Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials.

Background: The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of health in daily living and a more granular and objective manner compared to traditional tools in clinical settings. Summary: Within multidisciplinary teams, statisticians and data scientists are increasingly involved in clinical trials that incorporate digital clinical measures. They are called upon to provide input into trial planning, generation of evidence on the clinical validity of novel clinical measures, and evaluation of the adequacy of existing evidence. Analysis objectives related to demonstrating clinical validity of novel clinical measures differ from typical objectives related to demonstrating safety and efficacy of therapeutic interventions using established measures which statisticians are most familiar with. Key Messages: This paper discusses key considerations for generating evidence for clinical validity through the lens of the type and intended use of a clinical measure. This paper also briefly discusses the regulatory pathways through which clinical validity evidence may be reviewed and highlights challenges that investigators may encounter while dealing with data from biometric monitoring technologies.

Minimizing Patient Burden Through the Use of Historical Subject-Level Data in Innovative Confirmatory Clinical Trials: Review of Methods and Opportunities.

The goal of clinical trial research is to deliver safe and efficacious new treatments to patients in need in a timely and cost-effective manner. There is precedent in using historical control data to reduce the number of concurrent control subjects required in developing medicines for rare diseases and other areas of unmet need. The purpose of this paper is to provide a review for a regulatory and industry audience of the current state of relevant statistical methods, and of the uptake of these approaches and the opportunities for broader use of historical data in confirmatory clinical trials. General principles to consider when incorporating historical control data in a new trial are presented. Bayesian and frequentist approaches are outlined including how the operating characteristics for such a trial can be obtained. Finally, examples of approved new treatments that incorporated historical controls in their confirmatory trials are presented.