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Awareness and use of quantitative decision-making methods in pharmaceutical development

Author

Listed:
  • Guido Thommes
  • Martin Oliver Sailer
  • Nicolas Bonnet
  • Alex Carlton
  • Juan J. Abellan
  • Veronique Robert

Abstract

The pharmaceutical industry has experienced increasing costs and sustained high attrition rates in drug development over the last years. One proposal that addresses this challenge from a statistical perspective is the use of quantitative decision-making (QDM) methods to support a data-driven, objective appraisal of the evidence that forms the basis of decisions at different development levels. Growing awareness among statistical leaders in the industry has led to the creation of the European EFSPI/PSI special interest group (ESIG) on quantitative decision making to share experiences, collect best practices, and promote the use of QDM. In this paper, we introduce key components of QDM and present examples of QDM methods on trial, program, and portfolio level. The ESIG created a questionnaire to learn how and to what extent QDM methods are currently used in the different development phases. We present the main questionnaire findings, and we show where QDM is already used today but also where areas for future improvement can be identified. In particular, statisticians should increase their visibility, involvement, and leadership in cross-functional decision-making.

Suggested Citation

  • Guido Thommes & Martin Oliver Sailer & Nicolas Bonnet & Alex Carlton & Juan J. Abellan & Veronique Robert, 2022. "Awareness and use of quantitative decision-making methods in pharmaceutical development," Papers 2203.00684, arXiv.org.
    • Handle: RePEc:arx:papers:2203.00684
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    References listed on IDEAS

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    1. DiMasi, Joseph A. & Grabowski, Henry G. & Hansen, Ronald W., 2016. "Innovation in the pharmaceutical industry: New estimates of R&D costs," Journal of Health Economics, Elsevier, vol. 47(C), pages 20-33.
    2. Nitin R. Patel & Suresh Ankolekar, 2015. "Dynamically Optimizing Budget Allocation for Phase 3 Drug Development Portfolios Incorporating Uncertainty in the Pipeline," Springer Books, in: Zoran Antonijevic (ed.), Optimization of Pharmaceutical R&D Programs and Portfolios, edition 127, chapter 0, pages 181-200, Springer.
    3. Eric W. Gibson, 2019. "Leadership in Statistics: Increasing Our Value and Visibility," The American Statistician, Taylor & Francis Journals, vol. 73(2), pages 109-116, April.
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