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The discovery of first-in-class drugs: origins and evolution

Key Points

  • Here, we present an analysis of the origins of all 113 first-in-class drugs approved by the US Food and Drug Administration (FDA) from 1999 to 2013, which shows that the majority (78) of these drugs were discovered through target-based approaches (45 small-molecule drugs and 33 biologics).

  • Only eight of the 33 drugs identified in the absence of a target hypothesis were found by what we define here as 'phenotypic screening': the testing of a large number of compounds in a target-agnostic assay that monitors phenotypic changes. The discovery of the other 25 non-target-based drugs occurred through a chemocentric approach in which compounds with known pharmacology served as the starting point.

  • The median time from first disclosure of the concept (target, pathway or chemotype) to FDA approval was 25 years for non-target-based drugs and 20 years for target-based drugs. All but four of the non-target-based drugs had their origins before 1985, the time around which the technologies necessary for target-based approaches were introduced.

  • We conclude that target-based drug discovery is successful and recognize that high-throughput screening and other innovations applied in the past 25 years have only recently started to have a major impact on new approvals. We further suggest viewing phenotypic screening as a logical evolution of target-based approaches and consider it a novel discipline rather than a neoclassical approach.


Analysis of the origins of new drugs approved by the US Food and Drug Administration (FDA) from 1999 to 2008 suggested that phenotypic screening strategies had been more productive than target-based approaches in the discovery of first-in-class small-molecule drugs. However, given the relatively recent introduction of target-based approaches in the context of the long time frames of drug development, their full impact might not yet have become apparent. Here, we present an analysis of the origins of all 113 first-in-class drugs approved by the FDA from 1999 to 2013, which shows that the majority (78) were discovered through target-based approaches (45 small-molecule drugs and 33 biologics). In addition, of 33 drugs identified in the absence of a target hypothesis, 25 were found through a chemocentric approach in which compounds with known pharmacology served as the starting point, with only eight coming from what we define here as phenotypic screening: testing a large number of compounds in a target-agnostic assay that monitors phenotypic changes. We also discuss the implications for drug discovery strategies, including viewing phenotypic screening as a novel discipline rather than as a neoclassical approach.

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Figure 1: Discovery of first-in-class drugs approved by the FDA between 1999 and 2013.
Figure 2: Chronology of the discovery of first-in-class drugs approved between 1999 and 2003.
Figure 3: Chronology of the discovery of first-in-class drugs approved between 2004 and 2008.
Figure 4: Chronology of the discovery of first-in-class drugs approved between 2009 and 2013.
Figure 5: Distribution of first-in-class drugs according to the molecule type and target family.


  1. 1

    Drews, J. & Ryser, S. The role of innovation in drug development. Nature Biotech. 15, 1318–1319 (1997).

    CAS  Article  Google Scholar 

  2. 2

    Garnier, J. P. Rebuilding the R&D engine in big pharma. Harv. Bus. Rev. 86, 68–70 (2008).

    PubMed  Google Scholar 

  3. 3

    Douglas, F. L., Narayanan, V. K., Mitchell, L. & Litan, R. E. The case for entrepreneurship in R&D in the pharmaceutical industry. Nature Rev. Drug Discov. 9, 683–689 (2010).

    CAS  Article  Google Scholar 

  4. 4

    David, E., Tramontin, T. & Zemmel, R. Pharmaceutical R&D: the road to positive returns. Nature Rev. Drug Discov. 8, 609–610 (2009).

    CAS  Article  Google Scholar 

  5. 5

    Paul, S. M. et al. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nature Rev. Drug Discov. 9, 203–214 (2010).

    CAS  Article  Google Scholar 

  6. 6

    Kola, I. & Landis, J. Can the pharmaceutical industry reduce attrition rates? Nature Rev. Drug Discov. 3, 711–715 (2004).

    CAS  Article  Google Scholar 

  7. 7

    Ruffolo, R. R. Why has R&D productivity declined in the pharmaceutical industry? Expert Opin. Drug Discov. 1, 99–102 (2006).

    Article  Google Scholar 

  8. 8

    Scannell, J. W., Blanckley, A., Boldon, H. & Warrington, B. Diagnosing the decline in pharmaceutical R&D efficiency. Nature Rev. Drug Discov. 11, 191–200 (2012). This article discusses four factors as the primary causes of the decline in pharmaceutical R&D efficiency.

    CAS  Article  Google Scholar 

  9. 9

    Munos, B. Lessons from 60 years of pharmaceutical innovation. Nature Rev. Drug Discov. 8, 959–968 (2009).

    CAS  Article  Google Scholar 

  10. 10

    Horrobin, D. F. Realism in drug discovery — could Cassandra be right? Nature Biotech. 19, 1099–1100 (2001).

    CAS  Article  Google Scholar 

  11. 11

    Pammolli, F., Magazzini, L. & Riccaboni, M. The productivity crisis in pharmaceutical R&D. Nature Rev. Drug Discov. 10, 428–438 (2011).

    CAS  Article  Google Scholar 

  12. 12

    Swinney, D. C. & Anthony, J. How were new medicines discovered? Nature Rev. Drug Discov. 10, 507–519 (2011). This article analyses the origins of first-in-class drugs (FDA approvals from 1999 to 2008) and postulates that target-based drug discovery contributes to low productivity in pharmaceutical R&D.

    CAS  Article  Google Scholar 

  13. 13

    Butcher, E. C. Can cell systems biology rescue drug discovery? Nature Rev. Drug Discov. 4, 461–467 (2005).

    CAS  Article  Google Scholar 

  14. 14

    Hellerstein, M. K. A critique of the molecular target-based drug discovery paradigm based on principles of metabolic control: advantages of pathway-based discovery. Metab. Eng. 10, 1–9 (2008).

    CAS  Article  Google Scholar 

  15. 15

    Kell, D. B. Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it. FEBS J. 280, 5957–5980 (2013).

    CAS  Article  Google Scholar 

  16. 16

    Zheng, W., Thorne, N. & McKew, J. C. Phenotypic screens as a renewed approach for drug discovery. Drug Discov. Today 18, 1067–1073 (2013).

    CAS  Article  Google Scholar 

  17. 17

    Swinney, D. C. Phenotypic versus target-based drug discovery for first-in-class medicines. Clin. Pharmacol. Ther. 93, 299–301 (2013).

    CAS  Article  Google Scholar 

  18. 18

    Schrör, K. Acetylsalicylic Acid (Wiley, 2009).

    Google Scholar 

  19. 19

    Sneader, W. Drug Discovery: A History (Wiley, 2005).

    Google Scholar 

  20. 20

    Macarron, R. et al. Impact of high-throughput screening in biomedical research. Nature Rev. Drug Discov. 10, 188–195 (2011).

    CAS  Article  Google Scholar 

  21. 21

    Beck, A., Wurch, T., Bailly, C. & Corvaia, N. Strategies and challenges for the next generation of therapeutic antibodies. Nature Rev. Immunol. 10, 345–352 (2010).

    CAS  Article  Google Scholar 

  22. 22

    Algire, G. H. & Chalkley, H. W. Vascular reactions of normal and malignant tissues in vivo.1. Vascular reactions of mice to wounds and to normal and neoplastic transplants. J. Natl Cancer Inst. 6, 73–85 (1945).

    Article  Google Scholar 

  23. 23

    Greenblatt, M. & Shubk, P. Tumor angiogenesis — transfilter diffusion studies in hamster by transparent chamber technique. J. Natl Cancer Inst. 41, 111–124 (1968).

    CAS  PubMed  Google Scholar 

  24. 24

    Folkman, J. Tumor angiogenesis — therapeutic implications. N. Engl. J. Med. 285, 1182–1186 (1971).

    CAS  Article  Google Scholar 

  25. 25

    Senger, D. R. et al. Tumor cells secrete a vascular permeability factor that promotes accumulation of ascites fluid. Science 219, 983–985 (1983).

    CAS  Article  Google Scholar 

  26. 26

    Leung, D. W., Cachianes, G., Kuang, W. J., Goeddel, D. V. & Ferrara, N. Vascular endothelial growth factor is a secreted angiogenic mitogen. Science 246, 1306–1309 (1989).

    CAS  Article  Google Scholar 

  27. 27

    Presta, L. G. et al. Humanization of an anti-vascular endothelial growth factor monoclonal antibody for the therapy of solid tumors and other disorders. Cancer Res. 57, 4593–4599 (1997).

    CAS  PubMed  Google Scholar 

  28. 28

    Buchdunger, E. et al. Inhibition of the Abl protein-tyrosine kinase in vitro and in vivo by a 2-phenylaminopyrimidine derivative. Cancer Res. 56, 100–104 (1996).

    CAS  PubMed  Google Scholar 

  29. 29

    Nowell, P. C. & Hungerford, D. A minute chromosome in human chronic granulocytic leukemia. Science 132, 1497 (1960).

    Google Scholar 

  30. 30

    Rowley, J. D. New consistent chromosomal abnormality in chronic myelogenous leukemia identified by quinacrine fluorescence and Giemsa staining. Nature 243, 290–293 (1973).

    CAS  Article  Google Scholar 

  31. 31

    Shtivelman, E., Lifshitz, B., Gale, R. P. & Canaani, E. Fused transcript of abl and bcr genes in chronic myelogenous leukemia. Nature 315, 550–554 (1985).

    CAS  Article  Google Scholar 

  32. 32

    Burnett, D. A. et al. 2-Azetidinones as inhibitors of cholesterol absorption. J. Med. Chem. 37, 1733–1736 (1994).

    CAS  Article  Google Scholar 

  33. 33

    Hopkins, A. L. & Groom, C. R. The druggable genome. Nature Rev. Drug Discov. 1, 727–730 (2002).

    CAS  Article  Google Scholar 

  34. 34

    Lokey, R. S. Forward chemical genetics: progress and obstacles on the path to a new pharmacopoeia. Curr. Opin. Chem. Biol. 7, 91–96 (2003).

    CAS  Article  Google Scholar 

  35. 35

    Hall, S. E. Chemoproteomics-driven drug discovery: addressing high attrition rates. Drug Discov. Today 11, 495–502 (2006).

    CAS  Article  Google Scholar 

  36. 36

    Pruss, R. M. Phenotypic screening strategies for neurodegenerative diseases: a pathway to discover novel drug candidates and potential disease targets or mechanisms. CNS Neurol. Disord. Drug Targets 9, 693–700 (2010).

    CAS  Article  Google Scholar 

  37. 37

    St Onge, R., Schlecht, U., Scharfe, C. & Evangelista, M. Forward chemical genetics in yeast for discovery of chemical probes targeting metabolism. Molecules 17, 13098–13115 (2012).

    CAS  Article  Google Scholar 

  38. 38

    Heitman, J., Movva, N. R. & Hall, M. N. Targets for cell cycle arrest by the immunosuppressant rapamycin in yeast. Science 253, 905–909 (1991).

    CAS  Article  Google Scholar 

  39. 39

    Sams-Dodd, F. Is poor research the cause of the declining productivity of the pharmaceutical industry? An industry in need of a paradigm shift. Drug Discov. Today 18, 211–217 (2013). This paper discusses potential reasons for the high failure rate of target-based drug discovery and suggests changes to improve productivity.

    Article  Google Scholar 

  40. 40

    Lee, J. A. & Berg, E. L. Neoclassic drug discovery: the case for lead generation using phenotypic and functional approaches. J. Biomol. Screen. 18, 1143–1155 (2013).

    CAS  Article  Google Scholar 

  41. 41

    Carragher, N. O., Brunton, V. G. & Frame, M. C. Combining imaging and pathway profiling: an alternative approach to cancer drug discovery. Drug Discov. Today 17, 203–214 (2012).

    Article  Google Scholar 

  42. 42

    Lee, J. A., Uhlik, M. T., Moxham, C. M., Tomandl, D. & Sall, D. J. Modern phenotypic drug discovery is a viable, neoclassic pharma strategy. J. Med. Chem. 55, 4527–4538 (2012).

    CAS  Article  Google Scholar 

  43. 43

    Chatterjee, A. K. & Yeung, B. K. Back to the future: lessons learned in modern target-based and whole-cell lead optimization of antimalarials. Curr. Top. Med. Chem. 12, 473–483 (2012).

    CAS  Article  Google Scholar 

  44. 44

    Payne, D. J., Gwynn, M. N., Holmes, D. J. & Pompliano, D. L. Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nature Rev. Drug Discov. 6, 29–40 (2007).

    CAS  Article  Google Scholar 

  45. 45

    Fishman, M. C. & Porter, J. A. Pharmaceuticals: a new grammar for drug discovery. Nature 437, 491–493 (2005).

    CAS  Article  Google Scholar 

  46. 46

    Welch, E. M. et al. PTC124 targets genetic disorders caused by nonsense mutations. Nature 447, 87–91 (2007).

    CAS  Article  Google Scholar 

  47. 47

    Rottmann, M. et al. Spiroindolones, a potent compound class for the treatment of malaria. Science 329, 1175–1180 (2010).

    CAS  Article  Google Scholar 

  48. 48

    Butchbach, M. E. et al. Effects of 2,4-diaminoquinazoline derivatives on SMN expression and phenotype in a mouse model for spinal muscular atrophy. Hum. Mol. Genet. 19, 454–467 (2010).

    CAS  Article  Google Scholar 

  49. 49

    Chen, B. et al. Small molecule-mediated disruption of Wnt-dependent signaling in tissue regeneration and cancer. Nature Chem. Biol. 5, 100–107 (2009).

    CAS  Article  Google Scholar 

  50. 50

    Filippakopoulos, P. et al. Selective inhibition of BET bromodomains. Nature 468, 1067–1073 (2010).

    CAS  Article  Google Scholar 

  51. 51

    Gao, M. et al. Chemical genetics strategy identifies an HCV NS5A inhibitor with a potent clinical effect. Nature 465, 96–100 (2010). This paper describes the discovery of daclatasvir (BMS-790052) by phenotypic screening and further chemical optimization in the absence of target knowledge.

    CAS  Article  Google Scholar 

  52. 52

    Naylor, L. H. Reporter gene technology: the future looks bright. Biochem. Pharmacol. 58, 749–757 (1999).

    CAS  Article  Google Scholar 

  53. 53

    Chiba, T., Tsuchiya, T., Mori, R. & Shimokawa, I. Protein reporter bioassay systems for the phenotypic screening of candidate drugs: a mouse platform for anti-aging drug screening. Sensors 12, 1648–1656 (2012).

    CAS  Article  Google Scholar 

  54. 54

    Williams, M. Systems and integrative biology as alternative guises for pharmacology: prime time for an iPharm concept? Biochem. Pharmacol. 70, 1707–1716 (2005).

    CAS  Article  Google Scholar 

  55. 55

    Ogbourne, S. M. et al. Antitumor activity of 3-ingenyl angelate: plasma membrane and mitochondrial disruption and necrotic cell death. Cancer Res. 64, 2833–2839 (2004).

    CAS  Article  Google Scholar 

  56. 56

    Lock, E. A. et al. From toxicological problem to therapeutic use: the discovery of the mode of action of 2-(2-nitro-4-trifluoromethylbenzoyl)-1,3-cyclohexanedione (NTBC), its toxicology and development as a drug. J. Inherit. Metab. Dis. 21, 498–506 (1998).

    CAS  Article  Google Scholar 

  57. 57

    Coe, J. W. et al. Varenicline: an α4β2 nicotinic receptor partial agonist for smoking cessation. J. Med. Chem. 48, 3474–3477 (2005).

    CAS  Article  Google Scholar 

  58. 58

    Kessel, D., Hall, T. C. & Wodinsky, I. Transport and phosphorylation as factors in the antitumor action of cytosine arabinoside. Science 156, 1240–1241 (1967).

    CAS  Article  Google Scholar 

  59. 59

    Gudas, L. J., Ullman, B., Cohen, A. & Martin, D. W. Jr. Deoxyguanosine toxicity in a mouse T lymphoma: relationship to purine nucleoside phosphorylase-associated immune dysfunction. Cell 14, 531–538 (1978).

    CAS  Article  Google Scholar 

  60. 60

    Cohen, A., Lee, J. W. & Gelfand, E. W. Selective toxicity of deoxyguanosine and arabinosyl guanine for T-leukemic cells. Blood 61, 660–666 (1983).

    CAS  PubMed  Google Scholar 

  61. 61

    Lambe, C. U. et al. 2-amino-6-methoxypurine arabinoside: an agent for T-cell malignancies. Cancer Res. 55, 3352–3356 (1995).

    CAS  PubMed  Google Scholar 

  62. 62

    Katz, D. H., Marcelletti, J. F., Khalil, M. H., Pope, L. E. & Katz, L. R. Antiviral activity of 1-docosanol, an inhibitor of lipid-enveloped viruses including herpes simplex. Proc. Natl Acad. Sci. USA 88, 10825–10829 (1991).

    CAS  Article  Google Scholar 

  63. 63

    Szelenyi, I. Flupirtine, a re-discovered drug, revisited. Inflamm. Res. 62, 251–258 (2013).

    CAS  Article  Google Scholar 

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The authors are grateful to I. Jones for expert help in statistical analysis, and thank their colleagues at the Novartis Institutes for Biomedical Research for the stimulating discussions related to this work. The authors also thank M. C. Fishman for making valuable suggestions on the content and scope of the analysis, and U. Eder for important insights into general aspects of pharmaceutical research.

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Correspondence to Jörg Eder.

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All authors are employees of Novartis Pharma AG.

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Supplementary information S1 (table)

Characteristics and origins of first-in-class drugs approved by the US FDA: 1999–2013 (PDF 1759 kb)

Supplementary information S2 (box)

Approval times for target-based and systems-based first-in-class drugs: 1999–2013 (PDF 274 kb)

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First-in-class drugs

Drugs that modulate an as-yet unprecedented drug target or biological pathway.

Phenotypic screening

The testing of a large number of — in most cases randomly selected — compounds in a systems-based assay.

Target-based approaches

Hypothesis-based approaches that aim to manipulate a biological system bypharmacologically modulating a specific component or target (an enzyme, receptor, and so on).

Small-molecule drugs

Drugs with a low molecular mass (typically <1,000 Da); this includes synthetic drugs, natural products (or derivatives) and natural substances (or derivatives).

Systems-based approach

Hypothesis-agnostic assay or approach that monitors or is based on a phenotypic change in vitro or in vivo.

Chemocentric approaches

Drug discovery approaches based around a specific compound or compound class. Chemocentric approaches have made a substantial contribution both to drugs originating from systems-based approaches and to drugs originating from target-based approaches.

Natural substance (or derivative)

A chemical substance (or derivative thereof) produced by a living organism found in nature that usually has pharmacological or biological activity. For this article we arbitrarily excluded natural products from natural substances to keep the former as a separate class of compounds.


Defined here as all drugs approved under a biologics license application (BLA) by the US Food and Drug Administration (FDA); usually antibodies and other proteins.


A family of molecules that possess the same core structure or scaffold.

Natural product (or derivative)

Secondary metabolites (or derivatives thereof) that are extracted from tissues of plants, marine organisms or microorganism fermentation broths.


The steric and electronic features of a ligand that are necessary to ensure optimal interactions with a biological target structure and to trigger (or to block) its biological response.

Low-molecular-mass synthetic drug

Low-molecular-mass drugs that are not derived from natural products or natural substances.

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Eder, J., Sedrani, R. & Wiesmann, C. The discovery of first-in-class drugs: origins and evolution. Nat Rev Drug Discov 13, 577–587 (2014).

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