The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
When planning a conventional trial, one can anticipate the drug supply necessary for the trial by determining how the number of patients reflected in the sample size will distribute across the trial sites. Implementing an adaptive trial, by contrast, raises many challenges for predicting the necessary drug supply. It can require planning for different sample sizes depending on the outcome of an interim look; or preparing different dosages if certain arms of a multi-arm trial are to drop after the interim look. In the case of a biomarker-driven adaptive design, determining adequate drug supply may require the ability to predict which doses are necessary for different subpopulations at particular trial sites.
When designing clinical trials, many trial designers are advised to keep the trial simple. Prima facie, the keep it simple principle seems like sound advice. There are various logistical uncertainties that arise when implementing a clinical trial, and the more simple a trial – so conventional wisdom says – the easier it is to respond to these uncertainties.
According to Zoran Antonijevic, a Senior Director at Cytel Consulting, there is reason to doubt such conventional wisdom. After all, flexibility is hardly a virtue of a traditional trial design. Simple designs may seem to make it easier to monitor data and report results. However, a flexible design can better address remaining uncertainties in product development. These uncertainties are related to treatment effect, dose selection, or a sub-population that would experience the best benefit/risk from the treatment.
Adaptive designs are the unsurprising hot topic of this year’s Joint Statistical Meeting, which features over one hundred and thirty sessions on the subject. Statisticians at Cytel look forward to contributing to the dialogue with two papers on adaptive designs, and a workshop for using simulations to benefit from interim data (i.e. for prediction and trial forecasting.) In addition, Cytel Senior Director & Consultant Jim Bolognese has organized a session on making use of adaptive designs to optimize strategy for drug development programs.
In the Ernst & Young 2014 Biotechnology Industry Report, Cytel CTO Nitin Patel writes: "Historically, biotechnology companies haven't fully appreciated the link between trial design and the ability to secure external financing. Yet, adaptive trial designs - which often reduce the risk, time and cost associated with clinical development - can make the math more attractive for investors." [Beyond Borders, p. 20].