Abstract Body

Real-world evidence (RWE) of a new therapy provides insights into whether or not results from relatively small and highly structured clinical trials can be generalized to a wider user and provider populations. While randomized controlled trials provide a standardized mean to isolate an attribute, so the effect of a single therapy, can be deduced, in real-world situation , myriad of interaction and differing care structures occur that effect outcomes. Analyzing RWE from large data bases can, therefore, provides a more realistic scenario to assess the outcomes of therapeutic interventions.

In this presentation, the use of RWE driven insights to drive therapy recommendation for the individual user of automated insulin delivery systems, and the care provider, will be demonstrated . Harnessing the objectively and unbiased collected data requires attention to technical, analytical and privacy issues to ensure data quality and analytic integrity. The limited individual data and challenges of anonymization of RWE will be discussed as well.

The clinical outcome effect of applying the insights from the prediction analysis of RWE, will be demonstrated in the case of the MiniMed™ 780G Advanced Hybrid Closed Loop (AHCL) system.