Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

Bayesian approaches in drug development: continuing the virtuous cycle

Nature Reviews Drug Discovery volume 23, pages 962–963 (2024)Cite this article

Subjects

Access through your institution
Buy or subscribe

Ruberg et al. recently published an article with the aim of starting a virtuous cycle in the use of Bayesian approaches in drug development (Nat. Rev. Drug Discov. 22, 235–250; 2023)1. Here, we would like to extend important arguments of their article and add recommendations for using Bayesian statistics2.

The authors emphasize the fundamental distinctions between frequentist and Bayesian approaches1. However, we would also like to highlight the similarities between both perspectives. First, Bayesian and (likelihood-based) frequentist approaches will converge towards identical results as more data are collected, because the likelihood based on the observed data will dominate the model. Second, both approaches will give similar if not identical results if a non-informative prior distribution is used. Moreover, a frequentist one-sided p-value can indeed be interpreted as the probability that the null hypothesis is true in this situation because the p-value will be equal to the corresponding posterior predictive probability3. Awareness of these similarities may help to bridge both statistical schools of thought and to resolve regulatory concerns around the use of Bayesian approaches that may be less familiar than frequentist approaches to some researchers.

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

References

  1. Ruberg, S. J. et al. Application of Bayesian approaches in drug development: starting a virtuous cycle. Nat. Rev. Drug Discov. 22, 235–250 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Igl, W. & Constant, J. Hype, not hope – A comment on Ruberg et al. (2023) “Application of Bayesian approaches in drug development: starting a virtuous cycle”. (2023); https://wilmarigl.de/?p=689.

  3. Shi, H. & Yin, G. Reconnecting p-value and posterior probability under one- and two-sided tests. Am. Stat. 75, 265–275 (2021).

    Article  Google Scholar 

  4. Moler, F. W. et al. Therapeutic hypothermia after out-of-hospital cardiac arrest in children. N. Engl. J. Med. 372, 1898–1908 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Harhay, M. O. et al. A Bayesian interpretation of a pediatric cardiac arrest trial (THAPCA-OH). N. Engl. J. Med. Evid. 2, EVIDoa2200196 (2022).

    Google Scholar 

  6. Dias, S., Sutton, A. J., Welton, N. J. & Ades, A. E. NICE DSU Technical Support Document 3: Heterogeneity: Subgroups, Meta-Regression, Bias and Bias-Adjustment (Decision Support Unit, ScHARR, University of Sheffield, 2011); https://www.ncbi.nlm.nih.gov/books/NBK395886/pdf/Bookshelf_NBK395886.pdf.

  7. IntHout, J., Ioannidis, J. P. A., Rovers, M. M. & Goeman, J. J. Plea for routinely presenting prediction intervals in meta-analysis. BMJ Open 6, e010247 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biostatistics Consulting Services, ICON PLC, Uppsala, Sweden

    Wilmar Igl

  2. Scientific Affairs, ICON PLC, Vancouver, Canada

    John Constant

Authors
  1. Wilmar Igl
    View author publications

    Search author on:PubMed Google Scholar

  2. John Constant
    View author publications

    Search author on:PubMed Google Scholar

Contributions

W.I. drafted the first version of this article and acted as the corresponding author. J.C. provided revisions that substantially improved the article.

Corresponding author

Correspondence to Wilmar Igl.

Ethics declarations

Competing interests

The authors are both employees of ICON PLC; however, they are not aware of any competing interests.

Peer review

Peer review information

Nature Reviews Drug Discovery thanks Benjamin Saville, Philip Pallmann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Igl, W., Constant, J. Bayesian approaches in drug development: continuing the virtuous cycle. Nat Rev Drug Discov 23, 962–963 (2024). https://doi.org/10.1038/s41573-024-01052-w

Download citation

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41573-024-01052-w

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing