Specialising in the development of improved designs for clinical trials
Traditional phase III randomised trials often require large numbers of patients, take a long time, and cost many millions of pounds. The Design programme aims to improve the efficiency and resilience of randomised trials by proposing new trial designs. Efficiency is the ability to identify a treatment effect (or lack of effect) quickly with best use of resources. Resilience is the ability to reach credible answers when design assumptions turn out to be inaccurate.
We specialise in the development of improved designs for clinical trials and related study types, to enable rapid, efficient, and better evaluation of therapies. New design methodology usually requires new software, and we provide user-friendly software packages for internal and external use. We also improve some existing trial designs in a similar manner.
Our Main Areas of Work:
Durations design and non-inferiority trials
We are developing ways to choose a shortened treatment regimen (the Durations Design), and ways to address particular problems that occur in sensitivity to non-adherence and to small changes in the control event rate. Non-inferiority trials are widely used and are often the best way to improve outcomes, especially in tuberculosis and anti-microbial resistance. However, they are hard to implement and often lacking in resilience.
Multi-arm, multi-stage (MAMS) platform trials
To speed up the evaluation of new therapies and improve success rates in identifying effective ones, we pioneered the development and implementation of the MAMS design and wrote the nstage software suite in Stata for sample size calculation.
A MAMS platform trial generally has a single master protocol in which multiple treatments are evaluated over time, and offers flexible features such as early stopping of accrual to treatments for lack of benefit, and adding new treatments to be tested during the course of a trial.
We have several years of practical experience in design and conduct of such trials. We are inventing new and more efficient ways to design MAMS trials.
We have developed advanced methods of designing trials with time-to-event outcomes, where the sample size, power and analysis timings are estimated while taking into account complex factors such as non-proportional hazards, loss-to-follow-up, and treatment changes.
Trials with a time-to-event outcome are usually designed and analysed assuming the treatment effect remains stable over time (proportional hazards). However, non-proportional hazards (non-PH) is more common than previously thought, e.g. due to therapy ‘wearing off’ or taking time to work. If unrecognised and unaccommodated, non-PH may impact the success or failure of a trial. We are developing ways to design trials to anticipate possible non-PH.
Cluster-randomised and stepped-wedge trials
These are designs where clusters of individuals are randomised to treatment or control. We are developing methods to optimise the design of these trials by minimising the number of clusters and/or measurements required, and also to show new ways to understand these trials.
Trials for stratified medicine
Here our focus is on understanding how to design a trial when a treatment is suspected to work best in a particular subgroup, but this knowledge is not secure and may evolve during the trial.
The new “PRACTical” trial design
In some trials, where a number of treatments are available, due to other medical conditions some of the patients cannot receive some of the treatments. We are developing suitable ways to design and analyse such a trial.
We also have expertise in the methodology of non-inferiority trial designs, stratified medicine trial designs, accounting for missing data at the design stage, multiple primary outcomes, and many other design-related questions.