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  • From the Analyst's Couch
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R&D productivity: on the comeback trail

Nature Reviews Drug Discovery volume 13, pages 331–332 (2014)Cite this article

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First, in our view, the definition of approvals should be focused on all therapeutic advances approved by the FDA, not just those assessed and approved by the FDA's Center for Drug Evaluation and Research. Importantly, we exclude non-therapeutics such as diagnostic imaging agents, but we include other, often very significant and valued, therapeutic agents such as bioengineered vaccines, combination products, enantiomers, prodrugs and therapeutic blood and plasma products. We define this basket of relevant innovation as new therapeutic drugs (NTDs); see Supplementary information S1 (box) for details.

Second, although the number of approvals is a definitive and non-controversial metric, it is unrepresentative of what really matters for the commercial stability of the industry: namely, the value of approvals. In the analysis presented here, we have analysed the output of the industry in terms of peak sales of NTDs; notwithstanding that revenue profiles for drugs are never the same, we consider that peak sales represent an effective proxy for attributing value to an approval, and they can be effectively used from an outside-in perspective to compare productivity. Peak sales for earlier approvals (typically pre-2002) are actual peak sales that were achieved, whereas later approvals are progressively a forecast — based on consensus analyst projections — of peak sales. Although this approach introduces an element of uncertainty into the analysis of recent-year approvals, we are confident that, if anything, the reliance on forecast peak sales has the potential to underestimate subsequent actual peak sales, as Boston Consulting Group (BCG) proprietary analysis indicates that forecasts for blockbusters, at an aggregate level, tend to be initially underestimated.

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Figure 1: Number and aggregate peak sales value of new therapeutic drugs by year of FDA approval.
Figure 2: R&D productivity data.

References

  1. Tollman, P. et al. Identifying R&D outliers. Nature Rev. Drug Discov. 10, 653–654 (2011).

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  2. Ringel, M. et al. Does size matter in R&D productivity? If not, what does? Nature Rev. Drug Discov. 12, 901–902 (2013).

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Author information

Authors and Affiliations

  1. The Boston Consulting Group, Münstergasse 2, Zürich, 8001, Switzerland

    Ulrik Schulze & David Greber

  2. The Boston Consulting Group, Ludwigstraße 21, München, 80539, Germany

    Mathias Baedeker

  3. The Boston Consulting Group, The New Otani Garden Court, 4–1, Kioi-cho, Chiyoda-ku, Tokyo, 102–0094, Japan

    Yen Ting Chen

Authors
  1. Ulrik Schulze
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  2. Mathias Baedeker
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  3. Yen Ting Chen
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  4. David Greber
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Corresponding author

Correspondence to Ulrik Schulze.

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Competing interests

The authors of this article are employees of The Boston Consulting Group (BCG), a management consultancy that works with the world's leading biopharmaceutical companies on R&D productivity issues. The research for this specific article was funded by BCG's Health Care practice.

Supplementary information

Supplementary information S1 (box)

Data and analysis (PDF 70 kb)

Supplementary information S2 (figure)

Aggregate industry spending on research and development. (PDF 202 kb)

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Schulze, U., Baedeker, M., Chen, Y. et al. R&D productivity: on the comeback trail. Nat Rev Drug Discov 13, 331–332 (2014). https://doi.org/10.1038/nrd4320

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