Accelerating Clinical Evaluation of Repurposed Combination Therapies for COVID-19

Abstract

As the global COVID-19 pandemic continues, unabated and clinical trials demonstrate limited effective pharmaceutical interventions, there is a pressing need to accelerate treatment evaluations. Among options for accelerated development is the evaluation of drug combinations in the absence of prior monotherapy data. This approach is appealing for a number of reasons. First, combining two or more drugs with related or complementary therapeutic effects permits a multipronged approach addressing the variable pathways of the disease. Second, if an individual component of a combination offers a therapeutic effect, then in the absence of antagonism, a trial of combination therapy should still detect individual efficacy. Third, this strategy is time saving. Rather than taking a stepwise approach to evaluating monotherapies, this strategy begins with testing all relevant therapeutic options. Finally, given the severity of the current pandemic and the absence of treatment options, the likelihood of detecting a treatment effect with combination therapy maintains scientific enthusiasm for evaluating repurposed treatments. Antiviral combination selection can be facilitated by insights regarding SARS-CoV-2 pathophysiology and cell cycle dynamics, supported by infectious disease and clinical pharmacology expert advice. We describe a clinical evaluation strategy using adaptive combination platform trials to rapidly test combination therapies to treat COVID-19.

Figure 1.

A platform trial for combination therapy. Here, in this example, there are several interim analyses planned for the platform trial testing combination therapies using a backward stepwise approach. At the first interim analysis, combination arm 1 is dropped for futility followed by combination arm 2 dropped at the second interim analysis. At the third interim analysis, combination arm 3 shows superiority over placebo (PBO), and, thereafter, individual monotherapies are added and evaluated after.