Clinical trials impacted by the COVID-19 pandemic: Adaptive designs to the rescue?

TL;DR

This paper discusses the impact of COVID-19 on clinical trials and proposes adaptive design strategies, including Bayesian methods and early readouts, to address pandemic-related challenges while ensuring trial integrity.

Contribution

It introduces adaptive design approaches tailored for pandemic-affected trials, providing practical guidance and an accessible R shiny app implementation.

Findings

Adaptive designs help maintain trial validity during disruptions

Bayesian techniques facilitate flexible decision-making

Methods are implemented in a freely available R shiny app

Abstract

Very recently the new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified and the coronavirus disease 2019 (COVID-19) declared a pandemic by the World Health Organization. The pandemic has a number of consequences for the ongoing clinical trials in non-COVID-19 conditions. Motivated by four currently ongoing clinical trials in a variety of disease areas we illustrate the challenges faced by the pandemic and sketch out possible solutions including adaptive designs. Guidance is provided on (i) where blinded adaptations can help; (ii) how to achieve type I error rate control, if required; (iii) how to deal with potential treatment effect heterogeneity; (iv) how to utilize early readouts; and (v) how to utilize Bayesian techniques. In more detail approaches to resizing a trial affected by the pandemic are developed including considerations to stop a trial early, the use of group-sequential designs or sample size adjustment. All methods considered are implemented in a freely available R shiny app. Furthermore, regulatory and operational issues including the role of data monitoring committees are discussed.