The IMPaCT (Innovative Methods in Paediatric Clinical Trials) lab, led by Dr. Anna Heath, aims to improve the conception, design and conduct of paediatric clinical trials through the development of novel statistical methodology, software, expertise and guidance. Paediatric trials face significant challenges including limits to the number of patients who can be recruited, ethical concerns and the substantial differences in children across the childhood. By creating bespoke trial designs in paediatrics, we aim to tackle these issues and improve the evidence base for paediatric medicine. Our proposed trial designs can also be used for adult studies that suffer from the similar challenges such as restricted sample sizes and differences between patients.
Primarily, the team focuses on two interconnected methodologies:
1. Bayesian Statistics
Bayesian inference provides an alternative framework for drawing insights from data, compared to the standard “frequentist” approach. Recently, Bayesian methods have been gaining popularity in clinical trials, helped by increases in computational power and the flexibility of Bayesian trials to respond quickly, such as during the Covid-19 pandemic. Bayesian clinical trials are a particularly powerful tool for innovative trials and are commonly used for adaptive and platform trials. They are also useful for rare diseases as expert judgements can formally be incorporated into the analysis where data are limited.
2. Value of Information
Value of Information, first defined in 1959, uses Bayesian statistics and statistical decision theory to design research that support decision making. These methods have been most commonly explored alongside health economic modelling to calculate the monetary or health benefit associated with research. The goal of using Value of Information methods in paediatric clinical trials is to maximize the impact of clinical research by prioritizing research with high value. The IMPaCT lab works on both theoretical and applied projects to improve the use of Value of Information and integrate its use in the “evidence collection”-“decision-making” cycle displayed on this page.
More information about our approach can be found on our project-specific pages.