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Blog Post
Overcoming statistical challenges in rare disease drug development
Regulatory agencies like the FDA require substantial evidence of the drug’s effectiveness for its intended use and sufficient information to conclude that the drug is safe. However, flexibility is given in how the standard can be met given the challenges associated with the limited number of subjects available in rare disease.
Blog Post
Where did the odds ratios go?
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?
Blog Post
FDA’s Benefit-Risk Framework for NDAs and BLAs: The Presentation
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.
Blog Post
Study-Size Adjusted Percentages in Integrated Adverse Event Displays
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.
Blog Post
Submitting SAS Programs to FDA
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?
Blog Post
How to estimate the sample size for your next study from a publication with nothing but p-values and Ns
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.
Blog Post
Innovative Designs in Early-Stage Studies
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.
Blog Post
Transitioning Trials Approved under the Clinical Trials Directive to the Clinical Trials Regulation and CTIS
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.
Blog Post
Planning for a Successful Centralised Marketing Authorisation Application in the European Union
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.
Blog Post
How Many Strata can my Randomized Clinical Trial have?
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.