Reproducibility probability in clinical trials

TLDR

FDA approval requires substantial evidence from at least two well‑controlled trials, though the 1997 Modernization Act permits a single trial with confirmatory evidence in certain cases. The study aims to assess whether results from the first trial are reproducible in a second trial and to introduce reproducibility probability as a metric for regulatory decision‑making and sample‑size planning. We evaluate reproducibility probability using three methods—estimated power, confidence‑bound, and Bayesian approaches—across common clinical‑trial designs.

Abstract

For marketing approval of a new drug product, the United States Food and Drug Administration (FDA) requires that substantial evidence of the effectiveness of the drug product be provided through the conduct of at least two adequate and well-controlled clinical trials. The purpose of conducting the second clinical trial is to study whether the clinical result from the first trial is reproducible in the second trial with the same study protocol. Under certain circumstance, the FDA Modernization Act of 1997 includes a provision to allow data from one adequate and well-controlled clinical trial investigation and confirmatory evidence to establish effectiveness for risk/benefit assessment of drug and biological candidates for approval. In this paper, we introduce the concept of reproducibility probability for a given clinical trial, which is useful in providing important information for regulatory agencies in deciding whether a single clinical trial is sufficient and for pharmaceutical companies in adjusting the sample size in a future clinical trial. Three approaches, the estimated power approach, the method of confidence bounds and the Bayesian approach, are studied in evaluating reproducibility probabilities under several study designs commonly used in clinical trials.