Value-Adaptive Clinical Trial Designs for Efficient Delivery of Publicly Funded Trials - A Discussion of Methods, Case Studies, Opportunities and Challenges

Background: value-adaptive designs for clinical trials are a novel set of emerging methods for delivering greater value for clinical research. There is increasing interest in using them within publicly funded health systems. A value-adaptive design permits ‘in progress’ changes to be made to the trial according to criteria which reflect its overall value to the healthcare system, including the cost-effectiveness of the technologies under investigation, the cost of running the trial and the total health benefit delivered to patients. These trial designs offer the potential to explicitly balance the costs and benefits of adaptive clinical trials with the health economic benefits expected for populations that are affected by any subsequent health technology adoption decisions. They may also improve the expected value of learning from the budget that is spent within a trial. Main body: this paper introduces value-adaptive designs for publicly funded clinical trials. It discusses the idea of delivering ‘value for money’ in health technology assessment, what is meant by being ‘value-adaptive’ and the key features that characterise these designs. The methodology behind one kind of value-adaptive design - the value-based sequential model of a two-armed clinical trial proposed by Chick et al. (2017) – is described and illustrated using three retrospective case studies from the United Kingdom. The paper concludes by reviewing a range of perspectives provided by stakeholders, together with our own thoughts, on the practical opportunities and changes required for implementing a value-adaptive approach. Conclusions: value-adaptive clinical trial designs offer the potential to align health research funding allocations with population health economic goals. Many of the systems required to deploy value-adaptive designs within a publicly funded health system already exist and, with increased application, experience, and refinement they have the potential to deliver improved value for money.