14: External data sources and their utilization in the clinical environment: past, present and future

Music City Center 

In the past couple of years, the Clinical Research outlook has evolved, including rising costs for developing new treatments. This has led the industry to look for new innovations to help alleviate these costs, without the risk of losing scientific reliability. A few that I will be looking at, but not limited to, will include real-world data / real-world evidence and natural history studies. These discussions will include the benefits, pitfalls and unique considerations associated with each of these, as well as the stance that regulatory authorities currently have towards them. Each of these new innovations include their own different statistical methodology considerations to take into account. I will also look at some real examples where such sources were used in the industry thus far (the good, the bad and the ugly). Lastly, I will discuss what this could imply for the future and the practicing statistician. 

Real-World Data / Real-World Evidence

Purpose and utilization of natural history studies (i.e. external controls, and retrospective and prospective studies).

Sensitivity/covariate analysis between external data and recruited controls.

Doubly debiased machine learning to estimate average treatment effect (ATE)

The stratification score estimated probability of the outcome given potential confounders matching of external controls to mimic internal controls. 

Biometrics Section