow from hospitals, clinics and participants of studies in an organized and structured format to biorepositories and research-based facilities and laboratories. The sheer volume of data, combined with the need to share data across domains, demands an integrated and holistic approach to IT systems for informatics.
[edit] Definitions of translational research
Translational research is a new and rapidly evolving domain. As such, the definition is bound to evolve over time.
Websites that help to define translational research:
[edit] See also
Personalized medicine
Medical genetics
Human genetics
Biomedical research
Systems biology
Translational Research Informatics
Clinical trials
[edit] Related web sites
NIH Roadmap
CTSA Awards
Center for Translational Injury Research
[edit] References
- ^ Feldman, A. Does Academic Culture Support Translational Research? CTS: Clinical and Translational Science 2008;volume 1, issue 2;87-88
- Woolf, SH. The Meaning of Translational Research and Why It Matters. JAMA 2008;299;211-213.
- Sanchez-Serrano, I. Success in Translational Research: lessons from the development of bortezomib. Nature Reviews Drug Discovery 5, 107-114 (February 2006) http://www.nature.com/nrd/journal/v5/n2/abs/nrd1959.html
