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

35 Pages Posted: 18 May 2020 Last revised: 6 Nov 2021

See all articles by Shomesh Chaudhuri

Shomesh Chaudhuri

Massachusetts Institute of Technology

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering; Santa Fe Institute

Danying Xiao

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Qingyang Xu

Massachusetts Institute of Technology (MIT) - Operations Research Center

Date Written: May 2020

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 R0 – 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 R0 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

Chaudhuri, Shomesh and Lo, Andrew W. and Xiao, Danying and Xu, Qingyang, Bayesian Adaptive Clinical Trials for Anti‐Infective Therapeutics During Epidemic Outbreaks (May 2020). NBER Working Paper No. w27175, Available at SSRN: https://ssrn.com/abstract=3603805

Shomesh Chaudhuri (Contact Author)

Massachusetts Institute of Technology ( email )

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Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering ( email )

100 Main Street
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Cambridge, MA 02142
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781 891-9783 (Fax)

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Santa Fe Institute

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Santa Fe, NM 87501
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Danying Xiao

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
Cambridge, MA 02142
United States

Qingyang Xu

Massachusetts Institute of Technology (MIT) - Operations Research Center ( email )

77 Massachusetts Avenue
Bldg. E 40-149
Cambridge, MA 02139
United States

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