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Reducing safety-related drug attrition: the use of in vitro pharmacological profiling


In vitro pharmacological profiling is increasingly being used earlier in the drug discovery process to identify undesirable off-target activity profiles that could hinder or halt the development of candidate drugs or even lead to market withdrawal if discovered after a drug is approved. Here, for the first time, the rationale, strategies and methodologies for in vitro pharmacological profiling at four major pharmaceutical companies (AstraZeneca, GlaxoSmithKline, Novartis and Pfizer) are presented and illustrated with examples of their impact on the drug discovery process. We hope that this will enable other companies and academic institutions to benefit from this knowledge and consider joining us in our collaborative knowledge sharing.

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Figure 1: Alignment of in vitro pharmacology profiling to the drug discovery and development process.
Figure 2: Levels of promiscuity among marketed drugs and Novartis's compounds.
Figure 3: In vitro profiling during lead optimization.


  1. 1

    Stevens, J. L. Future of toxicology — mechanisms of toxicity and drug safety: where do we go from here? Chem. Res. Toxicol. 19, 1393–1401 (2006).

    CAS  PubMed  Google Scholar 

  2. 2

    Redfern, W. S. et al. Safety pharmacology — a progressive approach. Fundam. Clin. Pharmacol. 16, 161–173 (2002).

    CAS  PubMed  Google Scholar 

  3. 3

    Smith, D. A. & Schmid, E. F. Drug withdrawals and the lessons within. Curr. Opin. Drug Discov. Devel. 9, 38–46 (2006).

    CAS  PubMed  Google Scholar 

  4. 4

    European Medicines Agency (EMA). ICH Topic S7A: Safety pharmacology studies for human pharmaceuticals. CPMP/ICH/539/00. EMA website [online], (2001).

  5. 5

    European Medicines Agency (EMA). ICH Topic S7B: The nonclinical evaluation of the potential for delayed ventricular repolarization (QT interval prolongation) by human pharmaceuticals. CPMP/ICH/423/02. EMA website [online], (2005).

  6. 6

    European Medicines Agency (EMA). ICH Topic M3 (R2): Non-clinical safety studies for the conduct of human clinical trials and marketing authorization for pharmaceuticals. CPMP/ICH/286/95. EMA website [online], (2009).

  7. 7

    Sanguinetti, M. C., Jiang, C., Curran, M. E. & Keating, M. T. A mechanistic link between an inherited and an acquired cardiac arrhythmia: HERG encodes the IKr potassium channel. Cell 81, 299–307 (1995).

    CAS  PubMed  Google Scholar 

  8. 8

    Redfern, W. S. et al. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: evidence for a provisional safety margin in drug development. Cardiovasc. Res. 58, 32–45 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9

    European Medicines Agency (EMA). Guideline on the non-clinical investigation of the dependence potential of medicinal products. EMEA/CHMP/SWP/94227/2004. EMA website [online], (2006).

  10. 10

    Rothman, R. B. et al. Evidence for possible involvement of 5-HT2B receptors in the cardiac valvulopathy associated with fenfluramine and other serotonergic medications. Circulation 102, 2836–2841 (2000).

    CAS  PubMed  Google Scholar 

  11. 11

    Huang, X. P. et al. Parallel functional activity profiling reveals valvulopathogens are potent 5-hydroxytryptamine2B receptor agonists: implications for drug safety assessment. Mol. Pharmacol. 76, 710–722 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Whitebread, S., Hamon, J., Bojanic, D. & Urban, L. In vitro safety pharmacology profiling: an essential tool for drug development. Drug Discov. Today 10, 1421–1433 (2005).

    CAS  PubMed  Google Scholar 

  13. 13

    Bowes, J. et al. in The Process of New Drug Discovery and Development 2nd edn (eds Smith, C. G. & O'Donnell, J. T.) 103–134 (Informa Healthcare, 2006).

    Google Scholar 

  14. 14

    Laverty, H. G. et al. How can we improve our understanding of cardiovascular safety liabilities to develop safer medicines? Br. J. Pharmacol. 163, 675–693 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15

    Hamon, J. & Whitebread, S. in Hit and Lead Profiling (eds Faller, B. & Urban, L.) 273–295 (Wiley VCH, 2009).

    Google Scholar 

  16. 16

    Spence, S., Anderson, C., Cukierski, M. & Patrick, D. Teratogenic effects of the endothelin receptor antagonist L-753,037 in the rat. Reprod. Toxicol. 13, 15–29 (1999).

    CAS  PubMed  Google Scholar 

  17. 17

    Hulme, E. C., Birdsall, N. J. M. & Buckley, N. J. Muscarinic receptor subtypes. Annu. Rev. Pharmacol. Toxicol. 30, 633–673 (1990).

    CAS  PubMed  Google Scholar 

  18. 18

    Gerretsen, P. & Pollock, B. G. Drugs with anticholinergic properties: a current perspective on use and safety. Expert Opin. Drug Saf. 10, 751–765 (2011).

    PubMed  Google Scholar 

  19. 19

    Terstappen, G. C., Roncarati, R., Dunlop, J. & Peri, R. Screening technologies for ion channel drug discovery. Future Med. Chem. 2, 691–695 (2010).

    Google Scholar 

  20. 20

    Force, T. & Kolaja, K. L. Cardiotoxicity of kinase inhibitors: the prediction and translation of preclinical models to clinical outcomes. Nature Rev. Drug Discov. 10, 111–126 (2011).

    CAS  Google Scholar 

  21. 21

    Mellor, H. R., Bell, A. R., Valentin, J.-P. & Roberts, R. R. A. Cardiotoxicity associated with targeting kinase pathways in cancer. Toxicol. Sci. 120, 14–32 (2011).

    CAS  PubMed  Google Scholar 

  22. 22

    Bi, K., Lebakken, C. S. & Vogel, K. W. Transformation of in vitro tools for kinase profiling: keeping an eye over the off-target liabilities. Expert Opin. Drug Discov. 6, 701–712 (2011).

    CAS  PubMed  Google Scholar 

  23. 23

    Gilchrist, A. (ed.) GPCR Molecular Pharmacology and Drug Targeting: Shifting Paradigms and New Directions (Wiley, 2010).

    Google Scholar 

  24. 24

    Bridgland-Taylor, M. H. et al. Optimisation and validation of a medium-throughput electrophysiology-based hERG assay using IonWorks HT. J. Pharmacol. Toxicol. Methods 54, 189–199 (2006).

    CAS  PubMed  Google Scholar 

  25. 25

    Harmer, A. R. et al. Optimisation and validation of a medium-throughput electrophysiology-based hNav1.5 assay using IonWorks. J. Pharmacol. Toxicol. Methods 57, 30–41 (2008).

    CAS  PubMed  Google Scholar 

  26. 26

    Hamon, J. et al. In vitro safety pharmacology profiling: what else beyond hERG? Future Med. Chem. 1, 645–665 (2009).

    CAS  PubMed  Google Scholar 

  27. 27

    Migeon, J. in Polypharmacology in Drug Discovery (ed. Peters, J.-U. ) 111–132 (Wiley, 2012).

    Google Scholar 

  28. 28

    Valentin, J.-P. & Hammond, T. J. Safety and secondary pharmacology: successes, threats, challenges and opportunities. J. Pharmacol. Toxicol. Methods 58, 77–87 (2008).

    CAS  PubMed  Google Scholar 

  29. 29

    Heath, B. M., et al. Translation of flecainide- and mexiletine-induced cardiac sodium channel inhibition and ventricular conduction slowing from nonclinical models to clinical. J. Pharmacol. Toxicol. Methods 63, 258–268 (2011).

    CAS  PubMed  Google Scholar 

  30. 30

    Lazzara, R. Antiarrhythmic drugs and torsade de pointes. Eur. Heart J. 14 (Suppl. H), 88–92 (1993).

    PubMed  Google Scholar 

  31. 31

    Hamon, J. et al. In vitro safety pharmacology profiling. Eur. Pharmaceut. Rev. 2006, 60–63 (2006).

    Google Scholar 

  32. 32

    Leeson, P. D. & Springthorpe, B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nature Rev. Drug Discov. 6, 881–890 (2007).

    CAS  Google Scholar 

  33. 33

    Azzaoui, K. et al. Modeling promiscuity based on in vitro safety pharmacology profiling data. ChemMedChem 2, 874–880 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34

    Hughes, J. D. et al. Physiochemical drug properties associated with in vivo toxicological outcomes. Bioorg. Med. Chem. Lett. 18, 4872–4875 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35

    Peters, J.-U. et al. Can we discover pharmacological promiscuity early in the drug discovery process? Drug Discov. Today 17, 325–335 (2012).

    PubMed  Google Scholar 

  36. 36

    Peters, J.-U., Schnider, P., Mattei, P. & Kansy, M. Pharmacological promiscuity: dependence on compound properties and target specificity in a set of recent Roche compounds. ChemMedChem 4, 680–686 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37

    Fryer, R. M. et al. Mitigation of off-target adrenergic binding and effects on cardiovascular function in the discovery of novel ribosomal S6 kinase 2 inhibitors. J. Pharmacol. Exp. Ther. 340, 492–500 (2012).

    CAS  PubMed  Google Scholar 

  38. 38

    Gintant, G. An evaluation of hERG current assay performance: translating preclinical safety studies to clinical QT prolongation. Pharmacol. Ther. 129, 109–119 (2011).

    CAS  PubMed  Google Scholar 

  39. 39

    Harmer, A. R., Valentin, J.-P. & Pollard, C. E. On the relationship between block of the cardiac Na+ channel and drug-induced prolongation of the QRS complex. Br. J. Pharmacol. 164, 260–273 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40

    O'Connor, E. C., Chapman, K., Butler, P. & Mead, A. N. The predictive validity of the rat self-administration model for abuse liability. Neurosci. Biobehav. Rev. 35, 912–938 (2011).

    CAS  PubMed  Google Scholar 

  41. 41

    Overington, J. P., Al-Lazikani, B. & Hopkins, A. L. How many drug targets are there? Nature Rev. Drug Discov. 5, 993–996 (2006).

    CAS  Google Scholar 

  42. 42

    Taboureau, O. & Jørgensen, F. S. In silico predictions of hERG channel blockers in drug discovery: from ligand-based and target-based approaches to systems chemical biology. Comb. Chem. High Throughput Screen. 14, 375–387 (2011).

    CAS  PubMed  Google Scholar 

  43. 43

    Marchant, C. A., Briggs, K. A. & Long, A. In silico tools for sharing data and knowledge on toxicity and metabolism: Derek for Windows, Meteor, and Vitic. Toxicol. Mech. Methods 18, 177–187 (2008).

    CAS  PubMed  Google Scholar 

  44. 44

    Ekins, S., Mestres, J. & Testa, B. In silico pharmacology for drug discovery: applications to targets and beyond. Br. J. Pharmacol. 152, 21–37 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Bender, A. et al. Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure. ChemMedChem 2, 861–873 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46

    Nigsch, F. et al. Computational methods for early predictive safety assessment from biological and chemical data. Expert Opin. Drug Metab. Toxicol. 7, 1497–1511 (2011).

    CAS  PubMed  Google Scholar 

  47. 47

    Lounkine, E. et al. Large scale prediction and testing of drug activity on side-effect targets. Nature 486, 361–367 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48

    Vargas, H. M. et al. Scientific review and recommendations on preclinical cardiovascular safety evaluation of biologics. J. Pharmacol. Toxicol. Methods 58, 72–76 (2008).

    CAS  PubMed  Google Scholar 

  49. 49

    Mattes, W. B. & Walker, E. G. Translational toxicology and the work of the predictive safety testing consortium. Clin. Pharmacol. Ther. 85, 327–330 (2009).

    CAS  PubMed  Google Scholar 

  50. 50

    Knudsen, T. B. et al. Activity profiles of 309 ToxCast chemicals evaluated across 292 biochemical targets. Toxicology 282, 1–15 (2011).

    CAS  PubMed  Google Scholar 

  51. 51

    Wasserman, A. M. & Bajorath, J. BindingDB and ChEMBL: online compound databases for drug discovery. Expert Opin. Drug Discov. 6, 683–687 (2011).

    Google Scholar 

  52. 52

    Mirams, G. R. et al. Simulation of multiple ion channel block provides improved early prediction of drug molecules' clinical torsadogenic risk. Cardiovasc. Res. 91, 53–61 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Orchard, S. et al. Minimum information about a bioactive entity (MIABE). Nature Rev. Drug Discov. 10, 661–669 (2011).

    CAS  Google Scholar 

  54. 54

    Gintant, G. A., Gallacher, D. J. & Pugsley, M. K. The 'overly-sensitive' heart: sodium channel block and QRS interval prolongation. Br. J. Pharmacol. 164, 254–259 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Pfeufer, A. et al. Genome-wide association study of PR interval. Nature Genet. 42, 153–161 (2010).

    CAS  PubMed  Google Scholar 

  56. 56

    Erdemli, G. et al. Cardiac safety implications of hNav1.5 blockade and a framework for pre-clinical evaluation. Front. Pharmacol. 3, 1–9 (2012).

    Google Scholar 

  57. 57

    Benarroch, E. E. Adenosine and its receptors: Multiple modulatory functions and potential therapeutic targets for neurologic disease. Neurology 70, 231–236 (2008).

    PubMed  Google Scholar 

  58. 58

    Michelotti, G. A., Price, D. T. & Schwinn, D. A. α1-adrenergic receptor regulation: basic science and clinical implications. Pharmacol. Ther. 88, 281–309 (2000).

    CAS  PubMed  Google Scholar 

  59. 59

    Philipp, M., Brede, M. & Hein, L. Physiological significance of α2-adrenergic receptor subtype diversity: one receptor is not enough. Am. J. Physiol. Regul. Integr. Comp. Physiol. 283, R287–R295 (2002).

    CAS  PubMed  Google Scholar 

  60. 60

    Lohse, M. J., Engelhardt, S. & Eschenhagen, T. What is the role of β-adrenergic signaling in heart failure? Circ. Res. 93, 896–906 (2003).

    CAS  PubMed  Google Scholar 

  61. 61

    Cazzola, M., Matera, M. G. & Donner, C. F. Inhaled β2-adrenoceptor agonists: cardiovascular safety in patients with obstructive lung disease. Drugs 65, 1595–1610 (2005).

    CAS  PubMed  Google Scholar 

  62. 62

    Le Foll, B., Gorelick, D. A. & Goldberg, S. R. The future of endocannabinoid-oriented clinical research after CB1 antagonists. Psychopharmacology (Berl.) 205, 171–174 (2009).

    CAS  Google Scholar 

  63. 63

    Basu, S. & Dittel, B. N. Unraveling the complexities of cannabinoid receptor 2 (CB2) immune regulation in health and disease. Immunol. Res. 51, 26–38 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64

    Dufresne, M., Seva, C. & Fourmy, D. Cholecystokinin and gastrin receptors. Physiol. Rev. 86, 805–847 (2006).

    CAS  PubMed  Google Scholar 

  65. 65

    Peacock, L. & Gerlach, J. Aberrant behavioral effects of a dopamine D1 receptor antagonist and agonist in monkeys: evidence of uncharted dopamine D1 receptor actions. Biol. Psychiatry 50, 501–509 (2001).

    CAS  PubMed  Google Scholar 

  66. 66

    Emilien, G. et al. Dopamine receptors — physiological understanding to therapeutic intervention potential. Pharmacol. Ther. 84, 133–156 (1999).

    CAS  PubMed  Google Scholar 

  67. 67

    Palmer, M. J. Endothelin receptor antagonists: status and learning 20 years on. Prog. Med. Chem. 47, 203–237 (2009).

    CAS  PubMed  Google Scholar 

  68. 68

    Walsh, G. M. Emerging safety issues regarding long-term usage of H1 receptor antagonists. Expert Opin. Drug Saf. 1, 225–235 (2002).

    CAS  PubMed  Google Scholar 

  69. 69

    Hattori, Y. Cardiac histamine receptors: their pharmacological consequences and signal transduction pathways. Methods Find. Exp. Clin. Pharmacol. 21, 123–131 (1999).

    CAS  PubMed  Google Scholar 

  70. 70

    Barron, B. A. Cardiac opioids. Proc. Soc. Exp. Biol. Med. 224, 1–7 (2000).

    CAS  PubMed  Google Scholar 

  71. 71

    Walsh, S. L. et al. Enadoline, a selective κ opioid agonist: comparison with butorphanol and hydromorphone in humans. Psychopharmacology (Berl.) 157, 151–162 (2001).

    CAS  Google Scholar 

  72. 72

    Trescot, A. M., Datta, S. & Lee, M. Opioid pharmacology. Pain Physician 11 (Suppl. 2), S133–S153 (2008).

    PubMed  Google Scholar 

  73. 73

    Medina, A. et al. Effects of central muscarinic-1 receptor stimulation on blood pressure regulation. Hypertension 29, 828–834 (1997).

    CAS  PubMed  Google Scholar 

  74. 74

    Jooste, E., Klafter, F., Hirshman, C. A. & Emala, C. W. A mechanism for rapacuronium-induced bronchospasm: M2 muscarinic receptor antagonism. Anesthesiology 98, 906–911 (2003).

    CAS  PubMed  Google Scholar 

  75. 75

    Krejsa, C. M. et al. Predicting ADME properties and side effects: the BioPrint approach. Curr. Opin. Drug Discov. Dev. 6, 470–480 (2003).

    CAS  Google Scholar 

  76. 76

    Lacivita, E., Leopoldo, M., Berardi, F. & Perrone, R. 5-HT1A receptor, an old target for new therapeutic agents. Curr. Top. Med. Chem. 8, 1024–1034 (2008).

    CAS  PubMed  Google Scholar 

  77. 77

    Van de Kar, L. D. et al. ICV injection of the serotonin 5-HT1B agonist CP-93,129 increases the secretion of ACTH, prolactin, and renin and increases blood pressure by nonserotonergic mechanisms. Pharmacol. Biochem. Behav. 48, 429–436 (1994).

    CAS  PubMed  Google Scholar 

  78. 78

    Sun-Edelstein, C., Tepper, S. J. & Shapiro, R. E. Drug-induced serotonin syndrome: a review. Expert Opin. Drug Saf. 7, 587–596 (2008).

    CAS  PubMed  Google Scholar 

  79. 79

    Roth, B. L. Drugs and valvular heart disease. N. Engl. J. Med. 356, 6–9 (2007).

    CAS  PubMed  Google Scholar 

  80. 80

    Barrett, L. K., Singer, M. & Clapp, L. H. Vasopressin: mechanisms of action on the vasculature in health and in septic shock. Crit. Care Med. 35, 33–40 (2007).

    CAS  PubMed  Google Scholar 

  81. 81

    Kalamida, D. et al. Muscle and neuronal nicotinic acetylcholine receptors. FEBS J. 274, 3799–3845 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  82. 82

    Splawski, I. et al. Cav1.2 calcium channel dysfunction causes a multisystem disorder including arrhythmia and autism. Cell 119, 19–31 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. 83

    Lader, M. Effectiveness of benzodiazepines: do they work or not? Expert Rev. Neurother. 8, 1189–1191 (2008).

    CAS  PubMed  Google Scholar 

  84. 84

    Curran, M. E. et al. A molecular basis for cardiac arrhythmia: HERG mutations cause long QT syndrome. Cell 80, 795–803 (1995).

    CAS  PubMed  Google Scholar 

  85. 85

    Towart, R. et al. Blockade of the IKs potassium channel: An overlooked cardiovascular liability in drug safety screening? J. Pharmacol. Tox. Methods 60, 1–10 (2009).

    CAS  Google Scholar 

  86. 86

    Murray, J. B. Phencyclidine (PCP): a dangerous drug, but useful in schizophrenia research. J. Psychol. 136, 319–327 (2002).

    PubMed  Google Scholar 

  87. 87

    Goodin, S. & Cunningham, R. 5-HT3-receptor antagonists for the treatment of nausea and vomiting: a reappraisal of their side-effect profile. Oncologist 7, 424–436 (2002).

    CAS  PubMed  Google Scholar 

  88. 88

    Smits, J. P. P. et al. Cardiac sodium channels and inherited electrophysiologic disorders: a pharmacogenetic overview. Exp. Opin. Pharmacother. 9, 537–549 (2008).

    CAS  Google Scholar 

  89. 89

    Moretto, A. Experimental and clinical toxicology of anticholinesterase agents. Toxicol. Lett. 102–103, 509–513 (1998).

    PubMed  Google Scholar 

  90. 90

    Süleyman, H., Demircan, B. & Karagöz, Y. Anti-inflammatory and side effects of cyclooxygenase inhibitors. Pharmacol. Rep. 59, 247–258 (2007).

    PubMed  Google Scholar 

  91. 91

    Grosser, T., Fries, S. & FitzGerald, G. A. Biological basis for the cardiovascular consequences of COX-2 inhibition: therapeutic challenges and opportunities. J. Clin. Invest. 116, 4–15 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. 92

    Youdim, M. B. & Weinstock, M. Therapeutic applications of selective and non-selective inhibitors of monoamine oxidase A and B that do not cause significant tyramine potentiation. Neurotoxicology 25, 243–250 (2004).

    CAS  PubMed  Google Scholar 

  93. 93

    Aguirre, S. A. et al. Cardiovascular effects in rats following exposure to a receptor tyrosine kinase inhibitor. Toxicol. Pathol. 38, 416–428 (2010).

    CAS  PubMed  Google Scholar 

  94. 94

    Absallem, E., Kasparian, C., Haddour, G., Boissel, J. P. & Nony, P. Phosphodiesterase III inhibitors for heart failure. Cochrane Database Syst. Rev. 2005, CD002230 (2005).

    Google Scholar 

  95. 95

    Giembycz, M. A. Can the anti-inflammatory potential of PDE4 inhibitors be realized: guarded optimism or wishful thinking? Br. J. Pharmacol. 155, 288–290 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. 96

    Spina, D. PDE4 inhibitors: current status. Br. J. Pharmacol. 155, 308–315 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. 97

    Goldman, F. D. et al. Defective expression of p56lck in an infant with severe combined immunodeficiency. J. Clin. Invest. 102, 421–429 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. 98

    Bannon, M. J. The dopamine transporter: role in neurotoxicity and human disease. Toxicol. Appl. Pharmacol. 204, 355–360 (2005).

    CAS  PubMed  Google Scholar 

  99. 99

    Mayer, A. F. et al. Influences of norepinephrine transporter function on the distribution of sympathetic activity in humans. Hypertension 48, 120–126 (2006).

    CAS  PubMed  Google Scholar 

  100. 100

    Stahl, S. M. Mechanism of action of serotonin selective reuptake inhibitors: serotonin receptors and pathways mediate therapeutic effects and side effects. J. Affect. Disord. 51, 215–235 (1998).

    CAS  PubMed  Google Scholar 

  101. 101

    Mooradian, A. D., Morley, J. E. & Korenman, S. G. Biological actions of androgens. Endocr. Rev. 8, 1–28 (1987).

    CAS  PubMed  Google Scholar 

  102. 102

    Davison, S. L. & Bell, R. Androgen physiology. Semin. Reprod. Med. 24, 71–77 (2006).

    CAS  PubMed  Google Scholar 

  103. 103

    McMaster, A. & Ray, D. W. Drug insight: selective agonists and antagonists of the glucocorticoid receptor. Nature Clin. Pract. Endocrinol. Metab. 4, 91–101 (2008).

    CAS  Google Scholar 

  104. 104

    Muller, P. Y. & Milton, M. N. The determination and interpretation of the therapeutic index in drug development. Nature Rev. Drug Discov. 11, 751–761 (2012).

    CAS  Google Scholar 

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The authors thank the following individuals for their valuable discussions: J.-P. Valentin and C. Pollard from AstraZeneca; L. Urban, P. Muller and G. Erdemli from Novartis; N. McMahon and J. Louttit from GlaxoSmithKline; and A. Mead from Pfizer.

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Correspondence to Joanne Bowes, Andrew J. Brown, Jacques Hamon, Wolfgang Jarolimek, Arun Sridhar, Gareth Waldron or Steven Whitebread.

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The authors declare no competing financial interests.

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Concentration required to elicit a 50% response in an in vitro assay. IC50 refers to an inhibitory response (the half maximal inhibitory concentration) and EC50 refers to an effect (the effector concentration for half-maximum response), usually an activation or stimulation. AC50 is a collective term used for any activity.

Adverse drug reactions

(ADRs). Any noxious, unintended and undesired effects of a drug, occurring at doses used in humans for prophylaxis, diagnosis or therapy. These exclude therapeutic failures, intentional and accidental poisoning and drug abuse.


The concentration of an agonist that is required to produce 50% of the maximum response of that agonist.

Free Cmax

The fraction of the Cmax (peak total plasma concentration of a drug at a certain dose) that is not bound to plasma proteins. The percentage of the bound drug is determined separately and the Cmax is corrected accordingly.


The half maximal inhibitory concentration, or the concentration of an inhibitor that is required for 50% inhibition of the maximum control response in a biochemical or cellular assay.

K i

Inhibition constant; can be derived from the IC50 (half maximal inhibitory concentration) if the concentration of ligand or substrate and its dissociation or Michaelis constant is known. Should be used in preference to IC50 for binding assays.

Safety margins

Ratios of an AC50 (concentration required to elicit a 50% response in an in vitro assay) — or the inhibition constant Ki — of a drug at a target known to mediate specific adverse drug reactions (ADRs) and the therapeutic free plasma concentration. The latter can be directly determined in preclinical or clinical studies, or estimated from models. The AC50 is taken from the most relevant assay available for that target. Safety margins should be used as early as possible in the preclinical phase to continually assess the risk of an ADR occurring in the clinic.


The ratio of the AC50 (concentration required to elicit a 50% response in an in vitro assay) — or the inhibition constant Ki if available — of a drug at any target that is known or suspected to mediate an adverse drug reaction, and the primary (therapeutic) target.

Therapeutic free plasma concentration

The concentration of a compound in the plasma following a therapeutic dose. Often quoted as the maximum exposure.

Therapeutic index

In a drug development setting: the quantitative ratio of the exposure level at the chosen safety end point divided by the exposure level at the chosen efficacy end point, typically the ratio of the highest exposure to the drug that results in no toxicity over that which produces the desired efficacy. This term is often used incorrectly to describe the safety margin.

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Bowes, J., Brown, A., Hamon, J. et al. Reducing safety-related drug attrition: the use of in vitro pharmacological profiling. Nat Rev Drug Discov 11, 909–922 (2012).

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