Innovative Methods for Research and Trial Design using Value of Information

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Clinical trials test the effects, risks and benefits of medical treatments in people and are required before new treatments can be recommended for use in the Canadian healthcare system. As clinical trials are expensive and time consuming, they must be designed properly to ensure that the information collected during the trial will help doctors and policymakers to find the best treatment for patients. Value of Information (VoI) is a proposed method to design research that offers value-for-money and can select the best treatment. This ensures that the information collected during clinical trials supports doctors and policymakers to make decisions about treatments and maximizes the impact of clinical trials. Currently, VoI is more complex, time consuming and costly than standard research design methods, which means that it has not been used in practice. My previous research developed new statistical methods to reduce the time required to use VoI methods. Thus, this project will build on that work to develop statistical methods that continue to reduce the complexity of using VoI in the real world. In the short-term, this will focus on three key areas; i) applying VoI to realistic clinical trials, ii) using VoI to design clinical trials that change their conduct based on data collected during the trial, known as adaptive trials, and iii) improving the use of VoI when there is very limited evidence. As current research has focused on reducing the time taken to compute VoI, there is limited research on how to apply these methods to real-life clinical trials. Recently guidelines for VoI have highlighted the importance of considering more realistic trials but there is a gap in knowledge about how this can be achieved, which will be filled. Adaptive trials are often more efficient, ethical and informative than standard trials but they take more time to design, particularly when using VoI methods. This project will develop new statistical methods to reduce this time and allow VoI to be used to improve the efficiency of adaptive trials. Finally, trials are usually designed to collect more information when only a limited amount of data has been collected previously. In theory, VoI can still be used in these "data-poor" settings but we need new methods to understand how limited information influences decision making so VoI can accurately prioritize research. The overall goal of this project is to increase the use of VoI in clinical trial design. Alongside the short-term objectives, I will translate VoI into a feasible method for trial design by i) training highly qualified professionals to use VoI and develop new methods, ii) developing code and guidance to help other researchers use VoI and iii) collaborating with colleagues to implement VoI in practice. This will improve the use of VoI in trial design, ensuring that research is relevant to key decision makers and significantly increasing returns from research funding investment.