Metabonomics pp 195-207 | Cite as

Metabonomics and Drug Development

  • Pranov Ramana
  • Erwin Adams
  • Patrick Augustijns
  • Ann Van Schepdael
Part of the Methods in Molecular Biology book series (MIMB, volume 1277)


Metabolites as an end product of metabolism possess a wealth of information about altered metabolic control and homeostasis that is dependent on numerous variables including age, sex, and environment. Studying significant changes in the metabolite patterns has been recognized as a tool to understand crucial aspects in drug development like drug efficacy and toxicity. The inclusion of metabonomics into the OMICS study platform brings us closer to define the phenotype and allows us to look at alternatives to improve the diagnosis of diseases. Advancements in the analytical strategies and statistical tools used to study metabonomics allow us to prevent drug failures at early stages of drug development and reduce financial losses during expensive phase II and III clinical trials. This chapter introduces metabonomics along with the instruments used in the study; in addition relevant examples of the usage of metabonomics in the drug development process are discussed along with an emphasis on future directions and the challenges it faces.

Key words

Metabonomics Metabolomics Metabolic profiling Drug development 



The authors gratefully acknowledge the support of the ARIADME (Analytical Research in ADME profiling) project sponsored by FP7 Marie Skłodowska Curie grant under Grant Agreement No 607517.


  1. 1.
    Nicholson JK, Lindon JC, Holmes E et al (1999) Metabonomics: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29:1181–1189CrossRefPubMedGoogle Scholar
  2. 2.
    Tsui LC, Dorfman R et al (2013) The cystic fibrosis gene: a molecular genetic perspective. Cold Spring Harb Perspect Med 3:a009472. doi: 10.1101/cshperspect.a009472 CrossRefPubMedCentralPubMedGoogle Scholar
  3. 3.
    Craig J (2008) Complex diseases: research and applications. Nat Edu 1(1):184Google Scholar
  4. 4.
    Chen L, Wu J (2012) Systems biology for complex diseases. J Mol Cell Biol 4:125–126CrossRefPubMedGoogle Scholar
  5. 5.
    Nicholson JK, Wilson ID (2003) Opinion: understanding ‘global’ systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discov 2(8):668–676CrossRefPubMedGoogle Scholar
  6. 6.
    Wishart DS (2008) Applications of metabolomics in drug discovery and development. Drugs R D 9:307–322CrossRefPubMedGoogle Scholar
  7. 7.
    Fiehn O (2001) Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp Funct Genomics 2(3):155–168CrossRefPubMedCentralPubMedGoogle Scholar
  8. 8.
    Dunn WB, Broadhurst D, Griffin JL et al (2011) Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chem Soc Rev 40:387–426CrossRefPubMedGoogle Scholar
  9. 9.
    Smolinska A, Blanchet L, Buydens LM, Wijmenga SS (2012) NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery—a review. Anal Chim Acta 750:82–97CrossRefPubMedGoogle Scholar
  10. 10.
    Ma S, Chowdhury SK (2013) Data acquisition and data mining techniques for metabolite identification using LC coupled to high-resolution MS. Bioanalysis 5:1285–1297CrossRefPubMedGoogle Scholar
  11. 11.
    Doring G, Lackner H (1970) NMR spectroscopy identification of barbiturates. II. studies on biological material. Arch Toxikol 26:237–250CrossRefPubMedGoogle Scholar
  12. 12.
    Nicholson JK, Connelly J, Lindon JC, Holmes E (2002) Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 1:153–161CrossRefPubMedGoogle Scholar
  13. 13.
    Keun HC, Beckonert O, Griffin JL et al (2002) Cryogenic Probe 13C NMR spectroscopy of urine for metabonomic studies. Anal Chem 74(17):4588–4593CrossRefPubMedGoogle Scholar
  14. 14.
    Olsson LE, Chai CM, Axelsson O et al (2006) Magnetic resonance coronary angiography in pigs with intraarterial injections of a hyperpolarized 13C substance. Magn Reson Med 55:731–737CrossRefPubMedGoogle Scholar
  15. 15.
    Dettmer K, Aronov PA, Hammock BD et al (2007) Mass spectrometry-based metabolomics. Mass Spectrom Rev 26:51–78CrossRefPubMedCentralPubMedGoogle Scholar
  16. 16.
    Wilson ID, Nicholson JK, Plumb JRS et al (2005) High resolution “ultra performance” liquid chromatography coupled to OA-TOF mass spectrometry as a tool for differential metabolic pathway profiling in functional genomic studies. J Proteome Res 4:591–598CrossRefPubMedGoogle Scholar
  17. 17.
    Muller DC, Degen C, Scherer G et al (2014) Metabolomics using GC-TOF-MS followed by subsequent GC-Fid and HILIC-MS/MS analysis revealed significantly altered fatty acid and phospholipid species profiles in plasma of smokers. J Chromatogr B Analyt Technol Biomed Life Sci 966:117–126. doi: 10.1016/j.jchromb.2014.02.044 CrossRefPubMedGoogle Scholar
  18. 18.
    Cretich M, Chiari M, Pirri G, Crippa A et al (2005) Electroosmotic flow suppression in capillary electrophoresis: chemisorption of trimethoxy silane-modified polydimethylacrylamide. Electrophoresis 26:1913–1919CrossRefPubMedGoogle Scholar
  19. 19.
    Soga T, Sugimoto M, Honma M et al (2011) Serum metabolomics reveals gamma-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease. J Hepatol 55:896–905CrossRefPubMedGoogle Scholar
  20. 20.
    Wishart DS, Jewison T, Guo AC, Wilson M, Knox C et al (2013) HMDB 3.0: the human metabolome database in 2013. Nucleic Acids Res 1:D801–D807CrossRefGoogle Scholar
  21. 21.
    Haug K, Reza M, Steinbeck C et al (2013) Metabolights: an open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res 41:D781–D786CrossRefPubMedCentralPubMedGoogle Scholar
  22. 22.
    Schellenberger J, Park JO, Conrad TM, Palsson BO (2010) Bigg: a biochemical genetic and genomic knowledgebase of large scale metabolic reconstructions. BMC Bioinformatics 11:213CrossRefPubMedCentralPubMedGoogle Scholar
  23. 23.
    Croft D, Mundo AF, D’Eustachio P et al (2014) The reactome pathway knowledgebase. Nucleic Acids Res 42:D472–D477CrossRefPubMedCentralPubMedGoogle Scholar
  24. 24.
    Madsen R, Lundstedt T, Trygg J (2010) Chemometrics in metabolomics: a review in human disease diagnosis. Anal Chim Acta 659:23–33CrossRefPubMedGoogle Scholar
  25. 25.
    Roberts LD, Koulman A, Griffin JL (2014) Towards metabolic biomarkers of insulin resistance and type 2 diabetes: progress from the metabolome. Lancet Diabetes Endocrinol 2:65–75CrossRefPubMedGoogle Scholar
  26. 26.
    Zhao YY, Lin RC (2014) UPLC-MS(E) application in disease biomarker discovery: the discoveries in proteomics to metabolomics. Chem Biol Interact 215:7–16CrossRefPubMedGoogle Scholar
  27. 27.
    Roberts LD, Gerszten RE (2013) Toward new biomarkers of cardiometabolic diseases. Cell Metab 18:43–50CrossRefPubMedCentralPubMedGoogle Scholar
  28. 28.
    Valdes AM, Glass D, Spector TD (2013) OMICS technologies and the study of human ageing. Nat Rev Genet 14:601–607PubMedGoogle Scholar
  29. 29.
    Mannello F, Ligi D (2013) Resolving breast cancer heterogeneity by searching reliable protein cancer biomarkers in the breast fluid secretome. BMC Cancer 13:344CrossRefPubMedCentralPubMedGoogle Scholar
  30. 30.
    Ikeda A, Nishiumi S, Shinohara M et al (2012) Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer. Biomed Chromatogr 26:548–558CrossRefPubMedGoogle Scholar
  31. 31.
    Ritchie SA, Akita H, Takemasa IH et al (2013) Metabolic system alterations in pancreatic cancer patient serum: potential for early detection. BMC Cancer 13:416CrossRefPubMedCentralPubMedGoogle Scholar
  32. 32.
    Yang J, Chen T, Sun L et al (2013) Potential metabolite markers of schizophrenia. Mol Psychiatry 18:67–78CrossRefPubMedCentralPubMedGoogle Scholar
  33. 33.
    Tabak AG, Jokela M, Akbaraly TN et al (2009) Trajectories of glycaemia, insulin sensitivity, and insulin secretion before diagnosis of type 2 diabetes: an analysis from the Whitehall II study. Lancet 373:2215–2221CrossRefPubMedCentralPubMedGoogle Scholar
  34. 34.
    Wang TJ, Larson MG, Gerszten RE et al (2011) Metabolite profiles and the risk of developing diabetes. Nat Med 17:448–453CrossRefPubMedCentralPubMedGoogle Scholar
  35. 35.
    Chatterjee S, Richert L, Augustijns P, Annaert P (2014) Hepatocyte-based in vitro model for assessment of drug-induced cholestasis. Toxicol Appl Pharmacol 274:124–136CrossRefPubMedGoogle Scholar
  36. 36.
    Dambach DM, Andrews BA, Moulin F (2005) New technologies and screening strategies for hepatotoxicity: use of in vitro models. Toxicol Pathol 33:17–26CrossRefPubMedGoogle Scholar
  37. 37.
    Bjornsson ES, Bergmann OM, Olafsson S et al (2013) Incidence, presentation, and outcomes in patients with drug-induced liver injury in the general population of Iceland. Gastroenterology 144:1419–1425CrossRefPubMedGoogle Scholar
  38. 38.
    Rangnekar AS, Fontana RJ (2011) An update on drug induced liver injury. Minerva Gastroenterol Dietol 57:213–229PubMedGoogle Scholar
  39. 39.
    Kim JW, Ryu SH, Kim KB et al (2013) Pattern recognition analysis for hepatotoxicity induced by acetaminophen using plasma and urinary 1H NMR-based metabolomics in humans. Anal Chem 85:11326–11334CrossRefPubMedGoogle Scholar
  40. 40.
    Pannu N, Nadim MK (2008) An overview of drug-induced acute kidney injury. Crit Care Med 36:216–223CrossRefGoogle Scholar
  41. 41.
    Uehara T, Horinouchi A et al (2013) Identification of metabolomic biomarkers for drug-induced acute kidney injury in rats. J Appl Toxicol 34:1087–1095. doi: 10.1001/jat.2933 CrossRefPubMedGoogle Scholar
  42. 42.
    Falconi A, Lopes G, Parker JL et al (2014) Biomarkers and receptor targeted therapies reduce clinical trial risk in non-small cell lung cancer. J Thorac Oncol 9:163–169CrossRefPubMedGoogle Scholar
  43. 43.
    Hudler P, Kocevar N, Komel R et al (2014) Proteomic approaches in biomarker discovery: new perspectives in cancer diagnostics. Scientific World Journal 2014:260348. doi: 10.1155/20014/260348 CrossRefPubMedCentralPubMedGoogle Scholar
  44. 44.
    Serkova NJ, Spratlin JL, Eckhardt SG (2007) NMR-based metabolomics: translational application and treatment of cancer. Curr Opin Mol Ther 9:572–585PubMedGoogle Scholar
  45. 45.
    Van der Greef J, Hankemeier T, McBurney RN et al (2006) Metabolomics-based systems biology and personalized medicine: moving towards N = 1 clinical trials? Pharmacogenomics 7:1087–1094CrossRefPubMedGoogle Scholar
  46. 46.
    Johnson CH, Gonzalez FJ et al (2012) Challenges and opportunities of metabolomics. J Cell Physiol 227:2975–2981CrossRefPubMedGoogle Scholar
  47. 47.
    Bino RJ, Hall RD, Fiehn O et al (2004) Potential of metabolomics as a functional genomics tool. Trends Plant Sci 9:418–425CrossRefPubMedGoogle Scholar
  48. 48.
    Fernie AR, Trethewey RN, Willmitzer L et al (2004) Metabolite profiling: from diagnostics to systems biology. Nat Rev Mol Cell Biol 5:763–769CrossRefPubMedGoogle Scholar
  49. 49.
    Fiehn O (2002) Metabolomics-the link between genotypes and phenotypes. Plant Mol Biol 48:155–171CrossRefPubMedGoogle Scholar
  50. 50.
    Goodacre R, Vaidyanathan S, Kell DB et al (2004) Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol 22:245–252CrossRefPubMedGoogle Scholar
  51. 51.
    Griffin JL, Bollard ME (2004) Metabonomics: its potential as a tool in toxicology for safety assessment and data integration. Curr Drug Metab 5:389–398CrossRefPubMedGoogle Scholar
  52. 52.
    Lindon JC, Holmes E, Nicholson JK (2004) Metabonomics technologies and their applications in physiological monitoring, drug safety assessment and disease diagnosis. Biomarkers 9:1–31CrossRefPubMedGoogle Scholar
  53. 53.
    Lindon JC, Holmes E, Nicholson JK (2003) So What’s the deal with metabonomics? Anal Chem 75:384–391CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Pranov Ramana
    • 1
  • Erwin Adams
    • 1
  • Patrick Augustijns
    • 2
  • Ann Van Schepdael
    • 1
  1. 1.Pharmaceutical Analysis, Department of Pharmaceutical and Pharmacological SciencesKU LeuvenLeuvenBelgium
  2. 2.Department of Pharmaceutical and Pharmacological Sciences, Drug Delivery and DispositionKU LeuvenLeuvenBelgium

Personalised recommendations