Analysis | Published:

How to improve R&D productivity: the pharmaceutical industry's grand challenge

Nature Reviews Drug Discovery volume 9, pages 203214 (2010) | Download Citation

Abstract

The pharmaceutical industry is under growing pressure from a range of environmental issues, including major losses of revenue owing to patent expirations, increasingly cost-constrained healthcare systems and more demanding regulatory requirements. In our view, the key to tackling the challenges such issues pose to both the future viability of the pharmaceutical industry and advances in healthcare is to substantially increase the number and quality of innovative, cost-effective new medicines, without incurring unsustainable R&D costs. However, it is widely acknowledged that trends in industry R&D productivity have been moving in the opposite direction for a number of years. Here, we present a detailed analysis based on comprehensive, recent, industry-wide data to identify the relative contributions of each of the steps in the drug discovery and development process to overall R&D productivity. We then propose specific strategies that could have the most substantial impact in improving R&D productivity.

Key points

  • The biopharmaceutical industry is facing unprecedented challenges to its fundamental business model and currently cannot sustain sufficient innovation to replace its products and revenues lost due to patent expirations.

  • The number of truly innovative new medicines approved by regulatory agencies such as the US Food and Drug Administration has declined substantially despite continued increases in R&D spending, raising the current cost of each new molecular entity (NME) to approximately US$1.8 billion

  • Declining R&D productivity is arguably the most important challenge the industry faces and thus improving R&D productivity is its most important priority.

  • A detailed analysis of the key elements that determine overall R&D productivity and the cost to successfully develop an NME reveals exactly where (and to what degree) R&D productivity can (and must) be improved.

  • Reducing late-stage (Phase II and III) attrition rates and cycle times during drug development are among the key requirements for improving R&D productivity.

  • To achieve the necessary increase in R&D productivity, R&D investments, both financial and intellectual, must be focused on the 'sweet spot' of drug discovery and early clinical development, from target selection to clinical proof-of-concept.

  • The transformation from a traditional biopharmaceutical FIPCo (fully integrated pharmaceutical company) to a FIPNet (fully integrated pharmaceutical network) should allow a given R&D organization to 'play bigger than its size' and to more affordably fund the necessary number and quality of pipeline assets.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    & Bringing pharma R.&D back to health. Bain Brief [], (2009).

  2. 2.

    , & Waking the giant: business model innovation in the drug industry. In Vivo 26, 1–6 (2008).

  3. 3.

    Rebuilding the R.&D engine in big pharma. Harvard Bus. Rev. 86, 68–76 (2008). A candid assessment by the former CEO of GlaxoSmithKline of the downsides of the industry's process culture.

  4. 4.

    The Truth about Drug Companies: How They Deceive Us and What to do About It. (Random House Trade Paperbacks, New York, 2005).

  5. 5.

    Trends in pharmaceutical portfolio management: strategies to maintain profitability despite adversity. Datamonitor [] (2008).

  6. 6.

    , & Prescription drug spending trends in the United States: looking beyond the turning point. Health Affairs w151–w160, (2008).

  7. 7.

    EvaluatePharma Alpha World Preview 2014. Evaluate Pharma report (2009).

  8. 8.

    Market watch: Pharma industry performance metrics: 2007–2012E. Nature Rev. Drug Discov. 7, 795 (2008).

  9. 9.

    , ed. Parexel's Bio/Pharmaceutical R&D Statistical Sourcebook 2008/2009. (Parexel International Corporation, Waltham, 2008).

  10. 10.

    Science Business: the Promise, the Reality, and the Future of Biotech. (Harvard Business School Press, Boston, 2006). An insightful retrospective on the biotech industry, and the reasons why it has not yet lived up to its promises.

  11. 11.

    & The cost of biopharmaceutical R&D: Is biotech different? Manage. Decis. Econ. 28, 469–479 (2007). A contemporary assessment of the costs to discover, develop and launch new molecular entities.

  12. 12.

    The state of innovation in drug development. Clin. Pharmacol. Ther. 83, 227–230 (2008).

  13. 13.

    Macro trends in pharmaceutical innovation. Nature Rev. Drug Discov. 4, 78–84 (2005).

  14. 14.

    The impact of new drug launches on longevity: evidence from longitudinal, disease-level data from 52 countries, 1982–2001 Int. J. Health Care Finance Econ. 5, 47–43 (2005).

  15. 15.

    , , , & Obesity, diabetes damage young arteries, could shorten life. News release, American Heart Association website [] (2009).

  16. 16.

    KMR Group. Pharmaceutical Benchmarking Forum [] (2009).

  17. 17.

    & Prospects for productivity. Nature Rev. Drug Discov. 3, 451–456 (2004). Booth and Zemmil framed the issue of productivity in the pharmaceutical industry and provide a qualitative discussion of some of the drivers and potential solutions.

  18. 18.

    , , & The innovation gap in pharmaceutical drug discovery & new models for R&D success. [], (2007).

  19. 19.

    & Can the pharmaceutical industry reduce attrition rates? Nature Rev. Drug Discov. 3, 711–715 (2004). This article provides an in-depth analysis of attrition by phase and therapy area, and offers a scientific approach to reduce Phase II and Phase III attrition rates.

  20. 20.

    Innovation or Stagnation? Challenge and Opportunity on the Critical Path to New Medical Products[], (2004). A seminal paper on the hurdles that must be overcome to reverse the decline in R&D productivity.

  21. 21.

    Driving earlier clinical attrition: if you want to find the needle, burn down the haystack. Considerations for biomarker development. Drug Discov. Today 12, 289–294 (2007).

  22. 22.

    A proof of the queuing formula L = λ W. Oper. Res. 9, 383–387 (1961).

  23. 23.

    & Modeling resource requirements for pharmaceutical R.&D. Res. Technol. Manage. 45, 48–56 (2002).

  24. 24.

    Deloitte Touche Tohmatsu. Threading the talent needle: what global executives are saying about people and work. [], (2009).

  25. 25.

    PricewaterhouseCoopers. The changing dynamics of pharma outsourcing in Asia: are you readjusting your sights? [], (2008).

  26. 26.

    , & Productivity in pharmaceutical-biotechnology R&D: the role of experience and alliances. J. Health Econ. 24, 317–339 (2005).

  27. 27.

    , , & Pricing medicines: theory and practice, challenges and opportunities. Nature Rev. Drug Discov. 4, 121–130 (2005).

  28. 28.

    The prospects for “personalized medicine” in drug development and drug therapy. Clin. Pharmacol. Ther. 1, 164–169 (2007).

  29. 29.

    The value of improving the productivity of the drug development process: faster times and better decisions. Pharmacoeconomics 20, 1–10 (2002).

  30. 30.

    The Six Sigma Handbook: The complete guide for greenbelts, blackbelts, and managers of all levels. 2nd revised edition (McGraw-Hill, New York, 2003).

  31. 31.

    & The goal: a process of ongoing improvement. Third edition. (Gower Publishing, Aldershot, 2004).

  32. 32.

    , , Dragalin, V, Gallo, P, Adaptive seamless phase II/III designs—background, operational aspects, and examples. Drug Inf. J. 4, 463–473 (2006).

  33. 33.

    , & The application of discovery toxicology and pathology towards the design of safer pharmaceutical lead candidates. Nature Rev. Drug Discov. 6, 636–649 (2007).

  34. 34.

    & The druggable genome. Nature Rev. Drug Discov. 1, 727–730 (2002).

  35. 35.

    Significance of the human genome sequence to drug discovery. Pharmacogenomics J. 1, 11–12 (2001).

  36. 36.

    , & PCSK9: a convertase that coordinates LDL catabolism. J. Lipid Res. S172–S177 (2009).

  37. 37.

    et al. Mutations in PCSK9 cause autosomal dominant hypercholesterolemia. Nature Genet. 34, 154–156 (2003).

  38. 38.

    , , & Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N. Engl. J. Med. 354, 1264–1272 (2006).

  39. 39.

    , , & Further LDL cholesterol lowering through targeting PCSK9 for coronary artery disease. Endocrine, Metabolic & Immune Disorders – Drug Targets. 8, 238–243 (2008).

  40. 40.

    et al. A proprotein convertase subtilisin/kexin type 9 neutralizing antibody reduces serum cholesterol in mice and nonhuman primates. Proc. Natl Acad. Sci. USA 106, 9820–9825 (2009).

  41. 41.

    et al. Effect of lowering LDL cholesterol substantially below currently recommended levels in patients with coronary heart disease and diabetes. Diabetes Care 29, 1220–1226 (2006).

  42. 42.

    & Mutations in sodium-channel gene SCN9A cause a spectrum of human genetic pain disorders. J. Clin. Invest. 117, 3603–3609 (2007).

  43. 43.

    & Sodium channels and nociception: recent concepts and therapeutic opportunities. Curr. Opin. Pharmacol. 8, 50–56 (2008).

  44. 44.

    , & A more rational approach to new-product development. Harvard Bus. Rev. 86, 96–102 (2008). A review of Eli Lilly's Chorus model of early drug development and FIPNet strategy.

  45. 45.

    Drug discovery in jeopardy. J. Clin. Invest. 116, 2837–2842 (2006). A frank analysis by one of the most successful R&D leaders of problems that have fostered the current innovation crisis.

Download references

Acknowledgements

The authors wish to acknowledge the seminal thought leadership on the issue of R&D productivity that A. Bingham has provided to the pharmaceutical industry. In addition, we wish to thank J.S. Andersen and T. Mason for helping frame the productivity concepts expressed in this manuscript, and G. Pisano and J. DiMasi for helpful suggestions and comments.

Author information

Affiliations

  1. Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana 46285, USA.

    • Steven M. Paul
    • , Daniel S. Mytelka
    • , Christopher T. Dunwiddie
    • , Charles C. Persinger
    • , Bernard H. Munos
    • , Stacy R. Lindborg
    •  & Aaron L. Schacht

Authors

  1. Search for Steven M. Paul in:

  2. Search for Daniel S. Mytelka in:

  3. Search for Christopher T. Dunwiddie in:

  4. Search for Charles C. Persinger in:

  5. Search for Bernard H. Munos in:

  6. Search for Stacy R. Lindborg in:

  7. Search for Aaron L. Schacht in:

Competing interests

All authors are employees and shareholders of Eli lilly and company.

Corresponding author

Correspondence to Steven M. Paul.

Supplementary information

PDF files

  1. 1.

    Supplementary information S1 (box)

    What is R&D productivity?

  2. 2.

    Supplementary information S2 (box)

    R&D productivity model and cost of drug development estimates

  3. 3.

    Supplementary information S3 (box)

    The Pharmaceutical Benchmarking Forum

Glossary

New molecular entity

(NME). A medication containing an active ingredient that has not been previously approved for marketing in any form in the United States. NME is conventionally used to refer only to small-molecule drugs, but in this article we use the term as a shorthand to refer to both new chemical entities and new biologic entities.

Capitalized cost

This is the out-of-pocket cost corrected for cost of capital, and is the standard accounting treatment for long-term investments. It recognizes the fact that investors require a return on research investments that reflects alternative potential uses of their investment. So, the capitalized cost per drug launch increases out-of-pocket costs by the cost of capital for every year from expenditure to launch.

Out-of-pocket cost

This is the total cost required to expect one drug launch, taking into account attrition, but not the cost of capital.

Cost of capital

This is the annual rate of return expected by investors based on the level of risk of the investment.

Imatinib and trastuzumab

Imatinib blocks the activity of BCR–ABL, a deregulated tyrosine kinase that results from a chromosomal translocation in patients with chronic myelogenous leukaemia, and trastuzumab blocks the activity of HER2/neu, a receptor tyrosine kinase that is often overexpressed in patients with breast cancer. Patients that are most likely to benefit from each drug can be readily identified before initiating treatment on the basis of the associated biomarkers, which has been invaluable in the development of both drugs and in guiding their use.

Six Sigma

A quality management tool that is used to improve the quality of manufacturing and business processes by first identifying and removing the causes of errors or defects, as well as by minimizing variability.

Chorus

A virtual approach to drug development that is primarily focused on establishing early proof-of-concept in humans (ideally in Phase I) to reduce attrition at later stages. Chorus cost estimate quoted in the text was calculated including the direct and indirect costs for 21 molecules in the Chorus portfolio from 2005–2008 and one from 2004.

About this article

Publication history

Published

DOI

https://doi.org/10.1038/nrd3078

Further reading