American Journal of Pharmacogenomics

, Volume 5, Issue 1, pp 53–62 | Cite as

Pharmacogenomics and the Drug Discovery Pipeline

When Should it Be Implemented?
Genomics in Drug Development


One of the key factors in developing improved medicines lies in understanding the molecular basis of the complex diseases we treat. Investigation of genetic associations with disease utilizing advances in linkage disequilibrium-based whole genome association strategies will provide novel targets for therapy and define relevant pathways contributing to disease pathogenesis. Genetic studies in conjunction with gene expression, proteomic, and metabonomic analyses provide a powerful tool to identify molecular subtypes of disease. Using these molecular data, pharmacogenomics has the potential to impact on the drug discovery and development process at many stages of the pipeline, contributing to both target identification and increased confidence in the therapeutic rationale. This is exemplified by the identified association of 5-lipoxygenase-activating protein (ALOX5AP/FLAP) with increased risk of myocardial infarction, and of the chemokine receptor 5 (CCR5) with HIV infection and therapy. Pharmacogenomics has already been used in oncology to demonstrate that molecular data facilitates assessment of disease heterogeneity, and thus identification of molecular markers of response to drugs such as imatinib mesylate (Gleevec®) and trastuzumab (Herceptin®). p]Knowledge of genetic variation in a target allows early assessment of the clinical significance of polymorphism through the appropriate design of preclinical studies and use of relevant animal models. A focussed pharmacogenomic strategy at the preclinical phase of drug development will produce data to inform the pharmacogenomic plan for exploratory and full development of compounds. Opportunities post-approval show the value of large well-characterized data sets for a systematic assessment of the contribution of genetic determinants to adverse drug reactions and efficacy. The availability of genomic samples in large phase IV trials also provides a valuable resource for further understanding the molecular basis of disease heterogeneity, providing data that feeds back into the drug discovery process in target identification and validation for the next generation of improved medicines.


  1. 1.
    Cholerton S, Daly AK, Idle JR. The role of individual human cytochromes P450 in drug metabolism and clinical response. Trends Pharmacol Sci 1992; 13(12): 434–9PubMedCrossRefGoogle Scholar
  2. 2.
    Malhi H, Atac B, Daly AK, et al. Warfarin and celecoxib interaction in the setting of cytochrome P450 (CYP2C9) polymorphism with bleeding complication. Postgrad Med J 2004; 80(940): 107–9PubMedCrossRefGoogle Scholar
  3. 3.
    Shah RR. Pharmacogenetic aspects of drug-induced torsade de pointes: potential tool for improving clinical drug development and prescribing. Drug Saf 2004; 27(3): 145–72PubMedCrossRefGoogle Scholar
  4. 4.
    Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome. Nature 2001; 409(6822): 860–921PubMedCrossRefGoogle Scholar
  5. 5.
    Venter JC, Adams MD, Myers EW, et al. The sequence of the human genome. Science 2001; 291(5507): 1304–51PubMedCrossRefGoogle Scholar
  6. 6.
    Walsh EC, Mather KA, Schaffner SF, et al. An integrated haplotype map of the human major histocompatibility complex. Am J Hum Genet 2003; 73(3): 580–90PubMedCrossRefGoogle Scholar
  7. 7.
    Schmutz J, Wheeler J, Grimwood J, et al. Quality assessment of the human genome sequence. Nature 2004; 429(6990): 365–8PubMedCrossRefGoogle Scholar
  8. 8.
    Bentley DR. Genomes for medicine. Nature 2004; 429(6990): 440–5PubMedCrossRefGoogle Scholar
  9. 9.
    Zee RY, Lou YK, Griffiths LR, et al. Association of a polymorphism of the angiotensin I-converting enzyme gene with essential hypertension. Biochem Biophys Res Commun 1992; 184(1): 9–15PubMedCrossRefGoogle Scholar
  10. 10.
    Province MA, Kardia SL, Ranade K, et al. A meta-analysis of genome-wide linkage scans for hypertension: the National Heart, Lung and Blood Institute Family Blood Pressure Program. Am J Hypertens 2003; 16(2): 144–7PubMedCrossRefGoogle Scholar
  11. 11.
    Turki J, Pak J, Green SA, et al. Genetic polymorphisms of the beta 2-adrenergic receptor in nocturnal and nonnocturnal asthma: evidence that Gly16 correlates with the nocturnal phenotype. J Clin Invest 1995; 95(4): 1635–41PubMedCrossRefGoogle Scholar
  12. 12.
    Santillan AA, Camargo CA, Ramirez-Rivera A, et al. Association between beta2-adrenoceptor polymorphisms and asthma diagnosis among Mexican adults. J Allergy Clin Immunol 2003; 112(6): 1095–100PubMedCrossRefGoogle Scholar
  13. 13.
    Ogilvie AD, Battersby S, Bubb VJ, et al. Polymorphism in serotonin transporter gene associated with susceptibility to major depression. Lancet 1996; 347(9003): 731–3PubMedCrossRefGoogle Scholar
  14. 14.
    Golimbet VE, Alfimova MV, Shchebatykh TV, et al. Serotonin transporter polymorphism and depressive-related symptoms in schizophrenia. Am J Med Genet 2004; 126B(1): 1–7PubMedCrossRefGoogle Scholar
  15. 15.
    Liu R, Paxton WA, Choe S, et al. Homozygous defect in HIV-1 coreceptor accounts for resistance of some multiply-exposed individuals to HIV-1 infection. Cell 1996; 86(3): 367–77PubMedCrossRefGoogle Scholar
  16. 16.
    Samson M, Libert F, Doranz BJ, et al. Resistance to HIV-1 infection in Caucasian individuals bearing mutant alleles of the CCR-5 chemokine receptor gene. Nature 1996; 382(6593): 722–5PubMedCrossRefGoogle Scholar
  17. 17.
    Michael NL, Louie LG, Rohrbaugh AL, et al. The role of CCR5 and CCR2 polymorphisms in HIV-1 transmission and disease progression. Nat Med 1997; 3(10): 1160–2PubMedCrossRefGoogle Scholar
  18. 18.
    Eugen-Olsen J, Iversen AK, Garred P, et al. Heterozygosity for a deletion in the CKR-5 gene leads to prolonged AIDS-free survival and slower CD4 T-cell decline in a cohort of HIV-seropositive individuals. Aids 1997; 11(3): 305–10PubMedCrossRefGoogle Scholar
  19. 19.
    Shieh B, Liau YE, Hsieh PS, et al. Influence of nucleotide polymorphisms in the CCR2 gene and the CCR5 promoter on the expression of cell surface CCR5 and CXCR4. Int Immunol 2000; 12(9): 1311–8PubMedCrossRefGoogle Scholar
  20. 20.
    Salkowitz JR, Bruse SE, Meyerson H, et al. CCR5 promoter polymorphism determines macrophage CCR5 density and magnitude of HIV-1 propagation in vitro. Clin Immunol 2003; 108(3): 234–40PubMedCrossRefGoogle Scholar
  21. 21.
    McDermott DH, Zimmerman PA, Guignard F, et al. CCR5 promoter polymorphism and HIV-1 disease progression: Multicenter AIDS Cohort Study (MACS). Lancet 1998; 352(9131): 866–70PubMedCrossRefGoogle Scholar
  22. 22.
    Carrington M, Dean M, Martin MP, et al. Genetics of HIV-1 infection: chemokine receptor CCR5 polymorphism and its consequences. Hum Mol Genet 1999; 8(10): 1939–45PubMedCrossRefGoogle Scholar
  23. 23.
    Feinberg J. Meeting notes from the 43rd Interscience Conference on Antimicrobial Agents and Chemotherapy (ICAAC): new CCR5 antagonist shows antiretroviral effect. AIDS Clin Care 2003; 15(11): 94–5Google Scholar
  24. 24.
    Gretarsdottir S, Thorleifsson G, Reynisdottir ST, et al. The gene encoding phosphodiesterase 4D confers risk of ischemic stroke. Nat Genet 2003; 35(2): 131–8PubMedCrossRefGoogle Scholar
  25. 25.
    Helgadottir A, Manolescu A, Thorleifsson G, et al. The gene encoding 5-lipoxygenase activating protein confers risk of myocardial infarction and stroke. Nat Genet 2004; 36(3): 233–9PubMedCrossRefGoogle Scholar
  26. 26.
    Peltekova VD, Wintle RF, Rubin LA, et al. Functional variants of OCTN cation transporter genes are associated with Crohn disease. Nat Genet 2004; 36(5): 471–5PubMedCrossRefGoogle Scholar
  27. 27.
    Stoll M, Corneliussen B, Costello CM, et al. Genetic variation in DLG5 is associated with inflammatory bowel disease. Nat Genet 2004; 36(5): 476–80PubMedCrossRefGoogle Scholar
  28. 28.
    The International HapMap Project. Nature 2003; 426(6968): 789–96CrossRefGoogle Scholar
  29. 29.
    Couzin J. Genomics: consensus emerges on HapMap strategy. Science 2004; 304(5671): 671–3PubMedCrossRefGoogle Scholar
  30. 30.
    Carlson CS, Eberle MA, Kruglyak L, et al. Mapping complex disease loci in whole-genome association studies. Nature 2004; 429(6990): 446–52PubMedCrossRefGoogle Scholar
  31. 31.
    John S, Shephard N, Liu G, et al. Whole-genome scan, in a complex disease, using 11,245 single-nucleotide polymorphisms: comparison with microsatellites. Am J Hum Genet 2004; 75(1): 54–64PubMedCrossRefGoogle Scholar
  32. 32.
    Frazer K, Seymour, AB, Thompson, JF, et al. Identification of the genetic basis of individual differences in human serum high-density lipoprotein cholesterol (HDL-C) concentration. Los Angeles (CA): American Society of Human Genetics, 2004Google Scholar
  33. 33.
    Galileo genomics discovers more than 10 new gene candidate regions in Crohn’s disease in whole genome study powered by perlegen technology [online]. Genizon BioSciences 2004 Jun 22 [press release]. Available from URL: [Accessed 2005 Jan 28]Google Scholar
  34. 34.
    Silber BM. Pharmacogenomics, biomarkers and the promise of personalised medicine. In: Kallow W, Myer U, Tyndale R, editors. Pharmacogenomics. New York: Marcell Dekker, 2001Google Scholar
  35. 35.
    Caulfield M, Munroe P, Pembroke J, et al. Genome-wide mapping of human loci for essential hypertension. Lancet 2003; 361(9375): 2118–23PubMedCrossRefGoogle Scholar
  36. 36.
    Harrap SB. Where are all the blood-pressure genes? Lancet 2003; 361(9375): 2149–51PubMedCrossRefGoogle Scholar
  37. 37.
    Colhoun HM, McKeigue PM, Davey Smith G. Problems of reporting genetic associations with complex outcomes. Lancet 2003; 361(9360): 865–72PubMedCrossRefGoogle Scholar
  38. 38.
    Neale BM, Sham PC. The future of association studies: gene-based analysis and replication. Am J Hum Genet 2004; 75(3): 353–62PubMedCrossRefGoogle Scholar
  39. 39.
    Schadt EE, Monks SA, Drake TA, et al. Genetics of gene expression surveyed in maize, mouse and man. Nature 2003; 422(6929): 297–302PubMedCrossRefGoogle Scholar
  40. 40.
    Di Fiore PP, Pierce JH, Kraus MH, et al. erbB-2 is a potent oncogene when overexpressed in NIH/3T3 cells. Science 1987; 237(4811): 178–82PubMedCrossRefGoogle Scholar
  41. 41.
    Kraus MH, Di Fiore PP, Pierce JH, et al. Different mechanisms are responsible for oncogene activation in human mammary neoplasia. Cancer Treat Res 1988; 40: 49–66PubMedCrossRefGoogle Scholar
  42. 42.
    Vogel CL, Cobleigh MA, Tripathy D, et al. Efficacy and safety of trastuzumab as a single agent in first-line treatment of HER2-overexpressing metastatic breast cancer. J Clin Oncol 2002; 20(3): 719–26PubMedCrossRefGoogle Scholar
  43. 43.
    Deininger MW, Goldman JM, Lydon N, et al. The tyrosine kinase inhibitor CGP57148B selectively inhibits the growth of BCR-ABL-positive cells. Blood 1997; 90(9): 3691–8PubMedGoogle Scholar
  44. 44.
    Cohen MH, Moses ML, Pazdur R. Gleevec for the treatment of chronic myelogenous leukemia: US Food and Drug Administration regulatory mechanisms, accelerated approval, and orphan drug status. Oncologist 2002; 7(5): 390–2PubMedCrossRefGoogle Scholar
  45. 45.
    Deininger MW. Basic science going clinical: molecularly targeted therapy of chronic myelogenous leukemia. J Cancer Res Clin Oncol 2004; 130(2): 59–72PubMedCrossRefGoogle Scholar
  46. 46.
    Drews J. Genomic sciences and the medicine of tomorrow. Nat Biotechnol 1996; 14(11): 1516–8PubMedCrossRefGoogle Scholar
  47. 47.
    Drews J, Ryser S. The role of innovation in drug development. Nat Biotechnol 1997; 15(13): 1318–9PubMedCrossRefGoogle Scholar
  48. 48.
    Hopkins AL, Groom CR. The draggable genome. Nat Rev Drag Discov 2002; 1(9): 727–30CrossRefGoogle Scholar
  49. 49.
    Claverie JM. Gene number: what if there are only 30,000 human genes? Science 2001; 291(5507): 1255–7PubMedCrossRefGoogle Scholar
  50. 50.
    Cargill M, Altshuler D, Ireland J, et al. Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nat Genet 1999; 22(3): 231–8PubMedCrossRefGoogle Scholar
  51. 51.
    Iida A, Saito S, Sekine A, et al. Catalog of 668 SNPs detected among 31 genes encoding potential drag targets on the cell surface. J Hum Genet 2003; 48(1): 23–46PubMedCrossRefGoogle Scholar
  52. 52.
    Iida A, Saito S, Sekine A, et al. Catalog of 300 SNPs in 23 genes encoding G-protein coupled receptors. J Hum Genet 2004; 49(4): 194–208PubMedCrossRefGoogle Scholar
  53. 53.
    Johnson JA, Lima JJ. Drag receptor/effector polymorphisms and pharmacogenetics: current status and challenges. Pharmacogenetics 2003; 13(9): 525–34PubMedCrossRefGoogle Scholar
  54. 54.
    Dvornyk V, Long JR, Xiong DH, et al. Current limitations of SNP data from the public domain for studies of complex disorders: a test for ten candidate genes for obesity and osteoporosis. BMC Genet 2004; 5(1): 4PubMedCrossRefGoogle Scholar
  55. 55.
    Dvornyk V, Liu XH, Shen H, et al. Differentiation of Caucasians and Chinese at bone mass candidate genes: implication for ethnic difference of bone mass. Ann Hum Genet 2003; 67 (Pt 3): 216–27PubMedCrossRefGoogle Scholar
  56. 56.
    West DB, Iakougova O, Olsson C, et al. Mouse genetics/genomics: an effective approach for drug target discovery and validation. Med Res Rev 2000; 20(3): 216–30PubMedCrossRefGoogle Scholar
  57. 57.
    Rothberg BE. The use of animal models in expression pharmacogenomic analyses. Pharmacogenomics J 2001; 1(1): 48–58PubMedCrossRefGoogle Scholar
  58. 58.
    Lord PG. Progress in applying genomics in drag development. Toxicol Lett 2004; 149(1–3): 371–5PubMedCrossRefGoogle Scholar
  59. 59.
    Almind K, Kulkarni RN, Lannon SM, et al. Identification of interactive loci linked to insulin and leptin in mice with genetic insulin resistance. Diabetes 2003; 52(6): 1535–43PubMedCrossRefGoogle Scholar
  60. 60.
    Leiter EH, Reifsnyder PC. Differential levels of diabetogenic stress in two new mouse models of obesity and type 2 diabetes. Diabetes 2004; 53Suppl. 1: S4–11PubMedCrossRefGoogle Scholar
  61. 61.
    Qi N, Kazdova L, Zidek V, et al. Pharmacogenetic evidence that cd36 is a key determinant of the metabolic effects of pioglitazone. J Biol Chem 2002; 277(50): 48501–7PubMedCrossRefGoogle Scholar
  62. 62.
    Chesler EJ, Ritchie J, Kokayeff A, et al. Genotype-dependence of gabapentin and pregabalin sensitivity: the pharmacogenetic mediation of analgesia is specific to the type of pain being inhibited. Pain 2003; 106(3): 325–35PubMedCrossRefGoogle Scholar
  63. 63.
    Pennisi E. Genetics: genome resources to boost canines’ role in gene hunts. Science 2004; 304(5674): 1093–5PubMedCrossRefGoogle Scholar
  64. 64.
    Gibbs RA, Weinstock GM, Metzker ML, et al. Genome sequence of the Brown Norway rat yields insights into mammalian evolution. Nature 2004; 428(6982): 493–521PubMedCrossRefGoogle Scholar
  65. 65.
    Kawai J, Shinagawa A, Shibata K, et al. Functional annotation of a full-length mouse cDNA collection. Nature 2001; 409(6821): 685–90PubMedCrossRefGoogle Scholar
  66. 66.
    Frolov A, Chahwan S, Ochs M, et al. Response markers and the molecular mechanisms of action of Gleevec in gastrointestinal stromal tumors. Mol Cancer Ther 2003; 2(8): 699–709PubMedGoogle Scholar
  67. 67.
    Penny M, Myrand, S, Lin, C, et al. Pharmacogenetic analysis of polymorphisms in the chemokine receptors CCR5 and CCR2 in the clinical development of a CCR5 antagonist (UK-427, 857) for the treatment of HIV/AIDS. Washington, DC: FDA Science Forum, 2004Google Scholar
  68. 68.
    Salerno RA, Lesko LJ. Pharmacogenomics in drug development and regulatory decision-making: the Genomic Data Submission (GDS) proposal. Pharmacogenomics 2004; 5(1): 25–30PubMedCrossRefGoogle Scholar
  69. 69.
    Lesko LJ, Salerno RA, Spear BB, et al. Pharmacogenetics and pharmacogenomics in drug development and regulatory decision making: report of the first FDAPWG-PhRMA-DruSafe Workshop. J Clin Pharmacol 2003; 43(4): 342–58PubMedCrossRefGoogle Scholar
  70. 70.
    Lesko LJ, Woodcock J. Pharmacogenomic-guided drug development: regulatory perspective. Pharmacogenomics J 2002; 2(1): 20–4PubMedCrossRefGoogle Scholar
  71. 71.
    Ruano G, Collins JM, Dorner AJ, et al. Pharmacogenomic data submissions to the FDA: clinical pharmacology case studies. Pharmacogenomics 2004; 5(5): 513–7PubMedCrossRefGoogle Scholar
  72. 72.
    Pirmohamed M, James S, Meakin S, et al. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. BMJ 2004; 329(7456): 15–9PubMedCrossRefGoogle Scholar
  73. 73.
    Stricker BH, Psaty BM. Detection, verification, and quantification of adverse drug reactions. BMJ 2004; 329(7456): 44–7PubMedCrossRefGoogle Scholar
  74. 74.
    GlaxoSmithKline and First Genetic Trust to collaborate on additional study to identify genetic basis for Aaverse drug reactions [online]. First Genetic Trust. [press release] 2004 may 25. Available from URL: [Accessed 2005 Jan 28]
  75. 75.
    Haas DW, Wilkinson GR, Kuritzkes DR, et al. A multi-investigator/institutional DNA bank for AIDS-related human genetic studies: AACTG Protocol A5128. HIV Clin Trials 2003; 4(5): 287–300PubMedCrossRefGoogle Scholar
  76. 76.
    Payne DA, Bryant BJ. HIV Pharmacogenomics: closer to personalized therapy? Am J Pharmacogenomics 2004; 4(3): 141–50PubMedCrossRefGoogle Scholar
  77. 77.
    Pirmohamed M, Back DJ. The pharmacogenomics of HIV therapy. Pharmacogenomics J 2001; 1(4): 243–53PubMedCrossRefGoogle Scholar
  78. 78.
    Voigt E, Wasmuth JC, Vogel M, et al. Safety, efficacy and development of resistance under the new protease inhibitor lopinavir/ritonavir: 48-week results. Infection 2004; 32(2): 82–8PubMedCrossRefGoogle Scholar
  79. 79.
    Fellay J, Marzolini C, Meaden ER, et al. Response to antiretroviral treatment in HIV-1-infected individuals with allelic variants of the multidrug resistance transporter 1: a pharmacogenetics study. Lancet 2002; 359(9300): 30–6PubMedCrossRefGoogle Scholar
  80. 80.
    Hughes AR, Mosteller M, Bansal AT, et al. Association of genetic variations in HLA-B region with hypersensitivity to abacavir in some, but not all, populations. Pharmacogenomics 2004; 5(2): 203–11PubMedCrossRefGoogle Scholar
  81. 81.
    Martin AM, Nolan D, Gaudieri S, et al. Predisposition to abacavir hypersensitivity conferred by HLA-B*5701 and a haplotypic Hsp70-Hom variant. Proc Natl Acad Sci U S A 2004; 101(12): 4180–5PubMedCrossRefGoogle Scholar
  82. 82.
    Sever PS, Dahlof B, Poulter NR, et al. Anglo-Scandinavian Cardiac Outcomes Trial: a brief history, rationale and outline protocol. J Hum Hypertens 2001; 15Suppl. 1: S11–2PubMedGoogle Scholar
  83. 83.
    Sever PS, Dahlof B, Poulter NR, et al. Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial-Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial. Lancet 2003; 361(9364): 1149–58PubMedCrossRefGoogle Scholar
  84. 84.
    Chasman DI, Posada D, Subrahmanyan L, et al. Pharmacogenetic study of statin therapy and cholesterol reduction. JAMA 2004; 291(23): 2821–7PubMedCrossRefGoogle Scholar
  85. 85.
    Boekholdt SM, Agema WR, Peters RJ, et al. Variants of toll-like receptor 4 modify the efficacy of statin therapy and the risk of cardiovascular events. Circulation 2003; 107(19): 2416–21PubMedCrossRefGoogle Scholar
  86. 86.
    Mank-Seymour AR, Durham KL, Thompson JF, et al. Association between single-nucleotide polymorphisms in the endothelial lipase (LIPG) gene and high-density lipoprotein cholesterol levels. Biochim Biophys Acta 2004; 1636(1): 40–6PubMedCrossRefGoogle Scholar

Copyright information

© Adis Data Information BV 2005

Authors and Affiliations

  1. 1.Clinical Pharmacogenomics, Pfizer Global Research and DevelopmentSandwich Laboratories (ipc 746)SandwichUK

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