Real-World Evidence and Adaptive Clinical Trials

The future of clinical research is shifting trials from academic medical centers and into community settings.

Patients can be identified through the electronic health record (EHR) after diagnosis in outpatient clinics and regional hospitals. The EHR flags the eligible patient, prompting the doctor and patient to consider enrolling in an intervention trial for a new therapy. A research coordinator then contacts the patient and family to obtain consent.

Participants are randomized to treatment (A, B, C) or placebo. Outcomes are continuously monitored by blinded artificial intelligence protocols that assess pre-specified efficacy outcomes in the EHR such as organ function, survival, or hospitalization rates. If one treatment demonstrates superior performance, the trial adaptively randomizes more patients to that treatment, thus reducing exposure to less effective treatments. Once a treatment is found to be statistically superior, the trial is automatically stopped. 

Examples include the REMAP-CAP clinical trials group which adaptively randomized patients with SARS-CoV2 in hundreds of regional hospitals and rapidly established the efficacy of hydrocortisone, anti-IL6, and heparinization, improving mortality during severe COVID-19 pneumonia.