IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/27175.html
   My bibliography  Save this paper

Bayesian Adaptive Clinical Trials for Anti‐Infective Therapeutics during Epidemic Outbreaks

Author

Listed:
  • Shomesh Chaudhuri
  • Andrew W. Lo
  • Danying Xiao
  • Qingyang Xu

Abstract

In the midst of epidemics such as COVID-19, therapeutic candidates are unlikely to be able to complete the usual multiyear clinical trial and regulatory approval process within the course of an outbreak. We apply a Bayesian adaptive patient-centered model—which minimizes the expected harm of false positives and false negatives—to optimize the clinical trial development path during such outbreaks. When the epidemic is more infectious and fatal, the Bayesian-optimal sample size in the clinical trial is lower and the optimal statistical significance level is higher. For COVID-19 (assuming a static R ₀ – 2 and initial infection percentage of 0.1%), the optimal significance level is 7.1% for a clinical trial of a nonvaccine anti-infective therapeutic and 13.6% for that of a vaccine. For a dynamic R ₀ decreasing from 3 to 1.5, the corresponding values are 14.4% and 26.4%, respectively. Our results illustrate the importance of adapting the clinical trial design and the regulatory approval process to the specific parameters and stage of the epidemic.

Suggested Citation

  • Shomesh Chaudhuri & Andrew W. Lo & Danying Xiao & Qingyang Xu, 2020. "Bayesian Adaptive Clinical Trials for Anti‐Infective Therapeutics during Epidemic Outbreaks," NBER Working Papers 27175, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:27175
    Note: AP EH
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w27175.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Isakov, Leah & Lo, Andrew W. & Montazerhodjat, Vahid, 2019. "Is the FDA too conservative or too aggressive?: A Bayesian decision analysis of clinical trial design," Journal of Econometrics, Elsevier, vol. 211(1), pages 117-136.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shomesh E. Chaudhuri & Phillip Adamson & Dean Bruhn-Ding & Zied Ben Chaouch & David Gebben & Liliana Rincon-Gonzalez & Barry Liden & Shelby D. Reed & Anindita Saha & Daniel Schaber & Kenneth Stein & M, 2023. "Patient-Centered Clinical Trial Design for Heart Failure Devices via Bayesian Decision Analysis," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 16(4), pages 359-369, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Steven Glazerman & Ira Nichols-Barrer & Jon Valant & Alyson Burnett, "undated". "Presenting School Choice Information to Parents: An Evidence-Based Guide, Appendix," Mathematica Policy Research Reports d418c5d8768d4ed8ade319330, Mathematica Policy Research.
    2. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    3. Stacy Sneeringer & Matt Clancy, 2020. "Incentivizing New Veterinary Pharmaceutical Products to Combat Antibiotic Resistance," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(4), pages 653-673, December.
    4. Clancy, Matthew S. & Sneeringer, Stacy E., 2018. "How Much Does it Cost to Induce R&D in Animal Health?," 2018 Annual Meeting, August 5-7, Washington, D.C. 273865, Agricultural and Applied Economics Association.
    5. Erin R. Lipman & John Deke & Mariel M. Finucane, 2022. "Bayesian Interpretation Of Cluster‐Robust Subgroup Impact Estimates: The Best Of Both Worlds," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(4), pages 1204-1224, September.
    6. Donald A. Berry & Scott Berry & Peter Hale & Leah Isakov & Andrew W. Lo & Kien Wei Siah & Chi Heem Wong, 2020. "A Cost/Benefit Analysis of Clinical Trial Designs for COVID-19 Vaccine Candidates," NBER Working Papers 27882, National Bureau of Economic Research, Inc.
    7. David J. Hebert & Michael D. Curry, 2022. "Optimal lockdowns," Public Choice, Springer, vol. 193(3), pages 263-274, December.
    8. Raymond J. March, 2021. "The FDA and the COVID‐19: A political economy perspective," Southern Economic Journal, John Wiley & Sons, vol. 87(4), pages 1210-1228, April.
    9. Casey B. Mulligan, 2021. "Peltzman Revisited: Quantifying 21st Century Opportunity Costs of FDA Regulation," NBER Working Papers 29574, National Bureau of Economic Research, Inc.
    10. Thijssen, Jacco J.J. & Bregantini, Daniele, 2017. "Costly sequential experimentation and project valuation with an application to health technology assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 202-229.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I1 - Health, Education, and Welfare - - Health
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:27175. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.