Digital Therapeutic Based Randomized Investigation to Improve Glycemic Control in Patients With Type 2 Diabetes and Residual Hyperglycemia on Stable Medical Therapy: Rationale, Design, and Baseline Characteristics of the BRIGHT Trial.

Background: The prevalence of type 2 diabetes continues to rise in the United States and worldwide. Although novel pharmacotherapies have shown benefits, not all patients have access to these medications and of those who do, some are unable to tolerate treatment. Behavior change is long known to be foundational for patients with cardiometabolic disease due to its direct positive impact on health outcomes. Cognitive behavioral therapy delivered by a digital therapeutic has the potential to address access to behavioral therapy for patients with type 2 diabetes.

Methods: The BRIGHT (Digital Therapeutic Based Investigation to Improve Glycemic Control in Patients With Type 2 Diabetes and Residual Hyperglycemia on Stable Medical Therapy) Trial (NCT05266625) is a randomized, controlled, multicenter, pragmatic, pivotal trial with open-label extension evaluating the hypothesis that AspyreRx improves glycemic control and cardiometabolic measures in patients with type 2 diabetes compared with a control application added to usual care across a broad range of patients in a real-world setting. The current study objectives are to evaluate the efficacy and safety of AspyreRx at 90 and 180 days compared with a control group and to assess the long-term effectiveness, safety, and impact on health care and medication use over long-term follow up.

Conclusions: The AspyreRx digital therapeutic is a Food and Drug Administration approved therapy for patients with type 2 diabetes. Although its efficacy for lowering hemoglobin A1C at 90 days was demonstrated, opportunities remain to better understand the long-term effects and the effectiveness and safety in a broader and more diverse real-world environment. BRIGHT is designed to evaluate these questions using a virtual, decentralized, model and include a diverse site mix designed to better understand real-world effectiveness and generalizability.