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Reviewing recent FDA approvals, you may be struck by the total absence of odds ratios. Browsing the labels from the 2023 novel approvals, you can find proportions, differences in proportions, Chi-Squared analyses, CMH and variants, but logistic regression and odds ratios have practically disappeared from labeling. What gives?

FDA’s Benefit-Risk Framework is the presentation for communicating the assessment of the benefits and risks based on the therapeutic context, available evidence and uncertainties for the product in development.

Study sites have a tremendous influence on how, when, and where clinical trials take place. They’re the ones training personnel, allocating staff, enrolling participants, managing paperwork, and so much more. So it makes sense that when sponsors need to make important decisions—like which CRO to choose—sites will most certainly have an opinion.

To those of us who regularly create or review adverse event (AE) incidence tables for randomized controlled trials, it may come as a surprise that your typical AE incidence table can be misleading if data was combined from more than one trial. This is due to “Simpson’s paradox,” which, simply put, is the phenomenon that the mere grouping of data can introduce confounding or bias otherwise not present.

Biometrics teams can generate hundreds, if not thousands, of SAS programs throughout the drug development process. So how do you know which ones to submit to the FDA? And how do you go about submitting the programs?

As statisticians, we’re frequently asked to do power and sample size calculations from very thin data. Often, we’re given nothing but an ancient publication containing a few p-values, an occasional mean, and maybe a standard deviation (if we’re lucky). Back calculating something meaningful in these situations can seem intimidating, but it turns out that most standard sample size software can do the work for us when used unconventionally. We’ve outlined 2 such unconventional uses.

Innovation in early-stage studies presents the best opportunity to streamline the drug development process. Such designs may not only reduce costs and accelerate timelines but give us better flexibility to address the questions of interest in an increasingly evolving clinical development landscape.

The new European Union (EU) legislation regulating clinical trials harmonises the processes for assessment and supervision of clinical trials throughout the EU. It enables sponsors to submit 1 online application via a single platform (CTIS) for approval to run a clinical trial in several European countries, making the conduct of such multinational trials more efficient.

In the dynamic landscape of pharmaceuticals, obtaining a centralised marketing authorisation in the European Union (EU) is a crucial step for companies looking to bring their medicines to a broad market. The European Medicines Agency (EMA) is responsible for the scientific evaluation of applications for centralised marketing authorizations in the EU, offering a streamlined process that enables companies to submit a single marketing authorisation application (MAA) and to market their products across the entire European Economic Area (EEA), which includes the EU countries, Iceland, Norway and Liechtenstein, based on a single authorisation.

When running a randomized clinical trial, if there are factors which are known during the study design phase to influence study results, it may be advantageous to utilize a stratified randomization which ensures each prognostic factor is balanced between treatment arms.