International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

Application of translational bioinformatics in drug interaction research

Author Affiliations

  • 1Department of Biochemistry, University of Nigeria, Nsukka, Nigeria
  • 2Department of Biochemistry, University of Nigeria, Nsukka, Nigeria
  • 3Department of Biochemistry, University of Nigeria, Nsukka, Nigeria
  • 4Department of Biochemistry, University of Nigeria, Nsukka, Nigeria
  • 5Department of Biochemistry, University of Nigeria, Nsukka, Nigeria
  • 6Department of Biochemistry, University of Nigeria, Nsukka, Nigeria

Res. J. of Pharmaceutical Sci., Volume 7, Issue (2), Pages 1-5, December,30 (2018)


The application of translational approaches is gaining ground in the drug industry. The utility of the fast appreciation in data volume at all phases of processes involving the discovery of drugs, translational bioinformatics is geared towards addressing some of the key challenges encountered by the industry. Analyzing clinical data an records of patients through computational methods has Indeed influenced the decision-making in many aspects of drug discovery and development, which automatically leads to more effective treatments. Translational bioinformatics research alludes to the multidirectional mix of essential research, understanding focused research, and populace based research with the long haul point of enhancing the health of the general population. In different terms, bioinformatics is the utilization of PC innovation to the administration of biological data, used to assemble, store, dissect and incorporate biological information. This would then be able to be connected to tranquilize disclosure and advancement. Translational bioinformatics is a rising field that spotlights on the application of informatics philosophy to the expanding measure of biomedical and genomic information with a specific end goal to produce learning for clinical applications. For instance, examiners have been occupied with finding noteworthy transformations that can be utilized for the improvement of accuracy solution techniques from a large number of genetic changes or much more in an individual genome. Notwithstanding the difficulties above, there are different points that require quick consideration, for example, information sharing, effective clinical choice and emotional support network and outline, and advancement in the development of particular genes board for quick screening of patients. The interaction of drugs refers to the adjustment of reaction of one medication by another when they are administered with hardly a pause in between. Despite the fact that a moderately new technology, translational bioinformatics (TB) has turned into a major segment of biomedical research in the time of accuracy pharmaceuticals. Advancement of high-throughput advances and electronic health records has caused a change in outlook in both medicinal services and research pertaining to biomedicine. These Novel translational bioinformatics apparatus strategies are required to change over progressively voluminous datasets into significant information.


  1. McGrath J., Arar N. and Pugh J. (2007)., The influence of electronic medical record usage on nonverbal communication in the medical interview., Health Informatics J, 13, 105-118.
  2. Buetow S. and Elwyn G. (2008)., The window mirror: A new model of the patient-physician relationship., Open Med, 2(1), 20-25.
  3. Markou A., Chiamulera C. and Steckler T. (2009)., Removing obstacles in neuroscience drug discovery: the future path for animal models., Neuropsychopharmacology, 34, 74-89.
  4. Husserl E. (1970)., The crisis of European sciences and transcendental phenomenology: An introduction to phenomenological philosophy., Evanston: Northwestern University Press, 3-9.
  5. Edsall R. (2000)., Is the doctor-patient relationship finally growing up?., FamPractManag, 7, 12-13.
  6. Buchan N.S., Rajpal D.K., Webster Y., Alatorre C., Gudivada R.C., Zheng C., Sanseau P. and Koehler J. (2011)., Role of translational bioinformatics in drug discovery., Drug Discovery Today, 16(9), 426-434.
  7. Lussier Y.A., Butte A.J. and Hunter L. (2010)., Current methodologies for translational bioinformatics., Journal of Biomedical Informatics, 43, 355-357.
  8. Trujillo E., Davis C. and Milner J. (2006)., Nutrigenomics, proteomics, metabolomics, and the practice of dietetics., J Am Diet Assoc, 106, 403-413.
  9. Rubio D.M., Schoenbaum E.E., Lee L.S., Schteingant D.E., Marantz P.R., Anderson K.E., Dewey L., Baez A. and Esposito K. (2010)., Defining translational research: Implications for training., Academic Medicine, 85(3), 470-475.
  10. Tenenbaum J.D. (2016)., Translational bioinformatics: past, present, and future., Genomics, Proteomics and Bioinformatics, 14(1), 31-41.
  11. Feng X., Liu X., Luo Q. and Liu B.F (2008)., Mass spectrometry in systems biology: an overview., Mass Spectrom Rev., 27, 635-660.
  12. Agostino M. (2012)., Practical Informatics., First Edition. Garland Science, New York. 1-5.
  13. Lesk A.M. (2013)., Bioinformatics., Encyclopaedia Britannica. Retrieved 17 April 2017.
  14. Kmiecik S., Gront D., Kolinski M., Wieteska L., Dawid A. E. and Kolinski A. (2016)., Coarse-Grained Protein Models and their Applications., Chemical Reviews. 116:7898-936. doi:10.1021/acs.chemrev.6b00163.PMID 27333362.
  15. Lu Y., Shen D., Pietsch M., Nagar C., Fadli Z., Huang H., Tu Y. and Cheng F. (2015)., A novel algorithm for analyzing drug-drug interactions from Medline literature., Scientific Reports, 5, 17357-17360.
  16. Tenenbaum J.D. (2016)., Translational bioinformatics: past, present, and future., Genomics, Proteomics and Bioinformatics, 14(1), 31-41.
  17. Lesko L.J. (2012)., Drug research and translational bioinformatics., Clinical Pharmacology & Therapeutics. 91(6), 960-962. doi:10.1038/clpt.2012.45.
  18. Butte A.J. (2008)., Translational bioinformatics: coming of age., Journal of the American Medical Informatics Association, 15, 709-712.
  19. Silva L.R.F. (2008)., From old age to third age: the historical course of the identities linked to the process of ageing., HistCiencSaude-Manguinhos, 15(1), 155-68. 100009
  20. Saxena A.K., Singh D. and Singh G. (2009)., Structural interaction between drug - DNA and protein - A novel approach for bioinformatics in medicine., Biomedical Research, 20(1), 28-34.
  21. Troen B.R. (2003)., The biology of aging., Mt Sinai J Med. 70:3-22. Disponívelem: https://d2cauhfh6h4x0p.cloudfront.
  22. Kho R., Kim S., Lee S. and Tsu L.V. (2014)., A review of common drug-drug and food-drug interactions associated with cardiovascular medications., Arizona Journal of Pharmacy, 2, 36-43.
  23. Gurwitz J.H., Field T.S, Harrold L.R., Rothschild J., Debellis K. and Seger A.C. (2003)., Incidence and preventability of adverse drug events among older persons in the ambulatory setting., JAMA, 289(9), 1107-16.
  24. Vonbach P., Dubied A., Krähenbühl S. and Beer J.H. (2007)., Prevalence of drug-drug interactions at hospital entry and during stay of patients in internal medicine., Eur J Intern Med., 19(6), 413-20. doi: 10.1016/j.ejim. 2007.12.002.
  25. Alomar M.J. (2014)., Factors affecting the development of adverse drug reactions (Review article)., Saudi Pharm J. 22(2), 83-94. doi: 10.1016/j.jsps.2013.02.003.
  26. Mutalik M. and Sanghavi D. (2014)., Review of drug interactions: a comprehensive update., British Journal of Pharmaceutical Research, 4(8), 954-980.
  27. Hajjar E.R., Cafiero A.C. and Hanlon J.T. (2007)., Polypharmacy in elderly patients., Am J Geriatr Pharmacother. 5(4):345-51. doi: 10.1016/j.amjopharm. 2007.12.002.
  28. Fulton M.M. and Allen E.R. (2005)., Polypharmacy in the elderly: a literature review., J Am Acad Nurse Pract.. 17(4), 123-32. doi: 10.111/j.1041-2972.2005.0020.x
  29. Nidhi S. (2012)., Concept of drug interaction., International Research Journal of Pharmacy, 3(7), 120-123.
  30. Vonbach P., Dubied A., Krähenbühl S. and Beer J.H. (2007)., Prevalence of drug-drug interactions at hospital entry and during stay of patients in internal medicine., Eur J Intern Med., 19(6), 413-20. doi: 10.1016/j.ejim. 2007.12.002.
  31. Zhang M., Holman C.D.J., Price S.D., Sanfilippo F.M., Preen D.B. and Bulsara M.K. (2009)., Comorbidity and repeat admission to hospital for adverse drug reactions in older adults: retrospective cohort study., British Medical Journal. 2009 338:a2752. doi: http://dx.doi. org/10.1136/ bmj.a2752.
  32. Mendonca E.A. (2010)., Selected proceedings of the 2010 summit on translational bioinformatics., BMC Bioinformatics, 11(9), 1-4. doi:10.1186/1471-2105-11-S9-S1. PMC 2967739. PMID 2104435.
  33. Readhead B. and Dudley J. (2013)., Translational bioinformatics approaches to drug development., Advances in Wound Care, 2(9), 470-490.
  34. Kann M.G. (2010)., Advances in translational bioinformatics: Computational approaches for the hunting of disease genes., Briefings in Bioinformatics, 11(1), 96-110. doi:10.1093/bib/bbp048. PMC 2810112. PMID 20007728
  35. Duke J.D., Han X., Wang Z., Subhadarshini A., Karnik S.D., Li X., Hall S.D., Jin Y., Callaghan J.T., Overhage M.J., Flockhart D.A., Strother M.R., Quinney S.K. and Li L. (2012)., Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions., Computational Biology, 8(8), 1-13.
  36. Day M., Rutkowski J.L. and Feuerstein G.Z. (2009)., Translational medicine-a paradigm shift in modern drug discovery and development: the role of biomarkers., Advances in Experimental Medicine and Biology, 655, 1-12.
  37. Edwards D.J. (2012)., Beneficial pharmacokinetic drug interactions., Advances in Pharmacoepidemiology and Drug Safety. 1, 002-007.
  38. Dudley J.T. (2014)., Translational bioinformatics in the cloud: An affordable alternative., Genome Medicine, 2(8), 51. doi:10.1186/gm172.
  39. Wetterstrand K.A. (2012)., DNA sequencing costs: Data from the NHGRI Genome sequencing program (GSP)., Retrieved November 3, 2012.
  40. Du L., Chakraborty A., Chiang C.W., Cheng L., Quinney S.K., Wu H., Zhang P., Li L. and Shen L. (2015)., Graphic mining of high-order drug interactions and their directional effects on myopathy using electronic medical records., CPT Pharmacometrics and System Pharmacology, 4, 481-488.
  41. Azuaje F.J., Heymann M., Ternes A., Wienecke-Baldacchino A., Struck D., Moes D. and Schneider R. (2012)., Bioinformatics as a driver, not a passenger, of translational biomedical research: Perspectives from the 6th Benelux bioinformatics conference., Journal of Clinical Bioinformatics, 2(7), 1-3.
  42. Butte A.J. (2008)., Translational bioinformatics: coming of age., Journal of the American Medical Informatics Association, 15, 709-712.
  43. Embi P.J. and Payne P.R. (2013)., Evidence generating medicine: redefining the research-practice relationship to complete the evidence cycle., Med Care, 51, 87-S91.
  44. Ouzounis C.A. (2012)., Rise and demise of bioinformatics? Promise and progress., PLOS Computational Biology, 8(4), 1-5.doi:10.1371/journal.pcbi.1002487. PMC 3343106. PMID 22570600
  45. Luce B.R., Kramer J.M., Goodman S.N., Connor J.T., Tunis S., Whicher D. (2009)., Rethinking randomized clinical trials for comparative effectiveness research: the need for transformational change., Ann Intern Med. 151, 206-209.
  46. Botsis T., Hartvigsen G., Chen F. and Weng C. (2010)., Secondary use of EHR: data quality issues and informatics opportunities., AMIA Jt Summits TranslSci Proc., 1-5.
  47. Yan Q. (2010)., Translational bioinformatics and systems biology approaches for personalized medicine (PDF)., Methods in Molecular Biology, 662, 167-178.