Centre for Translational Research

August 30, 2017 Centre for Translational Research

Vision: Improving population health through application of research

Mission statement: To provide research resources, training, and collaboration
opportunities for IMU staff, health care providers, and the community


  1. To expedite scientific discovery to the clinic for the benefit of patients and communities
  2. To foster better integration of basic science and clinical research at IMU
  3. To promote translation of scientific discovery to practice by fostering innovative research, cultivating multi-disciplinary research partnerships, and ensuring a pipeline of next generation researchers through robust educational and career development programs.


In the current ‘omics’ era, the potential practice of precision medicine is finally on the horizon. The promise of personalized medicine is enticing both to the scientific community and the global population.

What is translational research?
Translational research involves application of knowledge and discovery gained from the basic sciences to clinical and community settings. It entails a continuum from generating and utilising vast information in research laboratories (basic science) to pre-clinical investigations through to its practical application in the clinic (Figure 1). 1-3 The ultimate goal of translational research is to reduce disease incidence, morbidity and mortality, and bring personalized medicine to the population. 2,3 It is a multidisciplinary research that brings together a conglomerate of experts such as physicians, basic scientists, epidemiologists, patent experts and others. Translational research enables new scientific findings to be put to use by health care professionals to the general population. One of the earlier examples of translational research is the use of blood typing to guide blood transfusion. From the discovery that blood transfusion can be carried out in animals by Richard Lower in 1665, to the key discovery on human blood group types by Karl Landsteiner in 1900 which was then translated by Reuben Ottenberg in 1907 who performed the first successful human-to- human blood transfusion at Mount Sinai Hospital in New York. 4,5

Rationale for Centre for Translational Research, IRDI (CTR, IRDI)
Conventionally, scientists have always been trained to think within the confines of their expertise. Such a compartmentalised approach has been a major stumbling block in making translational research a reality. Basic scientists are not trained to think about applying their work in a clinical setting, likewise, clinicians are not taught to think about research ideas related to clinical observations. Even though these two groups have long been collaborating and sharing knowledge, seamless translation of science from bench-to- bedside-and- back is almost nonexistent until recently. The pipeline for translational research thus will include a paradigm shift in the way research will be carried out by both basic scientists and clinicians with the aim of bridging the gap between basic science, clinical research and clinical practice. One of the key phases in translational research (Figure 1) is the translation from basic laboratory discoveries to pre-clinical/clinical studies (Gap 1) where various in vitro to in vivo scale ups and interspecies scaling are required since there are obvious interspecies differences in molecular targets and pathways. Understanding the contrast between using inbred animal models and translating the results into the outbred human population will be key and addressing these shortfalls will be pivotal in making precision medicine a reality. In addition, in vitro molecular observations in the homogenous cellular state will need to be up-scaled towards an intact mammalian system, such as humans, capitalising on high resolution high throughput ‘omics’ platform in an integrated systems biology manner to give a holistic view on the interaction between host and the surrounding environment and social strata (Figure 2). The other key phase in translation research involves translating clinical-trial research on best medical practices into the community. 1,3 It has to be stressed here though that to realise the true potential of translational research in providing the best medical care/treatments for the population, a bidirectional relationship should occur where basic science on pathophysiology of disease and new treatment are being translated into clinical trials and ultimately into public health. Similarly, clinical observations on disease and resultant treatment outcomes must be communicated effectively to basic scientists consequently providing the impetus to initiate disease research. This concept is also known as ‘From bench to bedside and back’.

Figure 1. The continuum of translational research with the key stages as proposed by the National Center for Advancing Translational Research (National Institute of Health, USA; https://ncats.nih.gov/translation/spectrum). T0, where basic/’bench’ research are being carried out to ascertain the underlying mechanisms and pathophysiology of a disease; T1, where the discoveries made in basic science are being tested for their clinical effect and potential application; T2, where new interventions will be tested on human subjects under controlled conditions; T3, where research on the application of the tested new intervention in clinical practice will take place and T4, where the interventions will be applied into the populations and investigation on the factors influencing the health of the population, as a result of the intervention, will take place. Gap 1 and Gap 2 are the major gaps identified that could potentially impact on progress in translational research, where Gap 1 involves translating discovery from basic science to clinical testing and Gap 2 involves establishment of personalized treatment guidelines and policy including consultation with community and potential socio-ethical impact.2,3

Conventional science has failed to live up to the expectation of finding the ‘magic bullet’, a concept introduced by Paul Ehrlich in 1913,6,7 to cure the plight of the human race. Even after the establishment of the human genome, predicting biological outcomes based on genomic data proved challenging due to the complexity of mammalian system in its entirety, with its many spatially heterogeneous arrays of disparate cell types and temporal displacement between gene, protein, metabolic and physiological events and subsequent phenotypic end points. Lederberg was the first to appreciate that human is a supraorganism8,9 consisting of host karyome, chondriome, microbiome, virome and epigenome that interact with the exposome (Figure 2).9-11 The complexity of these interactions both within and surrounding a supraorganism warrant a paradigm shift in the way scientists and clinicians think about drug design and optimised patient treatment/care.10,12 Translational research involves a holistic understanding into human health incorporating global systems biology which attempts to integrate information from the genome, proteome, metabolome, metagenome as well as their interactions with the exposomes (Figure 2). Such complex biological and interactive structures within the host with the environment and population sociodemographic necessitate the use of advanced technology and expert machine learning tools that allow scientists and clinicians to tease out relevant information that are easily interpreted and improve patient point of care. This eventually gives rise to precision medicine, which is an approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person. While some advances in precision medicine have been made, the practice is not currently in use for most diseases. Hence translational research plays an important role in making precision medicine a reality and not just a blip in the horizon.

Figure 2. Complexity of modelling mammalian biology and the potential research areas that can be carried out to address and dissect such complexity.

IRDI Centre for Translational Research
The objective of CTR, IRDI is to be the catalyst to instigate paradigm shift in the way basic scientists and clinicians conduct their research and patient care respectively so that T1 translation will be included automatically in their day-to-day research activities with the ultimate goal that future scientists and clinicians will always keep in mind the purpose of translational research that is, to improve our health through research and its application. In addition, the CTR will also facilitate the application of research findings to the community (T3 translation) through policy and guideline research as well as effective dissemination of scientific discoveries to the lay public. Further, the CTR will assist in the attainment of relevant experts in the field of systems biology, clinical and molecular research, clinical practice policy and guidelines. The CTR will do this through a multipronged approach (Figure 3) tapping into IMU undergraduate student semester research as seed funding to start pilot translational research projects and at the same time facilitate IMU staff in competitive research grant application. Apart from providing assistance with proposal development, the CTR will assist in study design, regulatory issues and submissions, biostatistics and informatics incorporating stochastic and probabilistic (fuzzy) modelling for large-scale data analysis, and offer ethics consultation, ‘omics’ technologies (outsource), biorepository services, facilitation with an affiliated laboratory network, and training for students and early career investigators. We envisage that with such a strategy in place, the CTR will be able to provide the impetus to advance scientific discovery to improve health thus bringing discoveries from the lab to the bedside and back.

Figure 3. The CTR strategy to initiate, promote and support translational research. Current State or Translational Research at IMU

Areas of focus:

  1. Population-wide association studies focusing on communicable and non-communicable disease co-morbidities on population phenome.
  2. Functional metagenomics incorporating functional redundancy theory in human population.
  3. Bioinformatics and network modelling to create robust integrative health systems model to understand and predict the relationship between lifestyle and indicators of health status on population phenotype.

Centre for Translational Research Working Group


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  2. Khoury, M. J. et al. The continuum of translation research in genomic medicine:how can we accelerate the appropriate integration of human genome discoveries into health care and disease prevention? Genetics in medicine : official journal of the American College of Medical Genetics 9, 665-674, doi:10.1097GIM.0b013e31815699d0 (2007).
  3. Ozdemir, V., Williams-Jones, B., Cooper, D. M., Someya, T. & Godard, B. Mapping translational research in personalized therapeutics: from molecular markers to health policy. Pharmacogenomics 8, 177-185, doi:10.2217/14622416.8.2.177 (2007).
  4. Fastag, E., Varon, J. & Sternbach, G. Richard Lower: the origins of blood transfusion. The Journal of emergency medicine 44, 1146-1150, doi:10.1016/j.jemermed.2012.12.015 (2013).
  5. Sobol, R. E. & Scanlon, K. J. The journal of cancer gene and cellular therapies.
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  6. Ehrlich, P. Address in Pathology, ON CHEMIOTHERAPY: Delivered before the Seventeenth International Congress of Medicine. British Medical Journal 2, 353-359 (1913).
  7. Gelpi, A., Gilbertson, A. & Tucker, J. D. Magic bullet: Paul Ehrlich, Salvarsan and the birth of venereology. Sexually Transmitted Infections 91, 68-69, doi:10.1136/sextrans-2014- 051779 (2015).
  8. Glendinning, L. & Free, A. Supra-organismal interactions in the human intestine. Frontiers in Cellular and Infection Microbiology 4, 47, doi:10.3389/fcimb.2014.00047 (2014).
  9. Lederberg, J. Infectious history. Science 288, 287-293 (2000).
  10. Faber, J. H. et al. Metabonomics in Diabetes Research. Journal of Diabetes Science and Technology (Online) 1, 549-557 (2007).
  11. Wild, C. P. Complementing the genome with an "exposome": the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 14, 1847-1850, doi:10.1158/1055-9965.EPI- 05-0456 (2005).
  12. Dumas, M.-E. et al. Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proceedings of the National Academy of Sciences of the United States of America 103, 12511-12516, doi:10.1073/pnas.0601056103 (2006).