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Basket designs are prospective clinical trials that are devised with the hypothesis that the presence of selected molecular features determine a patient's subsequent response to a particular "targeted" treatment strategy. Basket trials are…
The use of Bayesian adaptive designs for randomised controlled trials has been hindered by the lack of software readily available to statisticians. We have developed a new software package (Bayesian Adaptive Trials Simulator Software -…
We present a bayesassurance R package that computes the Bayesian assurance under various settings characterized by different assumptions and objectives. The package offers a constructive set of simulation-based functions suitable for…
Basket trials examine the efficacy of an intervention in multiple patient subgroups simultaneously. The division into subgroups, called baskets, is based on matching medical characteristics, which may result in small sample sizes within…
In basket trials a treatment is investigated in several subgroups. They are primarily used in oncology in early clinical phases as single-arm trials with a binary endpoint. For their analysis primarily Bayesian methods have been suggested,…
Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach to sample size determination in basket trials that permit…
Basket trials have gained increasing attention for their efficiency, as multiple patient subgroups are evaluated simultaneously. Conducted basket trials focus primarily on establishing the early efficacy of a treatment, yet continued…
Academic Clinical Trial Units frequently face fragmented statistical workflows, leading to duplicated effort, limited collaboration, and inconsistent analytical practices. To address these challenges within an oncology Clinical Trial Unit,…
We describe the R package acebayes and demonstrate its use to find Bayesian optimal experimental designs. A decision-theoretic approach is adopted, with the optimal design maximising an expected utility. Finding Bayesian optimal designs for…
Platform trials evaluate the efficacy of multiple treatments, allowing for late entry of the experimental arms and enabling efficiency gains by sharing controls. The power of individual treatment-control comparisons in such trials can be…
Therapeutic advancements in oncology have shifted towards targeted therapy based on genomic aberrations. This necessitates innovative statistical approaches in clinical trials, particularly in master protocol studies. Basket trials, a type…
Basket trials can efficiently evaluate a single treatment across multiple diseases with a common shared target. Prior methods for randomized basket trials required baskets to have the same sample and effect sizes. To that end, we developed…
Platform trials evaluate multiple experimental treatments against a common control group (and/or against each other), which often reduces the trial duration and sample size. Bayesian platform designs offer several practical advantages,…
Basket trials have emerged as a new class of efficient approaches in oncology to evaluate a new treatment in several patient subgroups simultaneously. In this paper, we extend the key ideas to disease areas outside of oncology, developing a…
Research in psychology generates interesting data sets and unique statistical modelling tasks. However, these tasks, while important, are often very specific, so appropriate statistical models and methods cannot be found in accessible…
Basket trials test a single therapeutic treatment on several patient populations under one master protocol. A desirable adaptive design feature in these studies may be the incorporation of new baskets to an ongoing study. Limited basket…
Observational studies are often conducted to estimate causal effects of treatments or exposures on event-time outcomes. Since treatments are not randomized in observational studies, techniques from causal inference are required to adjust…
Recent substantial advances of molecular targeted oncology drug development is requiring new paradigms for early-phase clinical trial methodologies to enable us to evaluate efficacy of several subtypes simultaneously and efficiently. The…
The Statistical Toolkit is an open source system specialized in the statistical comparison of distributions. It addresses requirements common to different experimental domains, such as simulation validation (e.g. comparison of experimental…
This paper proposes Bayesian Adaptive Trials (BAT) as both an efficient method to conduct trials and a unifying framework for evaluation social policy interventions, addressing limitations inherent in traditional methods such as Randomized…